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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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This commit is contained in:
Alexander Alekhin 2019-03-11 19:20:22 +00:00
commit 8c0b0714e7
48 changed files with 7633 additions and 5337 deletions
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4
modules/core/include/opencv2/core/cv_cpu_dispatch.h
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@ -124,6 +124,10 @@
#if defined CV_CPU_COMPILE_AVX && !defined CV_CPU_BASELINE_COMPILE_AVX
struct VZeroUpperGuard {
#ifdef __GNUC__
__attribute__((always_inline))
#endif
inline VZeroUpperGuard() { _mm256_zeroupper(); }
#ifdef __GNUC__
__attribute__((always_inline))
#endif

6
modules/core/include/opencv2/core/hal/intrin_neon.hpp
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@ -1202,14 +1202,16 @@ OPENCV_HAL_IMPL_NEON_EXPAND(v_int32x4, v_int64x2, int, s32)
inline v_uint32x4 v_load_expand_q(const uchar* ptr)
{
uint8x8_t v0 = vcreate_u8(*(unsigned*)ptr);
typedef unsigned int CV_DECL_ALIGNED(1) unaligned_uint;
uint8x8_t v0 = vcreate_u8(*(unaligned_uint*)ptr);
uint16x4_t v1 = vget_low_u16(vmovl_u8(v0));
return v_uint32x4(vmovl_u16(v1));
}
inline v_int32x4 v_load_expand_q(const schar* ptr)
{
int8x8_t v0 = vcreate_s8(*(unsigned*)ptr);
typedef unsigned int CV_DECL_ALIGNED(1) unaligned_uint;
int8x8_t v0 = vcreate_s8(*(unaligned_uint*)ptr);
int16x4_t v1 = vget_low_s16(vmovl_s8(v0));
return v_int32x4(vmovl_s16(v1));
}

4
modules/core/include/opencv2/core/private.hpp
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@ -789,9 +789,9 @@ CV_EXPORTS InstrNode* getCurrentNode();
#endif
#ifdef __CV_AVX_GUARD
#define CV_INSTRUMENT_REGION(); __CV_AVX_GUARD CV_INSTRUMENT_REGION_();
#define CV_INSTRUMENT_REGION() __CV_AVX_GUARD CV_INSTRUMENT_REGION_();
#else
#define CV_INSTRUMENT_REGION(); CV_INSTRUMENT_REGION_();
#define CV_INSTRUMENT_REGION() CV_INSTRUMENT_REGION_();
#endif
namespace cv {

342
modules/core/misc/java/src/java/core+Mat.java
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@ -67,6 +67,19 @@ public class Mat {
return;
}
//
// C++: Mat::Mat(int ndims, const int* sizes, int type)
//
// javadoc: Mat::Mat(sizes, type)
public Mat(int[] sizes, int type)
{
nativeObj = n_Mat(sizes.length, sizes, type);
return;
}
//
// C++: Mat::Mat(int rows, int cols, int type, Scalar s)
//
@ -93,6 +106,19 @@ public class Mat {
return;
}
//
// C++: Mat::Mat(int ndims, const int* sizes, int type, Scalar s)
//
// javadoc: Mat::Mat(sizes, type, s)
public Mat(int[] sizes, int type, Scalar s)
{
nativeObj = n_Mat(sizes.length, sizes, type, s.val[0], s.val[1], s.val[2], s.val[3]);
return;
}
//
// C++: Mat::Mat(Mat m, Range rowRange, Range colRange = Range::all())
//
@ -115,6 +141,19 @@ public class Mat {
return;
}
//
// C++: Mat::Mat(const Mat& m, const std::vector<Range>& ranges)
//
// javadoc: Mat::Mat(m, ranges)
public Mat(Mat m, Range[] ranges)
{
nativeObj = n_Mat(m.nativeObj, ranges);
return;
}
//
// C++: Mat::Mat(Mat m, Rect roi)
//
@ -370,6 +409,31 @@ public class Mat {
return;
}
//
// C++: void Mat::create(int ndims, const int* sizes, int type)
//
// javadoc: Mat::create(sizes, type)
public void create(int[] sizes, int type)
{
n_create(nativeObj, sizes.length, sizes, type);
return;
}
//
// C++: void Mat::copySize(const Mat& m);
//
// javadoc: Mat::copySize(m)
public void copySize(Mat m)
{
n_copySize(nativeObj, m.nativeObj);
return;
}
//
// C++: Mat Mat::cross(Mat m)
//
@ -633,6 +697,19 @@ public class Mat {
return retVal;
}
//
// C++: static Mat Mat::ones(int ndims, const int* sizes, int type)
//
// javadoc: Mat::ones(sizes, type)
public static Mat ones(int[] sizes, int type)
{
Mat retVal = new Mat(n_ones(sizes.length, sizes, type));
return retVal;
}
//
// C++: void Mat::push_back(Mat m)
//
@ -867,6 +944,19 @@ public class Mat {
return retVal;
}
//
// C++: Mat Mat::operator()(const std::vector<Range>& ranges)
//
// javadoc: Mat::operator()(ranges[])
public Mat submat(Range[] ranges)
{
Mat retVal = new Mat(n_submat_ranges(nativeObj, ranges));
return retVal;
}
//
// C++: Mat Mat::operator()(Rect roi)
//
@ -945,6 +1035,19 @@ public class Mat {
return retVal;
}
//
// C++: static Mat Mat::zeros(int ndims, const int* sizes, int type)
//
// javadoc: Mat::zeros(sizes, type)
public static Mat zeros(int[] sizes, int type)
{
Mat retVal = new Mat(n_zeros(sizes.length, sizes, type));
return retVal;
}
@Override
protected void finalize() throws Throwable {
n_delete(nativeObj);
@ -979,6 +1082,20 @@ public class Mat {
return nPutD(nativeObj, row, col, data.length, data);
}
// javadoc:Mat::put(idx,data)
public int put(int[] idx, double... data) {
int t = type();
if (data == null || data.length % CvType.channels(t) != 0)
throw new java.lang.UnsupportedOperationException(
"Provided data element number (" +
(data == null ? 0 : data.length) +
") should be multiple of the Mat channels count (" +
CvType.channels(t) + ")");
if (idx.length != dims())
throw new IllegalArgumentException("Incorrect number of indices");
return nPutDIdx(nativeObj, idx, data.length, data);
}
// javadoc:Mat::put(row,col,data)
public int put(int row, int col, float[] data) {
int t = type();
@ -994,6 +1111,23 @@ public class Mat {
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::put(idx,data)
public int put(int[] idx, float[] data) {
int t = type();
if (data == null || data.length % CvType.channels(t) != 0)
throw new java.lang.UnsupportedOperationException(
"Provided data element number (" +
(data == null ? 0 : data.length) +
") should be multiple of the Mat channels count (" +
CvType.channels(t) + ")");
if (idx.length != dims())
throw new IllegalArgumentException("Incorrect number of indices");
if (CvType.depth(t) == CvType.CV_32F) {
return nPutFIdx(nativeObj, idx, data.length, data);
}
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::put(row,col,data)
public int put(int row, int col, int[] data) {
int t = type();
@ -1009,6 +1143,23 @@ public class Mat {
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::put(idx,data)
public int put(int[] idx, int[] data) {
int t = type();
if (data == null || data.length % CvType.channels(t) != 0)
throw new java.lang.UnsupportedOperationException(
"Provided data element number (" +
(data == null ? 0 : data.length) +
") should be multiple of the Mat channels count (" +
CvType.channels(t) + ")");
if (idx.length != dims())
throw new IllegalArgumentException("Incorrect number of indices");
if (CvType.depth(t) == CvType.CV_32S) {
return nPutIIdx(nativeObj, idx, data.length, data);
}
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::put(row,col,data)
public int put(int row, int col, short[] data) {
int t = type();
@ -1024,6 +1175,23 @@ public class Mat {
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::put(idx,data)
public int put(int[] idx, short[] data) {
int t = type();
if (data == null || data.length % CvType.channels(t) != 0)
throw new java.lang.UnsupportedOperationException(
"Provided data element number (" +
(data == null ? 0 : data.length) +
") should be multiple of the Mat channels count (" +
CvType.channels(t) + ")");
if (idx.length != dims())
throw new IllegalArgumentException("Incorrect number of indices");
if (CvType.depth(t) == CvType.CV_16U || CvType.depth(t) == CvType.CV_16S) {
return nPutSIdx(nativeObj, idx, data.length, data);
}
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::put(row,col,data)
public int put(int row, int col, byte[] data) {
int t = type();
@ -1039,6 +1207,23 @@ public class Mat {
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::put(idx,data)
public int put(int[] idx, byte[] data) {
int t = type();
if (data == null || data.length % CvType.channels(t) != 0)
throw new java.lang.UnsupportedOperationException(
"Provided data element number (" +
(data == null ? 0 : data.length) +
") should be multiple of the Mat channels count (" +
CvType.channels(t) + ")");
if (idx.length != dims())
throw new IllegalArgumentException("Incorrect number of indices");
if (CvType.depth(t) == CvType.CV_8U || CvType.depth(t) == CvType.CV_8S) {
return nPutBIdx(nativeObj, idx, data.length, data);
}
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::put(row,col,data,offset,length)
public int put(int row, int col, byte[] data, int offset, int length) {
int t = type();
@ -1054,6 +1239,23 @@ public class Mat {
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::put(idx,data,offset,length)
public int put(int[] idx, byte[] data, int offset, int length) {
int t = type();
if (data == null || length % CvType.channels(t) != 0)
throw new java.lang.UnsupportedOperationException(
"Provided data element number (" +
(data == null ? 0 : data.length) +
") should be multiple of the Mat channels count (" +
CvType.channels(t) + ")");
if (idx.length != dims())
throw new IllegalArgumentException("Incorrect number of indices");
if (CvType.depth(t) == CvType.CV_8U || CvType.depth(t) == CvType.CV_8S) {
return nPutBwIdxOffset(nativeObj, idx, length, offset, data);
}
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::get(row,col,data)
public int get(int row, int col, byte[] data) {
int t = type();
@ -1069,6 +1271,23 @@ public class Mat {
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::get(idx,data)
public int get(int[] idx, byte[] data) {
int t = type();
if (data == null || data.length % CvType.channels(t) != 0)
throw new java.lang.UnsupportedOperationException(
"Provided data element number (" +
(data == null ? 0 : data.length) +
") should be multiple of the Mat channels count (" +
CvType.channels(t) + ")");
if (idx.length != dims())
throw new IllegalArgumentException("Incorrect number of indices");
if (CvType.depth(t) == CvType.CV_8U || CvType.depth(t) == CvType.CV_8S) {
return nGetBIdx(nativeObj, idx, data.length, data);
}
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::get(row,col,data)
public int get(int row, int col, short[] data) {
int t = type();
@ -1084,6 +1303,23 @@ public class Mat {
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::get(idx,data)
public int get(int[] idx, short[] data) {
int t = type();
if (data == null || data.length % CvType.channels(t) != 0)
throw new java.lang.UnsupportedOperationException(
"Provided data element number (" +
(data == null ? 0 : data.length) +
") should be multiple of the Mat channels count (" +
CvType.channels(t) + ")");
if (idx.length != dims())
throw new IllegalArgumentException("Incorrect number of indices");
if (CvType.depth(t) == CvType.CV_16U || CvType.depth(t) == CvType.CV_16S) {
return nGetSIdx(nativeObj, idx, data.length, data);
}
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::get(row,col,data)
public int get(int row, int col, int[] data) {
int t = type();
@ -1099,6 +1335,23 @@ public class Mat {
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::get(idx,data)
public int get(int[] idx, int[] data) {
int t = type();
if (data == null || data.length % CvType.channels(t) != 0)
throw new java.lang.UnsupportedOperationException(
"Provided data element number (" +
(data == null ? 0 : data.length) +
") should be multiple of the Mat channels count (" +
CvType.channels(t) + ")");
if (idx.length != dims())
throw new IllegalArgumentException("Incorrect number of indices");
if (CvType.depth(t) == CvType.CV_32S) {
return nGetIIdx(nativeObj, idx, data.length, data);
}
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::get(row,col,data)
public int get(int row, int col, float[] data) {
int t = type();
@ -1114,6 +1367,23 @@ public class Mat {
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::get(idx,data)
public int get(int[] idx, float[] data) {
int t = type();
if (data == null || data.length % CvType.channels(t) != 0)
throw new java.lang.UnsupportedOperationException(
"Provided data element number (" +
(data == null ? 0 : data.length) +
") should be multiple of the Mat channels count (" +
CvType.channels(t) + ")");
if (idx.length != dims())
throw new IllegalArgumentException("Incorrect number of indices");
if (CvType.depth(t) == CvType.CV_32F) {
return nGetFIdx(nativeObj, idx, data.length, data);
}
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::get(row,col,data)
public int get(int row, int col, double[] data) {
int t = type();
@ -1129,11 +1399,35 @@ public class Mat {
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::get(idx,data)
public int get(int[] idx, double[] data) {
int t = type();
if (data == null || data.length % CvType.channels(t) != 0)
throw new java.lang.UnsupportedOperationException(
"Provided data element number (" +
(data == null ? 0 : data.length) +
") should be multiple of the Mat channels count (" +
CvType.channels(t) + ")");
if (idx.length != dims())
throw new IllegalArgumentException("Incorrect number of indices");
if (CvType.depth(t) == CvType.CV_64F) {
return nGetDIdx(nativeObj, idx, data.length, data);
}
throw new java.lang.UnsupportedOperationException("Mat data type is not compatible: " + t);
}
// javadoc:Mat::get(row,col)
public double[] get(int row, int col) {
return nGet(nativeObj, row, col);
}
// javadoc:Mat::get(idx)
public double[] get(int[] idx) {
if (idx.length != dims())
throw new IllegalArgumentException("Incorrect number of indices");
return nGetIdx(nativeObj, idx);
}
// javadoc:Mat::height()
public int height() {
return rows();
@ -1155,6 +1449,9 @@ public class Mat {
// C++: Mat::Mat(int rows, int cols, int type)
private static native long n_Mat(int rows, int cols, int type);
// C++: Mat::Mat(int ndims, const int* sizes, int type)
private static native long n_Mat(int ndims, int[] sizes, int type);
// C++: Mat::Mat(int rows, int cols, int type, void* data)
private static native long n_Mat(int rows, int cols, int type, ByteBuffer data);
@ -1167,11 +1464,17 @@ public class Mat {
// C++: Mat::Mat(Size size, int type, Scalar s)
private static native long n_Mat(double size_width, double size_height, int type, double s_val0, double s_val1, double s_val2, double s_val3);
// C++: Mat::Mat(int ndims, const int* sizes, int type, Scalar s)
private static native long n_Mat(int ndims, int[] sizes, int type, double s_val0, double s_val1, double s_val2, double s_val3);
// C++: Mat::Mat(Mat m, Range rowRange, Range colRange = Range::all())
private static native long n_Mat(long m_nativeObj, int rowRange_start, int rowRange_end, int colRange_start, int colRange_end);
private static native long n_Mat(long m_nativeObj, int rowRange_start, int rowRange_end);
// C++: Mat::Mat(const Mat& m, const std::vector<Range>& ranges)
private static native long n_Mat(long m_nativeObj, Range[] ranges);
// C++: Mat Mat::adjustROI(int dtop, int dbottom, int dleft, int dright)
private static native long n_adjustROI(long nativeObj, int dtop, int dbottom, int dleft, int dright);
@ -1226,6 +1529,12 @@ public class Mat {
// C++: void Mat::create(Size size, int type)
private static native void n_create(long nativeObj, double size_width, double size_height, int type);
// C++: void Mat::create(int ndims, const int* sizes, int type)
private static native void n_create(long nativeObj, int ndims, int[] sizes, int type);
// C++: void Mat::copySize(const Mat& m)
private static native void n_copySize(long nativeObj, long m_nativeObj);
// C++: Mat Mat::cross(Mat m)
private static native long n_cross(long nativeObj, long m_nativeObj);
@ -1284,6 +1593,9 @@ public class Mat {
// C++: static Mat Mat::ones(Size size, int type)
private static native long n_ones(double size_width, double size_height, int type);
// C++: static Mat Mat::ones(int ndims, const int* sizes, int type)
private static native long n_ones(int ndims, int[] sizes, int type);
// C++: void Mat::push_back(Mat m)
private static native void n_push_back(long nativeObj, long m_nativeObj);
@ -1332,6 +1644,9 @@ public class Mat {
// C++: Mat Mat::operator()(Range rowRange, Range colRange)
private static native long n_submat_rr(long nativeObj, int rowRange_start, int rowRange_end, int colRange_start, int colRange_end);
// C++: Mat Mat::operator()(const std::vector<Range>& ranges)
private static native long n_submat_ranges(long nativeObj, Range[] ranges);
// C++: Mat Mat::operator()(Rect roi)
private static native long n_submat(long nativeObj, int roi_x, int roi_y, int roi_width, int roi_height);
@ -1350,32 +1665,59 @@ public class Mat {
// C++: static Mat Mat::zeros(Size size, int type)
private static native long n_zeros(double size_width, double size_height, int type);
// C++: static Mat Mat::zeros(int ndims, const int* sizes, int type)
private static native long n_zeros(int ndims, int[] sizes, int type);
// native support for java finalize()
private static native void n_delete(long nativeObj);
private static native int nPutD(long self, int row, int col, int count, double[] data);
private static native int nPutDIdx(long self, int[] idx, int count, double[] data);
private static native int nPutF(long self, int row, int col, int count, float[] data);
private static native int nPutFIdx(long self, int[] idx, int count, float[] data);
private static native int nPutI(long self, int row, int col, int count, int[] data);
private static native int nPutIIdx(long self, int[] idx, int count, int[] data);
private static native int nPutS(long self, int row, int col, int count, short[] data);
private static native int nPutSIdx(long self, int[] idx, int count, short[] data);
private static native int nPutB(long self, int row, int col, int count, byte[] data);
private static native int nPutBIdx(long self, int[] idx, int count, byte[] data);
private static native int nPutBwOffset(long self, int row, int col, int count, int offset, byte[] data);
private static native int nPutBwIdxOffset(long self, int[] idx, int count, int offset, byte[] data);
private static native int nGetB(long self, int row, int col, int count, byte[] vals);
private static native int nGetBIdx(long self, int[] idx, int count, byte[] vals);
private static native int nGetS(long self, int row, int col, int count, short[] vals);
private static native int nGetSIdx(long self, int[] idx, int count, short[] vals);
private static native int nGetI(long self, int row, int col, int count, int[] vals);
private static native int nGetIIdx(long self, int[] idx, int count, int[] vals);
private static native int nGetF(long self, int row, int col, int count, float[] vals);
private static native int nGetFIdx(long self, int[] idx, int count, float[] vals);
private static native int nGetD(long self, int row, int col, int count, double[] vals);
private static native int nGetDIdx(long self, int[] idx, int count, double[] vals);
private static native double[] nGet(long self, int row, int col);
private static native double[] nGetIdx(long self, int[] idx);
private static native String nDump(long self);
}

219
modules/core/misc/java/test/MatTest.java
View File

@ -185,6 +185,16 @@ public class MatTest extends OpenCVTestCase {
assertEquals(CvType.CV_16U, dst.type());
}
public void testCreateIntArrayInt() {
int[] dims = new int[] {5, 6, 7};
dst.create(dims, CvType.CV_16U);
assertEquals(5, dst.size(0));
assertEquals(6, dst.size(1));
assertEquals(7, dst.size(2));
assertEquals(CvType.CV_16U, dst.type());
}
public void testCross() {
Mat answer = new Mat(1, 3, CvType.CV_32F);
answer.put(0, 0, 7.0, 1.0, -5.0);
@ -569,6 +579,15 @@ public class MatTest extends OpenCVTestCase {
assertMatEqual(truth, dst, EPS);
}
public void testMatMatRangeArray() {
dst = new Mat(gray255_32f_3d, new Range[]{new Range(0, 5), new Range(0, 5), new Range(0, 5)});
truth = new Mat(new int[] {5, 5, 5}, CvType.CV_32FC1, new Scalar(255));
assertFalse(dst.empty());
assertMatEqual(truth, dst, EPS);
}
public void testMatMatRect() {
Mat m = new Mat(7, 6, CvType.CV_32SC1);
m.put(0, 0,
@ -606,6 +625,13 @@ public class MatTest extends OpenCVTestCase {
assertMatEqual(gray255_32f, dst, EPS);
}
public void testMatIntArrayIntScalar() {
dst = new Mat(new int[]{10, 10, 10}, CvType.CV_32F, new Scalar(255));
assertFalse(dst.empty());
assertMatEqual(gray255_32f_3d, dst, EPS);
}
public void testMulMat() {
assertMatEqual(gray0, gray0.mul(gray255));
@ -619,6 +645,16 @@ public class MatTest extends OpenCVTestCase {
}
public void testMulMat3d() {
Mat m1 = new Mat(new int[] {2, 2, 2}, CvType.CV_32F, new Scalar(2));
Mat m2 = new Mat(new int[] {2, 2, 2}, CvType.CV_32F, new Scalar(3));
dst = m1.mul(m2);
truth = new Mat(new int[] {2, 2, 2}, CvType.CV_32F, new Scalar(6));
assertMatEqual(truth, dst, EPS);
}
public void testMulMatDouble() {
Mat m1 = new Mat(2, 2, CvType.CV_32F, new Scalar(2));
Mat m2 = new Mat(2, 2, CvType.CV_32F, new Scalar(3));
@ -642,6 +678,12 @@ public class MatTest extends OpenCVTestCase {
assertMatEqual(truth, dst);
}
public void testOnesIntArrayInt() {
dst = Mat.ones(new int[]{2, 2, 2}, CvType.CV_16S);
truth = new Mat(new int[]{2, 2, 2}, CvType.CV_16S, new Scalar(1));
assertMatEqual(truth, dst);
}
public void testPush_back() {
Mat m1 = new Mat(2, 4, CvType.CV_32F, new Scalar(2));
Mat m2 = new Mat(3, 4, CvType.CV_32F, new Scalar(3));
@ -699,6 +741,46 @@ public class MatTest extends OpenCVTestCase {
}
}
public void testPutIntArrayByteArray() {
Mat m = new Mat(new int[]{5, 5, 5}, CvType.CV_8UC3, new Scalar(1, 2, 3));
Mat sm = m.submat(new Range[]{ new Range(0, 2), new Range(1, 3), new Range(2, 4)});
byte[] buff = new byte[] { 0, 0, 0, 0, 0, 0 };
byte[] buff0 = new byte[] { 10, 20, 30, 40, 50, 60 };
byte[] buff1 = new byte[] { -1, -2, -3, -4, -5, -6 };
int bytesNum = m.put(new int[]{1, 2, 0}, buff0);
assertEquals(6, bytesNum);
bytesNum = m.get(new int[]{1, 2, 0}, buff);
assertEquals(6, bytesNum);
assertTrue(Arrays.equals(buff, buff0));
bytesNum = sm.put(new int[]{0, 0, 0}, buff1);
assertEquals(6, bytesNum);
bytesNum = sm.get(new int[]{0, 0, 0}, buff);
assertEquals(6, bytesNum);
assertTrue(Arrays.equals(buff, buff1));
bytesNum = m.get(new int[]{0, 1, 2}, buff);
assertEquals(6, bytesNum);
assertTrue(Arrays.equals(buff, buff1));
Mat m1 = m.submat(new Range[]{ new Range(1,2), Range.all(), Range.all() });
bytesNum = m1.get(new int[]{ 0, 2, 0}, buff);
assertEquals(6, bytesNum);
assertTrue(Arrays.equals(buff, buff0));
try {
byte[] bytes2 = new byte[] { 10, 20, 30, 40, 50 };
m.put(new int[]{ 2, 2, 0 }, bytes2);
fail("Expected UnsupportedOperationException (data.length % CvType.channels(t) != 0)");
} catch (UnsupportedOperationException e) {
// expected
}
}
public void testPutIntIntDoubleArray() {
Mat m = new Mat(5, 5, CvType.CV_8UC3, new Scalar(1, 2, 3));
Mat sm = m.submat(2, 4, 3, 5);
@ -722,6 +804,29 @@ public class MatTest extends OpenCVTestCase {
assertTrue(Arrays.equals(buff, new byte[]{-1, -2, -3, -4, -5, -6}));
}
public void testPutIntArrayDoubleArray() {
Mat m = new Mat(new int[]{5, 5, 5}, CvType.CV_8UC3, new Scalar(1, 2, 3));
Mat sm = m.submat(new Range[]{ new Range(0, 2), new Range(1, 3), new Range(2, 4)});
byte[] buff = new byte[] { 0, 0, 0, 0, 0, 0 };
int bytesNum = m.put(new int[]{1, 2, 0}, 10, 20, 30, 40, 50, 60);
assertEquals(6, bytesNum);
bytesNum = m.get(new int[]{1, 2, 0}, buff);
assertEquals(6, bytesNum);
assertTrue(Arrays.equals(buff, new byte[]{10, 20, 30, 40, 50, 60}));
bytesNum = sm.put(new int[]{0, 0, 0}, 255, 254, 253, 252, 251, 250);
assertEquals(6, bytesNum);
bytesNum = sm.get(new int[]{0, 0, 0}, buff);
assertEquals(6, bytesNum);
assertTrue(Arrays.equals(buff, new byte[]{-1, -2, -3, -4, -5, -6}));
bytesNum = m.get(new int[]{0, 1, 2}, buff);
assertEquals(6, bytesNum);
assertTrue(Arrays.equals(buff, new byte[]{-1, -2, -3, -4, -5, -6}));
}
public void testPutIntIntFloatArray() {
Mat m = new Mat(5, 5, CvType.CV_32FC3, new Scalar(1, 2, 3));
float[] elements = new float[] { 10, 20, 30, 40, 50, 60 };
@ -745,6 +850,29 @@ public class MatTest extends OpenCVTestCase {
}
}
public void testPutIntArrayFloatArray() {
Mat m = new Mat(new int[]{5, 5, 5}, CvType.CV_32FC3, new Scalar(1, 2, 3));
float[] elements = new float[] { 10, 20, 30, 40, 50, 60 };
int bytesNum = m.put(new int[]{0, 4, 3}, elements);
assertEquals(elements.length * 4, bytesNum);
Mat m1 = m.submat(new Range[]{ Range.all(), new Range(4, 5), Range.all() });
float buff[] = new float[3];
bytesNum = m1.get(new int[]{ 0, 0, 4 }, buff);
assertEquals(buff.length * 4, bytesNum);
assertTrue(Arrays.equals(new float[]{40, 50, 60}, buff));
assertArrayEquals(new double[]{10, 20, 30}, m.get(new int[]{ 0, 4, 3 }), EPS);
try {
float[] elements2 = new float[] { 10, 20, 30, 40, 50 };
m.put(new int[]{4, 2, 2}, elements2);
fail("Expected UnsupportedOperationException (data.length % CvType.channels(t) != 0)");
} catch (UnsupportedOperationException e) {
// expected
}
}
public void testPutIntIntIntArray() {
Mat m = new Mat(5, 5, CvType.CV_32SC3, new Scalar(-1, -2, -3));
int[] elements = new int[] { 10, 20, 30, 40, 50, 60 };
@ -768,6 +896,29 @@ public class MatTest extends OpenCVTestCase {
}
}
public void testPutIntArrayIntArray() {
Mat m = new Mat(new int[]{5, 5, 5}, CvType.CV_32SC3, new Scalar(-1, -2, -3));
int[] elements = new int[] { 10, 20, 30, 40, 50, 60 };
int bytesNum = m.put(new int[]{ 0, 0, 4 }, elements);
assertEquals(elements.length * 4, bytesNum);
Mat m1 = m.submat(new Range[]{ Range.all(), Range.all(), new Range(4, 5)});
int buff[] = new int[3];
bytesNum = m1.get(new int[]{ 0, 0, 0 }, buff);
assertEquals(buff.length * 4, bytesNum);
assertTrue(Arrays.equals(new int[]{ 10, 20, 30 }, buff));
assertArrayEquals(new double[]{ 40, 50, 60 }, m.get(new int[]{ 0, 1, 0 }), EPS);
try {
int[] elements2 = new int[] { 10, 20, 30, 40, 50 };
m.put(new int[] { 2, 2, 0 }, elements2);
fail("Expected UnsupportedOperationException (data.length % CvType.channels(t) != 0)");
} catch (UnsupportedOperationException e) {
// expected
}
}
public void testPutIntIntShortArray() {
Mat m = new Mat(5, 5, CvType.CV_16SC3, new Scalar(-1, -2, -3));
short[] elements = new short[] { 10, 20, 30, 40, 50, 60 };
@ -790,6 +941,28 @@ public class MatTest extends OpenCVTestCase {
}
}
public void testPutIntArrayShortArray() {
Mat m = new Mat(new int[]{ 5, 5, 5}, CvType.CV_16SC3, new Scalar(-1, -2, -3));
short[] elements = new short[] { 10, 20, 30, 40, 50, 60 };
int bytesNum = m.put(new int[]{ 0, 2, 3 }, elements);
assertEquals(elements.length * 2, bytesNum);
Mat m1 = m.submat(new Range[]{ Range.all(), Range.all(), new Range(3, 4)});
short buff[] = new short[3];
bytesNum = m1.get(new int[]{ 0, 2, 0 }, buff);
assertTrue(Arrays.equals(new short[]{10, 20, 30}, buff));
assertArrayEquals(new double[]{40, 50, 60}, m.get(new int[]{ 0, 2, 4 }), EPS);
try {
short[] elements2 = new short[] { 10, 20, 30, 40, 50 };
m.put(new int[] { 2, 2, 0 }, elements2);
fail("Expected UnsupportedOperationException (data.length % CvType.channels(t) != 0)");
} catch (UnsupportedOperationException e) {
// expected
}
}
public void testRelease() {
assertFalse(gray0.empty());
assertTrue(gray0.rows() > 0);
@ -818,6 +991,7 @@ public class MatTest extends OpenCVTestCase {
}
public void testReshapeIntIntArray() {
// 2D -> 4D
Mat src = new Mat(6, 5, CvType.CV_8UC3, new Scalar(0));
assertEquals(2, src.dims());
assertEquals(src.rows(), src.size(0));
@ -828,6 +1002,34 @@ public class MatTest extends OpenCVTestCase {
assertEquals(newShape.length, dst.dims());
for (int i = 0; i < newShape.length; ++i)
assertEquals(newShape[i], dst.size(i));
// 3D -> 2D
src = new Mat(new int[]{4, 6, 7}, CvType.CV_8UC3, new Scalar(0));
assertEquals(3, src.dims());
assertEquals(4, src.size(0));
assertEquals(6, src.size(1));
assertEquals(7, src.size(2));
int[] newShape2 = {src.channels() * src.size(2), src.size(0) * src.size(1)};
dst = src.reshape(1, newShape2);
assertEquals(newShape2.length, dst.dims());
for (int i = 0; i < newShape2.length; ++i)
assertEquals(newShape2[i], dst.size(i));
}
public void testCopySize() {
Mat src = new Mat(new int[]{1, 1, 10, 10}, CvType.CV_8UC1, new Scalar(1));
assertEquals(4, src.dims());
assertEquals(1, src.size(0));
assertEquals(1, src.size(1));
assertEquals(10, src.size(2));
assertEquals(10, src.size(3));
Mat other = new Mat(new int[]{10, 10}, src.type());
src.copySize(other);
assertEquals(other.dims(), src.dims());
for (int i = 0; i < other.dims(); ++i)
assertEquals(other.size(i), src.size(i));
}
public void testRow() {
@ -949,6 +1151,16 @@ public class MatTest extends OpenCVTestCase {
assertEquals(2, submat.cols());
}
public void testSubmatRangeArray() {
Mat submat = gray255_32f_3d.submat(new Range[]{ new Range(2, 4), new Range(2, 4), new Range(3, 6) });
assertTrue(submat.isSubmatrix());
assertFalse(submat.isContinuous());
assertEquals(2, submat.size(0));
assertEquals(2, submat.size(1));
assertEquals(3, submat.size(2));
}
public void testSubmatRect() {
Mat submat = gray255.submat(new Rect(5, 5, gray255.cols() / 2, gray255.rows() / 2));
assertTrue(submat.isSubmatrix());
@ -1015,6 +1227,13 @@ public class MatTest extends OpenCVTestCase {
assertMatEqual(truth, dst);
}
public void testZerosIntArray() {
dst = Mat.zeros(new int[]{2, 3, 4}, CvType.CV_16S);
truth = new Mat(new int[]{2, 3, 4}, CvType.CV_16S, new Scalar(0));
assertMatEqual(truth, dst);
}
public void testMatFromByteBuffer() {
ByteBuffer bbuf = ByteBuffer.allocateDirect(64*64);
bbuf.putInt(0x01010101);

38
modules/core/src/matrix_wrap.cpp
View File

@ -1288,16 +1288,11 @@ void _OutputArray::create(int d, const int* sizes, int mtype, int i,
{
CV_Assert( i < 0 );
Mat& m = *(Mat*)obj;
if( allowTransposed )
if (allowTransposed && !m.empty() &&
d == 2 && m.dims == 2 &&
m.type() == mtype && m.rows == sizes[1] && m.cols == sizes[0] &&
m.isContinuous())
{
if( !m.isContinuous() )
{
CV_Assert(!fixedType() && !fixedSize());
m.release();
}
if( d == 2 && m.dims == 2 && m.data &&
m.type() == mtype && m.rows == sizes[1] && m.cols == sizes[0] )
return;
}
@ -1306,13 +1301,13 @@ void _OutputArray::create(int d, const int* sizes, int mtype, int i,
if(CV_MAT_CN(mtype) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0 )
mtype = m.type();
else
CV_Assert(CV_MAT_TYPE(mtype) == m.type());
CV_CheckTypeEQ(m.type(), CV_MAT_TYPE(mtype), "");
}
if(fixedSize())
{
CV_Assert(m.dims == d);
CV_CheckEQ(m.dims, d, "");
for(int j = 0; j < d; ++j)
CV_Assert(m.size[j] == sizes[j]);
CV_CheckEQ(m.size[j], sizes[j], "");
}
m.create(d, sizes, mtype);
return;
@ -1322,16 +1317,11 @@ void _OutputArray::create(int d, const int* sizes, int mtype, int i,
{
CV_Assert( i < 0 );
UMat& m = *(UMat*)obj;
if( allowTransposed )
if (allowTransposed && !m.empty() &&
d == 2 && m.dims == 2 &&
m.type() == mtype && m.rows == sizes[1] && m.cols == sizes[0] &&
m.isContinuous())
{
if( !m.isContinuous() )
{
CV_Assert(!fixedType() && !fixedSize());
m.release();
}
if( d == 2 && m.dims == 2 && !m.empty() &&
m.type() == mtype && m.rows == sizes[1] && m.cols == sizes[0] )
return;
}
@ -1340,13 +1330,13 @@ void _OutputArray::create(int d, const int* sizes, int mtype, int i,
if(CV_MAT_CN(mtype) == m.channels() && ((1 << CV_MAT_TYPE(flags)) & fixedDepthMask) != 0 )
mtype = m.type();
else
CV_Assert(CV_MAT_TYPE(mtype) == m.type());
CV_CheckTypeEQ(m.type(), CV_MAT_TYPE(mtype), "");
}
if(fixedSize())
{
CV_Assert(m.dims == d);
CV_CheckEQ(m.dims, d, "");
for(int j = 0; j < d; ++j)
CV_Assert(m.size[j] == sizes[j]);
CV_CheckEQ(m.size[j], sizes[j], "");
}
m.create(d, sizes, mtype);
return;

7
modules/core/test/test_misc.cpp
View File

@ -177,6 +177,13 @@ TEST(Core_OutputArray, FixedType)
EXPECT_EQ(2, num_defaultResult);
}
TEST(Core_OutputArrayCreate, _13772)
{
cv::Mat1d mat;
cv::OutputArray o(mat);
ASSERT_NO_THROW(o.create(3, 5, CV_64F, -1, true));
}
TEST(Core_String, find_last_of__with__empty_string)

8
modules/dnn/src/darknet/darknet_io.cpp
View File

@ -371,7 +371,7 @@ namespace cv {
fused_layer_names.push_back(last_layer);
}
void setYolo(int classes, const std::vector<int>& mask, const std::vector<float>& anchors)
void setYolo(int classes, const std::vector<int>& mask, const std::vector<float>& anchors, float thresh, float nms_threshold)
{
cv::dnn::LayerParams region_param;
region_param.name = "Region-name";
@ -382,6 +382,8 @@ namespace cv {
region_param.set<int>("classes", classes);
region_param.set<int>("anchors", numAnchors);
region_param.set<bool>("logistic", true);
region_param.set<float>("thresh", thresh);
region_param.set<float>("nms_threshold", nms_threshold);
std::vector<float> usedAnchors(numAnchors * 2);
for (int i = 0; i < numAnchors; ++i)
@ -646,6 +648,8 @@ namespace cv {
{
int classes = getParam<int>(layer_params, "classes", -1);
int num_of_anchors = getParam<int>(layer_params, "num", -1);
float thresh = getParam<float>(layer_params, "thresh", 0.2);
float nms_threshold = getParam<float>(layer_params, "nms_threshold", 0.4);
std::string anchors_values = getParam<std::string>(layer_params, "anchors", std::string());
CV_Assert(!anchors_values.empty());
@ -658,7 +662,7 @@ namespace cv {
CV_Assert(classes > 0 && num_of_anchors > 0 && (num_of_anchors * 2) == anchors_vec.size());
setParams.setPermute(false);
setParams.setYolo(classes, mask_vec, anchors_vec);
setParams.setYolo(classes, mask_vec, anchors_vec, thresh, nms_threshold);
}
else {
CV_Error(cv::Error::StsParseError, "Unknown layer type: " + layer_type);

82
modules/dnn/src/layers/convolution_layer.cpp
View File

@ -62,6 +62,8 @@ namespace dnn
class BaseConvolutionLayerImpl : public ConvolutionLayer
{
public:
bool newWeightAndBias;
std::vector<double> weightsMultipliers;
BaseConvolutionLayerImpl(const LayerParams &params)
{
setParamsFrom(params);
@ -85,6 +87,8 @@ public:
CV_Assert(numOutput % ngroups == 0);
CV_Assert(adjustPad.width < stride.width &&
adjustPad.height < stride.height);
newWeightAndBias = false;
}
void finalize(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr) CV_OVERRIDE
@ -135,6 +139,20 @@ public:
(dilation.height == 1 && dilation.width == 1);
}
virtual bool tryFuse(Ptr<Layer>& top) CV_OVERRIDE
{
Mat w, b;
top->getScaleShift(w, b);
if (!w.empty() || !b.empty())
{
fuseWeights(w, b);
return true;
}
return false;
}
virtual void fuseWeights(const Mat& w_, const Mat& b_) = 0;
virtual void applyHalideScheduler(Ptr<BackendNode>& node,
const std::vector<Mat*> &inputs,
const std::vector<Mat> &outputs,
@ -185,11 +203,9 @@ class ConvolutionLayerImpl CV_FINAL : public BaseConvolutionLayerImpl
public:
enum { VEC_ALIGN = 8, DFT_TYPE = CV_32F };
Mat weightsMat;
std::vector<double> weightsMultipliers;
std::vector<float> biasvec;
std::vector<float> reluslope;
Ptr<ActivationLayer> activ;
bool newWeightAndBias;
bool fusedBias;
#ifdef HAVE_OPENCL
@ -201,7 +217,6 @@ public:
#endif
ConvolutionLayerImpl(const LayerParams &params) : BaseConvolutionLayerImpl(params)
{
newWeightAndBias = false;
fusedBias = false;
#ifdef HAVE_OPENCL
newActiv = false;
@ -349,19 +364,7 @@ public:
return !activ.empty();
}
virtual bool tryFuse(Ptr<Layer>& top) CV_OVERRIDE
{
Mat w, b;
top->getScaleShift(w, b);
if (!w.empty() || !b.empty())
{
fuseWeights(w, b);
return true;
}
return false;
}
void fuseWeights(const Mat& w_, const Mat& b_)
void fuseWeights(const Mat& w_, const Mat& b_) CV_OVERRIDE
{
// Convolution weights have OIHW data layout. Parameters fusion in case of
// (conv(I) + b1 ) * w + b2
@ -1308,6 +1311,45 @@ public:
pad.width = pad_l;
pad.height = pad_t;
weightsMultipliers.assign(numOutput, 1.0);
if (weightsMat.empty())
{
transpose(blobs[0].reshape(1, blobs[0].size[0]), weightsMat);
biasesMat = hasBias() ? blobs[1].reshape(1, numOutput)
: Mat::zeros(numOutput, 1, CV_32F);
}
}
void fuseWeights(const Mat& w_, const Mat& b_) CV_OVERRIDE
{
Mat w = w_.total() == 1 ? Mat(1, numOutput, CV_32F, Scalar(w_.at<float>(0))) : w_;
Mat b = b_.total() == 1 ? Mat(1, numOutput, CV_32F, Scalar(b_.at<float>(0))) : b_;
CV_Assert_N(!weightsMat.empty(),
w.empty() || numOutput == w.total(),
b.empty() || numOutput == b.total());
if (!w.empty())
{
transpose(blobs[0].reshape(1, blobs[0].size[0]), weightsMat);
weightsMat = weightsMat.reshape(1, numOutput);
for (int i = 0; i < numOutput; ++i)
{
double wi = w.at<float>(i);
weightsMultipliers[i] *= wi;
cv::multiply(weightsMat.row(i), weightsMultipliers[i], weightsMat.row(i));
biasesMat.at<float>(i) *= wi;
}
weightsMat = weightsMat.reshape(1, weightsMat.total() / blobs[0].size[0]);
}
if (!b.empty())
{
cv::add(biasesMat, b.reshape(1, numOutput), biasesMat);
}
newWeightAndBias = !w.empty() || !b.empty();
}
class MatMulInvoker : public ParallelLoopBody
@ -1574,6 +1616,13 @@ public:
return false;
if (umat_weights.empty())
{
if (newWeightAndBias)
{
weightsMat.copyTo(umat_weights);
biasesMat.copyTo(umat_biases);
}
else
{
transpose(blobs[0].reshape(1, inpCn), umat_weights);
if (hasBias())
@ -1581,6 +1630,7 @@ public:
else
umat_biases = UMat::zeros(outCn, 1, CV_32F);
}
}
String buildopt = format("-DT=%s ", ocl::typeToStr(inputs[0].type()));
buildopt += format("-DPAD_H=%d -DPAD_W=%d -DKERNEL_H=%d -DKERNEL_W=%d -DSTRIDE_H=%d -DSTRIDE_W=%d ",

9
modules/dnn/test/test_backends.cpp
View File

@ -305,9 +305,16 @@ TEST_P(DNNTestNetwork, DenseNet_121)
TEST_P(DNNTestNetwork, FastNeuralStyle_eccv16)
{
if (backend == DNN_BACKEND_HALIDE ||
(backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) ||
(backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD))
throw SkipTestException("");
#if defined(INF_ENGINE_RELEASE)
#if INF_ENGINE_RELEASE <= 2018050000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL)
throw SkipTestException("");
#endif
#endif
Mat img = imread(findDataFile("dnn/googlenet_1.png", false));
Mat inp = blobFromImage(img, 1.0, Size(320, 240), Scalar(103.939, 116.779, 123.68), false, false);
// Output image has values in range [-143.526, 148.539].

8
modules/dnn/test/test_torch_importer.cpp
View File

@ -394,6 +394,14 @@ TEST_P(Test_Torch_nets, ENet_accuracy)
TEST_P(Test_Torch_nets, FastNeuralStyle_accuracy)
{
checkBackend();
#if defined(INF_ENGINE_RELEASE)
#if INF_ENGINE_RELEASE <= 2018050000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL)
throw SkipTestException("");
#endif
#endif
std::string models[] = {"dnn/fast_neural_style_eccv16_starry_night.t7",
"dnn/fast_neural_style_instance_norm_feathers.t7"};
std::string targets[] = {"dnn/lena_starry_night.png", "dnn/lena_feathers.png"};

1
modules/imgcodecs/include/opencv2/imgcodecs.hpp
View File

@ -95,6 +95,7 @@ enum ImwriteFlags {
IMWRITE_TIFF_RESUNIT = 256,//!< For TIFF, use to specify which DPI resolution unit to set; see libtiff documentation for valid values
IMWRITE_TIFF_XDPI = 257,//!< For TIFF, use to specify the X direction DPI
IMWRITE_TIFF_YDPI = 258, //!< For TIFF, use to specify the Y direction DPI
IMWRITE_TIFF_COMPRESSION = 259, //!< For TIFF, use to specify the image compression scheme. See libtiff for integer constants corresponding to compression formats. Note, for images whose depth is CV_32F, only libtiff's SGILOG compression scheme is used. For other supported depths, the compression scheme can be specified by this flag; LZW compression is the default.
IMWRITE_JPEG2000_COMPRESSION_X1000 = 272 //!< For JPEG2000, use to specify the target compression rate (multiplied by 1000). The value can be from 0 to 1000. Default is 1000.
};

3
modules/imgcodecs/src/grfmt_tiff.cpp
View File

@ -750,12 +750,11 @@ bool TiffEncoder::writeLibTiff( const std::vector<Mat>& img_vec, const std::vect
}
//Settings that matter to all images
// defaults for now, maybe base them on params in the future
int compression = COMPRESSION_LZW;
int predictor = PREDICTOR_HORIZONTAL;
int resUnit = -1, dpiX = -1, dpiY = -1;
readParam(params, TIFFTAG_COMPRESSION, compression);
readParam(params, IMWRITE_TIFF_COMPRESSION, compression);
readParam(params, TIFFTAG_PREDICTOR, predictor);
readParam(params, IMWRITE_TIFF_RESUNIT, resUnit);
readParam(params, IMWRITE_TIFF_XDPI, dpiX);

9
modules/imgproc/CMakeLists.txt
View File

@ -1,3 +1,12 @@
set(the_description "Image Processing")
ocv_add_dispatched_file(accum SSE4_1 AVX AVX2)
ocv_add_dispatched_file(bilateral_filter SSE2 AVX2)
ocv_add_dispatched_file(box_filter SSE2 SSE4_1 AVX2)
ocv_add_dispatched_file(filter SSE2 SSE4_1 AVX2)
ocv_add_dispatched_file(color_hsv SSE2 SSE4_1 AVX2)
ocv_add_dispatched_file(color_rgb SSE2 SSE4_1 AVX2)
ocv_add_dispatched_file(color_yuv SSE2 SSE4_1 AVX2)
ocv_add_dispatched_file(median_blur SSE2 SSE4_1 AVX2)
ocv_add_dispatched_file(morph SSE2 SSE4_1 AVX2)
ocv_add_dispatched_file(smooth SSE2 SSE4_1 AVX2)
ocv_define_module(imgproc opencv_core WRAP java python js)

2
modules/imgproc/perf/perf_filter2d.cpp
View File

@ -39,7 +39,7 @@ PERF_TEST_P( TestFilter2d, Filter2d,
SANITY_CHECK(dst, 1);
}
PERF_TEST_P(TestFilter2d, Filter2d_ovx,
PERF_TEST_P(TestFilter2d, DISABLED_Filter2d_ovx,
Combine(
Values(Size(320, 240), sz1080p),
Values(3, 5),

2
modules/imgproc/perf/perf_pyramids.cpp
View File

@ -26,7 +26,7 @@ PERF_TEST_P(Size_MatType, pyrDown, testing::Combine(
SANITY_CHECK(dst, eps, error_type);
}
PERF_TEST_P(Size_MatType, pyrDown_ovx, testing::Combine(
PERF_TEST_P(Size_MatType, DISABLED_pyrDown_ovx, testing::Combine(
testing::Values(sz1080p, sz720p, szVGA, szQVGA, szODD),
testing::Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16SC1, CV_16SC3, CV_16SC4, CV_32FC1, CV_32FC3, CV_32FC4)
)

4
modules/imgproc/perf/perf_warp.cpp
View File

@ -48,7 +48,7 @@ PERF_TEST_P( TestWarpAffine, WarpAffine,
#endif
}
PERF_TEST_P(TestWarpAffine, WarpAffine_ovx,
PERF_TEST_P(TestWarpAffine, DISABLED_WarpAffine_ovx,
Combine(
Values(szVGA, sz720p, sz1080p),
InterType::all(),
@ -116,7 +116,7 @@ PERF_TEST_P( TestWarpPerspective, WarpPerspective,
#endif
}
PERF_TEST_P(TestWarpPerspective, WarpPerspective_ovx,
PERF_TEST_P(TestWarpPerspective, DISABLED_WarpPerspective_ovx,
Combine(
Values(szVGA, sz720p, sz1080p),
InterType::all(),

427
modules/imgproc/src/bilateral_filter.dispatch.cpp Normal file
View File

@ -0,0 +1,427 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, 2018, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2014-2015, Itseez Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#include <vector>
#include "opencv2/core/hal/intrin.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "bilateral_filter.simd.hpp"
#include "bilateral_filter.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
/****************************************************************************************\
Bilateral Filtering
\****************************************************************************************/
namespace cv {
#ifdef HAVE_OPENCL
static bool ocl_bilateralFilter_8u(InputArray _src, OutputArray _dst, int d,
double sigma_color, double sigma_space,
int borderType)
{
CV_INSTRUMENT_REGION();
#ifdef __ANDROID__
if (ocl::Device::getDefault().isNVidia())
return false;
#endif
int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
int i, j, maxk, radius;
if (depth != CV_8U || cn > 4)
return false;
if (sigma_color <= 0)
sigma_color = 1;
if (sigma_space <= 0)
sigma_space = 1;
double gauss_color_coeff = -0.5 / (sigma_color * sigma_color);
double gauss_space_coeff = -0.5 / (sigma_space * sigma_space);
if ( d <= 0 )
radius = cvRound(sigma_space * 1.5);
else
radius = d / 2;
radius = MAX(radius, 1);
d = radius * 2 + 1;
UMat src = _src.getUMat(), dst = _dst.getUMat(), temp;
if (src.u == dst.u)
return false;
copyMakeBorder(src, temp, radius, radius, radius, radius, borderType);
std::vector<float> _space_weight(d * d);
std::vector<int> _space_ofs(d * d);
float * const space_weight = &_space_weight[0];
int * const space_ofs = &_space_ofs[0];
// initialize space-related bilateral filter coefficients
for( i = -radius, maxk = 0; i <= radius; i++ )
for( j = -radius; j <= radius; j++ )
{
double r = std::sqrt((double)i * i + (double)j * j);
if ( r > radius )
continue;
space_weight[maxk] = (float)std::exp(r * r * gauss_space_coeff);
space_ofs[maxk++] = (int)(i * temp.step + j * cn);
}
char cvt[3][40];
String cnstr = cn > 1 ? format("%d", cn) : "";
String kernelName("bilateral");
size_t sizeDiv = 1;
if ((ocl::Device::getDefault().isIntel()) &&
(ocl::Device::getDefault().type() == ocl::Device::TYPE_GPU))
{
//Intel GPU
if (dst.cols % 4 == 0 && cn == 1) // For single channel x4 sized images.
{
kernelName = "bilateral_float4";
sizeDiv = 4;
}
}
ocl::Kernel k(kernelName.c_str(), ocl::imgproc::bilateral_oclsrc,
format("-D radius=%d -D maxk=%d -D cn=%d -D int_t=%s -D uint_t=uint%s -D convert_int_t=%s"
" -D uchar_t=%s -D float_t=%s -D convert_float_t=%s -D convert_uchar_t=%s -D gauss_color_coeff=(float)%f",
radius, maxk, cn, ocl::typeToStr(CV_32SC(cn)), cnstr.c_str(),
ocl::convertTypeStr(CV_8U, CV_32S, cn, cvt[0]),
ocl::typeToStr(type), ocl::typeToStr(CV_32FC(cn)),
ocl::convertTypeStr(CV_32S, CV_32F, cn, cvt[1]),
ocl::convertTypeStr(CV_32F, CV_8U, cn, cvt[2]), gauss_color_coeff));
if (k.empty())
return false;
Mat mspace_weight(1, d * d, CV_32FC1, space_weight);
Mat mspace_ofs(1, d * d, CV_32SC1, space_ofs);
UMat ucolor_weight, uspace_weight, uspace_ofs;
mspace_weight.copyTo(uspace_weight);
mspace_ofs.copyTo(uspace_ofs);
k.args(ocl::KernelArg::ReadOnlyNoSize(temp), ocl::KernelArg::WriteOnly(dst),
ocl::KernelArg::PtrReadOnly(uspace_weight),
ocl::KernelArg::PtrReadOnly(uspace_ofs));
size_t globalsize[2] = { (size_t)dst.cols / sizeDiv, (size_t)dst.rows };
return k.run(2, globalsize, NULL, false);
}
#endif
static void
bilateralFilter_8u( const Mat& src, Mat& dst, int d,
double sigma_color, double sigma_space,
int borderType )
{
CV_INSTRUMENT_REGION();
int cn = src.channels();
int i, j, maxk, radius;
CV_Assert( (src.type() == CV_8UC1 || src.type() == CV_8UC3) && src.data != dst.data );
if( sigma_color <= 0 )
sigma_color = 1;
if( sigma_space <= 0 )
sigma_space = 1;
double gauss_color_coeff = -0.5/(sigma_color*sigma_color);
double gauss_space_coeff = -0.5/(sigma_space*sigma_space);
if( d <= 0 )
radius = cvRound(sigma_space*1.5);
else
radius = d/2;
radius = MAX(radius, 1);
d = radius*2 + 1;
Mat temp;
copyMakeBorder( src, temp, radius, radius, radius, radius, borderType );
std::vector<float> _color_weight(cn*256);
std::vector<float> _space_weight(d*d);
std::vector<int> _space_ofs(d*d);
float* color_weight = &_color_weight[0];
float* space_weight = &_space_weight[0];
int* space_ofs = &_space_ofs[0];
// initialize color-related bilateral filter coefficients
for( i = 0; i < 256*cn; i++ )
color_weight[i] = (float)std::exp(i*i*gauss_color_coeff);
// initialize space-related bilateral filter coefficients
for( i = -radius, maxk = 0; i <= radius; i++ )
{
j = -radius;
for( ; j <= radius; j++ )
{
double r = std::sqrt((double)i*i + (double)j*j);
if( r > radius )
continue;
space_weight[maxk] = (float)std::exp(r*r*gauss_space_coeff);
space_ofs[maxk++] = (int)(i*temp.step + j*cn);
}
}
CV_CPU_DISPATCH(bilateralFilterInvoker_8u, (dst, temp, radius, maxk, space_ofs, space_weight, color_weight),
CV_CPU_DISPATCH_MODES_ALL);
}
static void
bilateralFilter_32f( const Mat& src, Mat& dst, int d,
double sigma_color, double sigma_space,
int borderType )
{
CV_INSTRUMENT_REGION();
int cn = src.channels();
int i, j, maxk, radius;
double minValSrc=-1, maxValSrc=1;
const int kExpNumBinsPerChannel = 1 << 12;
int kExpNumBins = 0;
float lastExpVal = 1.f;
float len, scale_index;
CV_Assert( (src.type() == CV_32FC1 || src.type() == CV_32FC3) && src.data != dst.data );
if( sigma_color <= 0 )
sigma_color = 1;
if( sigma_space <= 0 )
sigma_space = 1;
double gauss_color_coeff = -0.5/(sigma_color*sigma_color);
double gauss_space_coeff = -0.5/(sigma_space*sigma_space);
if( d <= 0 )
radius = cvRound(sigma_space*1.5);
else
radius = d/2;
radius = MAX(radius, 1);
d = radius*2 + 1;
// compute the min/max range for the input image (even if multichannel)
minMaxLoc( src.reshape(1), &minValSrc, &maxValSrc );
if(std::abs(minValSrc - maxValSrc) < FLT_EPSILON)
{
src.copyTo(dst);
return;
}
// temporary copy of the image with borders for easy processing
Mat temp;
copyMakeBorder( src, temp, radius, radius, radius, radius, borderType );
// allocate lookup tables
std::vector<float> _space_weight(d*d);
std::vector<int> _space_ofs(d*d);
float* space_weight = &_space_weight[0];
int* space_ofs = &_space_ofs[0];
// assign a length which is slightly more than needed
len = (float)(maxValSrc - minValSrc) * cn;
kExpNumBins = kExpNumBinsPerChannel * cn;
std::vector<float> _expLUT(kExpNumBins+2);
float* expLUT = &_expLUT[0];
scale_index = kExpNumBins/len;
// initialize the exp LUT
for( i = 0; i < kExpNumBins+2; i++ )
{
if( lastExpVal > 0.f )
{
double val = i / scale_index;
expLUT[i] = (float)std::exp(val * val * gauss_color_coeff);
lastExpVal = expLUT[i];
}
else
expLUT[i] = 0.f;
}
// initialize space-related bilateral filter coefficients
for( i = -radius, maxk = 0; i <= radius; i++ )
for( j = -radius; j <= radius; j++ )
{
double r = std::sqrt((double)i*i + (double)j*j);
if( r > radius || ( i == 0 && j == 0 ) )
continue;
space_weight[maxk] = (float)std::exp(r*r*gauss_space_coeff);
space_ofs[maxk++] = (int)(i*(temp.step/sizeof(float)) + j*cn);
}
// parallel_for usage
CV_CPU_DISPATCH(bilateralFilterInvoker_32f, (cn, radius, maxk, space_ofs, temp, dst, scale_index, space_weight, expLUT),
CV_CPU_DISPATCH_MODES_ALL);
}
#ifdef HAVE_IPP
#define IPP_BILATERAL_PARALLEL 1
#ifdef HAVE_IPP_IW
class ipp_bilateralFilterParallel: public ParallelLoopBody
{
public:
ipp_bilateralFilterParallel(::ipp::IwiImage &_src, ::ipp::IwiImage &_dst, int _radius, Ipp32f _valSquareSigma, Ipp32f _posSquareSigma, ::ipp::IwiBorderType _borderType, bool *_ok):
src(_src), dst(_dst)
{
pOk = _ok;
radius = _radius;
valSquareSigma = _valSquareSigma;
posSquareSigma = _posSquareSigma;
borderType = _borderType;
*pOk = true;
}
~ipp_bilateralFilterParallel() {}
virtual void operator() (const Range& range) const CV_OVERRIDE
{
if(*pOk == false)
return;
try
{
::ipp::IwiTile tile = ::ipp::IwiRoi(0, range.start, dst.m_size.width, range.end - range.start);
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterBilateral, src, dst, radius, valSquareSigma, posSquareSigma, ::ipp::IwDefault(), borderType, tile);
}
catch(const ::ipp::IwException &)
{
*pOk = false;
return;
}
}
private:
::ipp::IwiImage &src;
::ipp::IwiImage &dst;
int radius;
Ipp32f valSquareSigma;
Ipp32f posSquareSigma;
::ipp::IwiBorderType borderType;
bool *pOk;
const ipp_bilateralFilterParallel& operator= (const ipp_bilateralFilterParallel&);
};
#endif
static bool ipp_bilateralFilter(Mat &src, Mat &dst, int d, double sigmaColor, double sigmaSpace, int borderType)
{
#ifdef HAVE_IPP_IW
CV_INSTRUMENT_REGION_IPP();
int radius = IPP_MAX(((d <= 0)?cvRound(sigmaSpace*1.5):d/2), 1);
Ipp32f valSquareSigma = (Ipp32f)((sigmaColor <= 0)?1:sigmaColor*sigmaColor);
Ipp32f posSquareSigma = (Ipp32f)((sigmaSpace <= 0)?1:sigmaSpace*sigmaSpace);
// Acquire data and begin processing
try
{
::ipp::IwiImage iwSrc = ippiGetImage(src);
::ipp::IwiImage iwDst = ippiGetImage(dst);
::ipp::IwiBorderSize borderSize(radius);
::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize));
if(!ippBorder)
return false;
const int threads = ippiSuggestThreadsNum(iwDst, 2);
if(IPP_BILATERAL_PARALLEL && threads > 1) {
bool ok = true;
Range range(0, (int)iwDst.m_size.height);
ipp_bilateralFilterParallel invoker(iwSrc, iwDst, radius, valSquareSigma, posSquareSigma, ippBorder, &ok);
if(!ok)
return false;
parallel_for_(range, invoker, threads*4);
if(!ok)
return false;
} else {
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterBilateral, iwSrc, iwDst, radius, valSquareSigma, posSquareSigma, ::ipp::IwDefault(), ippBorder);
}
}
catch (const ::ipp::IwException &)
{
return false;
}
return true;
#else
CV_UNUSED(src); CV_UNUSED(dst); CV_UNUSED(d); CV_UNUSED(sigmaColor); CV_UNUSED(sigmaSpace); CV_UNUSED(borderType);
return false;
#endif
}
#endif
void bilateralFilter( InputArray _src, OutputArray _dst, int d,
double sigmaColor, double sigmaSpace,
int borderType )
{
CV_INSTRUMENT_REGION();
_dst.create( _src.size(), _src.type() );
CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
ocl_bilateralFilter_8u(_src, _dst, d, sigmaColor, sigmaSpace, borderType))
Mat src = _src.getMat(), dst = _dst.getMat();
CV_IPP_RUN_FAST(ipp_bilateralFilter(src, dst, d, sigmaColor, sigmaSpace, borderType));
if( src.depth() == CV_8U )
bilateralFilter_8u( src, dst, d, sigmaColor, sigmaSpace, borderType );
else if( src.depth() == CV_32F )
bilateralFilter_32f( src, dst, d, sigmaColor, sigmaSpace, borderType );
else
CV_Error( CV_StsUnsupportedFormat,
"Bilateral filtering is only implemented for 8u and 32f images" );
}
} // namespace

394
modules/imgproc/src/bilateral_filter.cpp → modules/imgproc/src/bilateral_filter.simd.hpp
View File

@ -43,18 +43,25 @@
#include "precomp.hpp"
#include <vector>
#include "opencv2/core/hal/intrin.hpp"
#include "opencl_kernels_imgproc.hpp"
/****************************************************************************************\
Bilateral Filtering
\****************************************************************************************/
namespace cv
{
namespace cv {
CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
// forward declarations
void bilateralFilterInvoker_8u(
Mat& dst, const Mat& temp, int radius, int maxk,
int* space_ofs, float *space_weight, float *color_weight);
void bilateralFilterInvoker_32f(
int cn, int radius, int maxk, int *space_ofs,
const Mat& temp, Mat& dst, float scale_index, float *space_weight, float *expLUT);
#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
namespace {
class BilateralFilter_8u_Invoker :
public ParallelLoopBody
{
@ -68,6 +75,8 @@ public:
virtual void operator() (const Range& range) const CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int i, j, cn = dest->channels(), k;
Size size = dest->size();
@ -536,161 +545,20 @@ private:
float *space_weight, *color_weight;
};
#ifdef HAVE_OPENCL
} // namespace anon
static bool ocl_bilateralFilter_8u(InputArray _src, OutputArray _dst, int d,
double sigma_color, double sigma_space,
int borderType)
void bilateralFilterInvoker_8u(
Mat& dst, const Mat& temp, int radius, int maxk,
int* space_ofs, float *space_weight, float *color_weight)
{
#ifdef __ANDROID__
if (ocl::Device::getDefault().isNVidia())
return false;
#endif
int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
int i, j, maxk, radius;
if (depth != CV_8U || cn > 4)
return false;
if (sigma_color <= 0)
sigma_color = 1;
if (sigma_space <= 0)
sigma_space = 1;
double gauss_color_coeff = -0.5 / (sigma_color * sigma_color);
double gauss_space_coeff = -0.5 / (sigma_space * sigma_space);
if ( d <= 0 )
radius = cvRound(sigma_space * 1.5);
else
radius = d / 2;
radius = MAX(radius, 1);
d = radius * 2 + 1;
UMat src = _src.getUMat(), dst = _dst.getUMat(), temp;
if (src.u == dst.u)
return false;
copyMakeBorder(src, temp, radius, radius, radius, radius, borderType);
std::vector<float> _space_weight(d * d);
std::vector<int> _space_ofs(d * d);
float * const space_weight = &_space_weight[0];
int * const space_ofs = &_space_ofs[0];
// initialize space-related bilateral filter coefficients
for( i = -radius, maxk = 0; i <= radius; i++ )
for( j = -radius; j <= radius; j++ )
{
double r = std::sqrt((double)i * i + (double)j * j);
if ( r > radius )
continue;
space_weight[maxk] = (float)std::exp(r * r * gauss_space_coeff);
space_ofs[maxk++] = (int)(i * temp.step + j * cn);
}
char cvt[3][40];
String cnstr = cn > 1 ? format("%d", cn) : "";
String kernelName("bilateral");
size_t sizeDiv = 1;
if ((ocl::Device::getDefault().isIntel()) &&
(ocl::Device::getDefault().type() == ocl::Device::TYPE_GPU))
{
//Intel GPU
if (dst.cols % 4 == 0 && cn == 1) // For single channel x4 sized images.
{
kernelName = "bilateral_float4";
sizeDiv = 4;
}
}
ocl::Kernel k(kernelName.c_str(), ocl::imgproc::bilateral_oclsrc,
format("-D radius=%d -D maxk=%d -D cn=%d -D int_t=%s -D uint_t=uint%s -D convert_int_t=%s"
" -D uchar_t=%s -D float_t=%s -D convert_float_t=%s -D convert_uchar_t=%s -D gauss_color_coeff=(float)%f",
radius, maxk, cn, ocl::typeToStr(CV_32SC(cn)), cnstr.c_str(),
ocl::convertTypeStr(CV_8U, CV_32S, cn, cvt[0]),
ocl::typeToStr(type), ocl::typeToStr(CV_32FC(cn)),
ocl::convertTypeStr(CV_32S, CV_32F, cn, cvt[1]),
ocl::convertTypeStr(CV_32F, CV_8U, cn, cvt[2]), gauss_color_coeff));
if (k.empty())
return false;
Mat mspace_weight(1, d * d, CV_32FC1, space_weight);
Mat mspace_ofs(1, d * d, CV_32SC1, space_ofs);
UMat ucolor_weight, uspace_weight, uspace_ofs;
mspace_weight.copyTo(uspace_weight);
mspace_ofs.copyTo(uspace_ofs);
k.args(ocl::KernelArg::ReadOnlyNoSize(temp), ocl::KernelArg::WriteOnly(dst),
ocl::KernelArg::PtrReadOnly(uspace_weight),
ocl::KernelArg::PtrReadOnly(uspace_ofs));
size_t globalsize[2] = { (size_t)dst.cols / sizeDiv, (size_t)dst.rows };
return k.run(2, globalsize, NULL, false);
}
#endif
static void
bilateralFilter_8u( const Mat& src, Mat& dst, int d,
double sigma_color, double sigma_space,
int borderType )
{
int cn = src.channels();
int i, j, maxk, radius;
Size size = src.size();
CV_Assert( (src.type() == CV_8UC1 || src.type() == CV_8UC3) && src.data != dst.data );
if( sigma_color <= 0 )
sigma_color = 1;
if( sigma_space <= 0 )
sigma_space = 1;
double gauss_color_coeff = -0.5/(sigma_color*sigma_color);
double gauss_space_coeff = -0.5/(sigma_space*sigma_space);
if( d <= 0 )
radius = cvRound(sigma_space*1.5);
else
radius = d/2;
radius = MAX(radius, 1);
d = radius*2 + 1;
Mat temp;
copyMakeBorder( src, temp, radius, radius, radius, radius, borderType );
std::vector<float> _color_weight(cn*256);
std::vector<float> _space_weight(d*d);
std::vector<int> _space_ofs(d*d);
float* color_weight = &_color_weight[0];
float* space_weight = &_space_weight[0];
int* space_ofs = &_space_ofs[0];
// initialize color-related bilateral filter coefficients
for( i = 0; i < 256*cn; i++ )
color_weight[i] = (float)std::exp(i*i*gauss_color_coeff);
// initialize space-related bilateral filter coefficients
for( i = -radius, maxk = 0; i <= radius; i++ )
{
j = -radius;
for( ; j <= radius; j++ )
{
double r = std::sqrt((double)i*i + (double)j*j);
if( r > radius )
continue;
space_weight[maxk] = (float)std::exp(r*r*gauss_space_coeff);
space_ofs[maxk++] = (int)(i*temp.step + j*cn);
}
}
CV_INSTRUMENT_REGION();
BilateralFilter_8u_Invoker body(dst, temp, radius, maxk, space_ofs, space_weight, color_weight);
parallel_for_(Range(0, size.height), body, dst.total()/(double)(1<<16));
parallel_for_(Range(0, dst.rows), body, dst.total()/(double)(1<<16));
}
namespace {
class BilateralFilter_32f_Invoker :
public ParallelLoopBody
{
@ -705,6 +573,8 @@ public:
virtual void operator() (const Range& range) const CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int i, j, k;
Size size = dest->size();
@ -1153,216 +1023,18 @@ private:
float scale_index, *space_weight, *expLUT;
};
} // namespace anon
static void
bilateralFilter_32f( const Mat& src, Mat& dst, int d,
double sigma_color, double sigma_space,
int borderType )
{
int cn = src.channels();
int i, j, maxk, radius;
double minValSrc=-1, maxValSrc=1;
const int kExpNumBinsPerChannel = 1 << 12;
int kExpNumBins = 0;
float lastExpVal = 1.f;
float len, scale_index;
Size size = src.size();
CV_Assert( (src.type() == CV_32FC1 || src.type() == CV_32FC3) && src.data != dst.data );
if( sigma_color <= 0 )
sigma_color = 1;
if( sigma_space <= 0 )
sigma_space = 1;
double gauss_color_coeff = -0.5/(sigma_color*sigma_color);
double gauss_space_coeff = -0.5/(sigma_space*sigma_space);
if( d <= 0 )
radius = cvRound(sigma_space*1.5);
else
radius = d/2;
radius = MAX(radius, 1);
d = radius*2 + 1;
// compute the min/max range for the input image (even if multichannel)
minMaxLoc( src.reshape(1), &minValSrc, &maxValSrc );
if(std::abs(minValSrc - maxValSrc) < FLT_EPSILON)
{
src.copyTo(dst);
return;
}
// temporary copy of the image with borders for easy processing
Mat temp;
copyMakeBorder( src, temp, radius, radius, radius, radius, borderType );
// allocate lookup tables
std::vector<float> _space_weight(d*d);
std::vector<int> _space_ofs(d*d);
float* space_weight = &_space_weight[0];
int* space_ofs = &_space_ofs[0];
// assign a length which is slightly more than needed
len = (float)(maxValSrc - minValSrc) * cn;
kExpNumBins = kExpNumBinsPerChannel * cn;
std::vector<float> _expLUT(kExpNumBins+2);
float* expLUT = &_expLUT[0];
scale_index = kExpNumBins/len;
// initialize the exp LUT
for( i = 0; i < kExpNumBins+2; i++ )
{
if( lastExpVal > 0.f )
{
double val = i / scale_index;
expLUT[i] = (float)std::exp(val * val * gauss_color_coeff);
lastExpVal = expLUT[i];
}
else
expLUT[i] = 0.f;
}
// initialize space-related bilateral filter coefficients
for( i = -radius, maxk = 0; i <= radius; i++ )
for( j = -radius; j <= radius; j++ )
{
double r = std::sqrt((double)i*i + (double)j*j);
if( r > radius || ( i == 0 && j == 0 ) )
continue;
space_weight[maxk] = (float)std::exp(r*r*gauss_space_coeff);
space_ofs[maxk++] = (int)(i*(temp.step/sizeof(float)) + j*cn);
}
// parallel_for usage
BilateralFilter_32f_Invoker body(cn, radius, maxk, space_ofs, temp, dst, scale_index, space_weight, expLUT);
parallel_for_(Range(0, size.height), body, dst.total()/(double)(1<<16));
}
#ifdef HAVE_IPP
#define IPP_BILATERAL_PARALLEL 1
#ifdef HAVE_IPP_IW
class ipp_bilateralFilterParallel: public ParallelLoopBody
{
public:
ipp_bilateralFilterParallel(::ipp::IwiImage &_src, ::ipp::IwiImage &_dst, int _radius, Ipp32f _valSquareSigma, Ipp32f _posSquareSigma, ::ipp::IwiBorderType _borderType, bool *_ok):
src(_src), dst(_dst)
{
pOk = _ok;
radius = _radius;
valSquareSigma = _valSquareSigma;
posSquareSigma = _posSquareSigma;
borderType = _borderType;
*pOk = true;
}
~ipp_bilateralFilterParallel() {}
virtual void operator() (const Range& range) const CV_OVERRIDE
{
if(*pOk == false)
return;
try
{
::ipp::IwiTile tile = ::ipp::IwiRoi(0, range.start, dst.m_size.width, range.end - range.start);
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterBilateral, src, dst, radius, valSquareSigma, posSquareSigma, ::ipp::IwDefault(), borderType, tile);
}
catch(const ::ipp::IwException &)
{
*pOk = false;
return;
}
}
private:
::ipp::IwiImage &src;
::ipp::IwiImage &dst;
int radius;
Ipp32f valSquareSigma;
Ipp32f posSquareSigma;
::ipp::IwiBorderType borderType;
bool *pOk;
const ipp_bilateralFilterParallel& operator= (const ipp_bilateralFilterParallel&);
};
#endif
static bool ipp_bilateralFilter(Mat &src, Mat &dst, int d, double sigmaColor, double sigmaSpace, int borderType)
{
#ifdef HAVE_IPP_IW
CV_INSTRUMENT_REGION_IPP();
int radius = IPP_MAX(((d <= 0)?cvRound(sigmaSpace*1.5):d/2), 1);
Ipp32f valSquareSigma = (Ipp32f)((sigmaColor <= 0)?1:sigmaColor*sigmaColor);
Ipp32f posSquareSigma = (Ipp32f)((sigmaSpace <= 0)?1:sigmaSpace*sigmaSpace);
// Acquire data and begin processing
try
{
::ipp::IwiImage iwSrc = ippiGetImage(src);
::ipp::IwiImage iwDst = ippiGetImage(dst);
::ipp::IwiBorderSize borderSize(radius);
::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize));
if(!ippBorder)
return false;
const int threads = ippiSuggestThreadsNum(iwDst, 2);
if(IPP_BILATERAL_PARALLEL && threads > 1) {
bool ok = true;
Range range(0, (int)iwDst.m_size.height);
ipp_bilateralFilterParallel invoker(iwSrc, iwDst, radius, valSquareSigma, posSquareSigma, ippBorder, &ok);
if(!ok)
return false;
parallel_for_(range, invoker, threads*4);
if(!ok)
return false;
} else {
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterBilateral, iwSrc, iwDst, radius, valSquareSigma, posSquareSigma, ::ipp::IwDefault(), ippBorder);
}
}
catch (const ::ipp::IwException &)
{
return false;
}
return true;
#else
CV_UNUSED(src); CV_UNUSED(dst); CV_UNUSED(d); CV_UNUSED(sigmaColor); CV_UNUSED(sigmaSpace); CV_UNUSED(borderType);
return false;
#endif
}
#endif
}
void cv::bilateralFilter( InputArray _src, OutputArray _dst, int d,
double sigmaColor, double sigmaSpace,
int borderType )
void bilateralFilterInvoker_32f(
int cn, int radius, int maxk, int *space_ofs,
const Mat& temp, Mat& dst, float scale_index, float *space_weight, float *expLUT)
{
CV_INSTRUMENT_REGION();
_dst.create( _src.size(), _src.type() );
CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
ocl_bilateralFilter_8u(_src, _dst, d, sigmaColor, sigmaSpace, borderType))
Mat src = _src.getMat(), dst = _dst.getMat();
CV_IPP_RUN_FAST(ipp_bilateralFilter(src, dst, d, sigmaColor, sigmaSpace, borderType));
if( src.depth() == CV_8U )
bilateralFilter_8u( src, dst, d, sigmaColor, sigmaSpace, borderType );
else if( src.depth() == CV_32F )
bilateralFilter_32f( src, dst, d, sigmaColor, sigmaSpace, borderType );
else
CV_Error( CV_StsUnsupportedFormat,
"Bilateral filtering is only implemented for 8u and 32f images" );
BilateralFilter_32f_Invoker body(cn, radius, maxk, space_ofs, temp, dst, scale_index, space_weight, expLUT);
parallel_for_(Range(0, dst.rows), body, dst.total()/(double)(1<<16));
}
/* End of file. */
#endif
CV_CPU_OPTIMIZATION_NAMESPACE_END
} // namespace

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@ -0,0 +1,557 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, 2018, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2014-2015, Itseez Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#include <vector>
#include "opencv2/core/hal/intrin.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "opencv2/core/openvx/ovx_defs.hpp"
#include "box_filter.simd.hpp"
#include "box_filter.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
namespace cv {
#ifdef HAVE_OPENCL
static bool ocl_boxFilter3x3_8UC1( InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor, int borderType, bool normalize )
{
const ocl::Device & dev = ocl::Device::getDefault();
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if (ddepth < 0)
ddepth = sdepth;
if (anchor.x < 0)
anchor.x = ksize.width / 2;
if (anchor.y < 0)
anchor.y = ksize.height / 2;
if ( !(dev.isIntel() && (type == CV_8UC1) &&
(_src.offset() == 0) && (_src.step() % 4 == 0) &&
(_src.cols() % 16 == 0) && (_src.rows() % 2 == 0) &&
(anchor.x == 1) && (anchor.y == 1) &&
(ksize.width == 3) && (ksize.height == 3)) )
return false;
float alpha = 1.0f / (ksize.height * ksize.width);
Size size = _src.size();
size_t globalsize[2] = { 0, 0 };
size_t localsize[2] = { 0, 0 };
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
globalsize[0] = size.width / 16;
globalsize[1] = size.height / 2;
char build_opts[1024];
sprintf(build_opts, "-D %s %s", borderMap[borderType], normalize ? "-D NORMALIZE" : "");
ocl::Kernel kernel("boxFilter3x3_8UC1_cols16_rows2", cv::ocl::imgproc::boxFilter3x3_oclsrc, build_opts);
if (kernel.empty())
return false;
UMat src = _src.getUMat();
_dst.create(size, CV_MAKETYPE(ddepth, cn));
if (!(_dst.offset() == 0 && _dst.step() % 4 == 0))
return false;
UMat dst = _dst.getUMat();
int idxArg = kernel.set(0, ocl::KernelArg::PtrReadOnly(src));
idxArg = kernel.set(idxArg, (int)src.step);
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst));
idxArg = kernel.set(idxArg, (int)dst.step);
idxArg = kernel.set(idxArg, (int)dst.rows);
idxArg = kernel.set(idxArg, (int)dst.cols);
if (normalize)
idxArg = kernel.set(idxArg, (float)alpha);
return kernel.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false);
}
static bool ocl_boxFilter( InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor, int borderType, bool normalize, bool sqr = false )
{
const ocl::Device & dev = ocl::Device::getDefault();
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type), esz = CV_ELEM_SIZE(type);
bool doubleSupport = dev.doubleFPConfig() > 0;
if (ddepth < 0)
ddepth = sdepth;
if (cn > 4 || (!doubleSupport && (sdepth == CV_64F || ddepth == CV_64F)) ||
_src.offset() % esz != 0 || _src.step() % esz != 0)
return false;
if (anchor.x < 0)
anchor.x = ksize.width / 2;
if (anchor.y < 0)
anchor.y = ksize.height / 2;
int computeUnits = ocl::Device::getDefault().maxComputeUnits();
float alpha = 1.0f / (ksize.height * ksize.width);
Size size = _src.size(), wholeSize;
bool isolated = (borderType & BORDER_ISOLATED) != 0;
borderType &= ~BORDER_ISOLATED;
int wdepth = std::max(CV_32F, std::max(ddepth, sdepth)),
wtype = CV_MAKE_TYPE(wdepth, cn), dtype = CV_MAKE_TYPE(ddepth, cn);
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
size_t globalsize[2] = { (size_t)size.width, (size_t)size.height };
size_t localsize_general[2] = { 0, 1 }, * localsize = NULL;
UMat src = _src.getUMat();
if (!isolated)
{
Point ofs;
src.locateROI(wholeSize, ofs);
}
int h = isolated ? size.height : wholeSize.height;
int w = isolated ? size.width : wholeSize.width;
size_t maxWorkItemSizes[32];
ocl::Device::getDefault().maxWorkItemSizes(maxWorkItemSizes);
int tryWorkItems = (int)maxWorkItemSizes[0];
ocl::Kernel kernel;
if (dev.isIntel() && !(dev.type() & ocl::Device::TYPE_CPU) &&
((ksize.width < 5 && ksize.height < 5 && esz <= 4) ||
(ksize.width == 5 && ksize.height == 5 && cn == 1)))
{
if (w < ksize.width || h < ksize.height)
return false;
// Figure out what vector size to use for loading the pixels.
int pxLoadNumPixels = cn != 1 || size.width % 4 ? 1 : 4;
int pxLoadVecSize = cn * pxLoadNumPixels;
// Figure out how many pixels per work item to compute in X and Y
// directions. Too many and we run out of registers.
int pxPerWorkItemX = 1, pxPerWorkItemY = 1;
if (cn <= 2 && ksize.width <= 4 && ksize.height <= 4)
{
pxPerWorkItemX = size.width % 8 ? size.width % 4 ? size.width % 2 ? 1 : 2 : 4 : 8;
pxPerWorkItemY = size.height % 2 ? 1 : 2;
}
else if (cn < 4 || (ksize.width <= 4 && ksize.height <= 4))
{
pxPerWorkItemX = size.width % 2 ? 1 : 2;
pxPerWorkItemY = size.height % 2 ? 1 : 2;
}
globalsize[0] = size.width / pxPerWorkItemX;
globalsize[1] = size.height / pxPerWorkItemY;
// Need some padding in the private array for pixels
int privDataWidth = roundUp(pxPerWorkItemX + ksize.width - 1, pxLoadNumPixels);
// Make the global size a nice round number so the runtime can pick
// from reasonable choices for the workgroup size
const int wgRound = 256;
globalsize[0] = roundUp(globalsize[0], wgRound);
char build_options[1024], cvt[2][40];
sprintf(build_options, "-D cn=%d "
"-D ANCHOR_X=%d -D ANCHOR_Y=%d -D KERNEL_SIZE_X=%d -D KERNEL_SIZE_Y=%d "
"-D PX_LOAD_VEC_SIZE=%d -D PX_LOAD_NUM_PX=%d "
"-D PX_PER_WI_X=%d -D PX_PER_WI_Y=%d -D PRIV_DATA_WIDTH=%d -D %s -D %s "
"-D PX_LOAD_X_ITERATIONS=%d -D PX_LOAD_Y_ITERATIONS=%d "
"-D srcT=%s -D srcT1=%s -D dstT=%s -D dstT1=%s -D WT=%s -D WT1=%s "
"-D convertToWT=%s -D convertToDstT=%s%s%s -D PX_LOAD_FLOAT_VEC_CONV=convert_%s -D OP_BOX_FILTER",
cn, anchor.x, anchor.y, ksize.width, ksize.height,
pxLoadVecSize, pxLoadNumPixels,
pxPerWorkItemX, pxPerWorkItemY, privDataWidth, borderMap[borderType],
isolated ? "BORDER_ISOLATED" : "NO_BORDER_ISOLATED",
privDataWidth / pxLoadNumPixels, pxPerWorkItemY + ksize.height - 1,
ocl::typeToStr(type), ocl::typeToStr(sdepth), ocl::typeToStr(dtype),
ocl::typeToStr(ddepth), ocl::typeToStr(wtype), ocl::typeToStr(wdepth),
ocl::convertTypeStr(sdepth, wdepth, cn, cvt[0]),
ocl::convertTypeStr(wdepth, ddepth, cn, cvt[1]),
normalize ? " -D NORMALIZE" : "", sqr ? " -D SQR" : "",
ocl::typeToStr(CV_MAKE_TYPE(wdepth, pxLoadVecSize)) //PX_LOAD_FLOAT_VEC_CONV
);
if (!kernel.create("filterSmall", cv::ocl::imgproc::filterSmall_oclsrc, build_options))
return false;
}
else
{
localsize = localsize_general;
for ( ; ; )
{
int BLOCK_SIZE_X = tryWorkItems, BLOCK_SIZE_Y = std::min(ksize.height * 10, size.height);
while (BLOCK_SIZE_X > 32 && BLOCK_SIZE_X >= ksize.width * 2 && BLOCK_SIZE_X > size.width * 2)
BLOCK_SIZE_X /= 2;
while (BLOCK_SIZE_Y < BLOCK_SIZE_X / 8 && BLOCK_SIZE_Y * computeUnits * 32 < size.height)
BLOCK_SIZE_Y *= 2;
if (ksize.width > BLOCK_SIZE_X || w < ksize.width || h < ksize.height)
return false;
char cvt[2][50];
String opts = format("-D LOCAL_SIZE_X=%d -D BLOCK_SIZE_Y=%d -D ST=%s -D DT=%s -D WT=%s -D convertToDT=%s -D convertToWT=%s"
" -D ANCHOR_X=%d -D ANCHOR_Y=%d -D KERNEL_SIZE_X=%d -D KERNEL_SIZE_Y=%d -D %s%s%s%s%s"
" -D ST1=%s -D DT1=%s -D cn=%d",
BLOCK_SIZE_X, BLOCK_SIZE_Y, ocl::typeToStr(type), ocl::typeToStr(CV_MAKE_TYPE(ddepth, cn)),
ocl::typeToStr(CV_MAKE_TYPE(wdepth, cn)),
ocl::convertTypeStr(wdepth, ddepth, cn, cvt[0]),
ocl::convertTypeStr(sdepth, wdepth, cn, cvt[1]),
anchor.x, anchor.y, ksize.width, ksize.height, borderMap[borderType],
isolated ? " -D BORDER_ISOLATED" : "", doubleSupport ? " -D DOUBLE_SUPPORT" : "",
normalize ? " -D NORMALIZE" : "", sqr ? " -D SQR" : "",
ocl::typeToStr(sdepth), ocl::typeToStr(ddepth), cn);
localsize[0] = BLOCK_SIZE_X;
globalsize[0] = divUp(size.width, BLOCK_SIZE_X - (ksize.width - 1)) * BLOCK_SIZE_X;
globalsize[1] = divUp(size.height, BLOCK_SIZE_Y);
kernel.create("boxFilter", cv::ocl::imgproc::boxFilter_oclsrc, opts);
if (kernel.empty())
return false;
size_t kernelWorkGroupSize = kernel.workGroupSize();
if (localsize[0] <= kernelWorkGroupSize)
break;
if (BLOCK_SIZE_X < (int)kernelWorkGroupSize)
return false;
tryWorkItems = (int)kernelWorkGroupSize;
}
}
_dst.create(size, CV_MAKETYPE(ddepth, cn));
UMat dst = _dst.getUMat();
int idxArg = kernel.set(0, ocl::KernelArg::PtrReadOnly(src));
idxArg = kernel.set(idxArg, (int)src.step);
int srcOffsetX = (int)((src.offset % src.step) / src.elemSize());
int srcOffsetY = (int)(src.offset / src.step);
int srcEndX = isolated ? srcOffsetX + size.width : wholeSize.width;
int srcEndY = isolated ? srcOffsetY + size.height : wholeSize.height;
idxArg = kernel.set(idxArg, srcOffsetX);
idxArg = kernel.set(idxArg, srcOffsetY);
idxArg = kernel.set(idxArg, srcEndX);
idxArg = kernel.set(idxArg, srcEndY);
idxArg = kernel.set(idxArg, ocl::KernelArg::WriteOnly(dst));
if (normalize)
idxArg = kernel.set(idxArg, (float)alpha);
return kernel.run(2, globalsize, localsize, false);
}
#endif
Ptr<BaseRowFilter> getRowSumFilter(int srcType, int sumType, int ksize, int anchor)
{
CV_INSTRUMENT_REGION();
CV_CPU_DISPATCH(getRowSumFilter, (srcType, sumType, ksize, anchor),
CV_CPU_DISPATCH_MODES_ALL);
}
Ptr<BaseColumnFilter> getColumnSumFilter(int sumType, int dstType, int ksize, int anchor, double scale)
{
CV_INSTRUMENT_REGION();
CV_CPU_DISPATCH(getColumnSumFilter, (sumType, dstType, ksize, anchor, scale),
CV_CPU_DISPATCH_MODES_ALL);
}
Ptr<FilterEngine> createBoxFilter(int srcType, int dstType, Size ksize,
Point anchor, bool normalize, int borderType)
{
CV_INSTRUMENT_REGION();
CV_CPU_DISPATCH(createBoxFilter, (srcType, dstType, ksize, anchor, normalize, borderType),
CV_CPU_DISPATCH_MODES_ALL);
}
#ifdef HAVE_OPENVX
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_BOX_3x3>(int w, int h) { return w*h < 640 * 480; }
}
static bool openvx_boxfilter(InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType)
{
if (ddepth < 0)
ddepth = CV_8UC1;
if (_src.type() != CV_8UC1 || ddepth != CV_8U || !normalize ||
_src.cols() < 3 || _src.rows() < 3 ||
ksize.width != 3 || ksize.height != 3 ||
(anchor.x >= 0 && anchor.x != 1) ||
(anchor.y >= 0 && anchor.y != 1) ||
ovx::skipSmallImages<VX_KERNEL_BOX_3x3>(_src.cols(), _src.rows()))
return false;
Mat src = _src.getMat();
if ((borderType & BORDER_ISOLATED) == 0 && src.isSubmatrix())
return false; //Process isolated borders only
vx_enum border;
switch (borderType & ~BORDER_ISOLATED)
{
case BORDER_CONSTANT:
border = VX_BORDER_CONSTANT;
break;
case BORDER_REPLICATE:
border = VX_BORDER_REPLICATE;
break;
default:
return false;
}
_dst.create(src.size(), CV_8UC1);
Mat dst = _dst.getMat();
try
{
ivx::Context ctx = ovx::getOpenVXContext();
Mat a;
if (dst.data != src.data)
a = src;
else
src.copyTo(a);
ivx::Image
ia = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(a.cols, a.rows, 1, (vx_int32)(a.step)), a.data),
ib = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(dst.cols, dst.rows, 1, (vx_int32)(dst.step)), dst.data);
//ATTENTION: VX_CONTEXT_IMMEDIATE_BORDER attribute change could lead to strange issues in multi-threaded environments
//since OpenVX standard says nothing about thread-safety for now
ivx::border_t prevBorder = ctx.immediateBorder();
ctx.setImmediateBorder(border, (vx_uint8)(0));
ivx::IVX_CHECK_STATUS(vxuBox3x3(ctx, ia, ib));
ctx.setImmediateBorder(prevBorder);
}
catch (const ivx::RuntimeError & e)
{
VX_DbgThrow(e.what());
}
catch (const ivx::WrapperError & e)
{
VX_DbgThrow(e.what());
}
return true;
}
#endif
#if defined(HAVE_IPP)
static bool ipp_boxfilter(Mat &src, Mat &dst, Size ksize, Point anchor, bool normalize, int borderType)
{
#ifdef HAVE_IPP_IW
CV_INSTRUMENT_REGION_IPP();
#if IPP_VERSION_X100 < 201801
// Problem with SSE42 optimization for 16s and some 8u modes
if(ipp::getIppTopFeatures() == ippCPUID_SSE42 && (((src.depth() == CV_16S || src.depth() == CV_16U) && (src.channels() == 3 || src.channels() == 4)) || (src.depth() == CV_8U && src.channels() == 3 && (ksize.width > 5 || ksize.height > 5))))
return false;
// Other optimizations has some degradations too
if((((src.depth() == CV_16S || src.depth() == CV_16U) && (src.channels() == 4)) || (src.depth() == CV_8U && src.channels() == 1 && (ksize.width > 5 || ksize.height > 5))))
return false;
#endif
if(!normalize)
return false;
if(!ippiCheckAnchor(anchor, ksize))
return false;
try
{
::ipp::IwiImage iwSrc = ippiGetImage(src);
::ipp::IwiImage iwDst = ippiGetImage(dst);
::ipp::IwiSize iwKSize = ippiGetSize(ksize);
::ipp::IwiBorderSize borderSize(iwKSize);
::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize));
if(!ippBorder)
return false;
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterBox, iwSrc, iwDst, iwKSize, ::ipp::IwDefault(), ippBorder);
}
catch (const ::ipp::IwException &)
{
return false;
}
return true;
#else
CV_UNUSED(src); CV_UNUSED(dst); CV_UNUSED(ksize); CV_UNUSED(anchor); CV_UNUSED(normalize); CV_UNUSED(borderType);
return false;
#endif
}
#endif
void boxFilter(InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType)
{
CV_INSTRUMENT_REGION();
CV_OCL_RUN(_dst.isUMat() &&
(borderType == BORDER_REPLICATE || borderType == BORDER_CONSTANT ||
borderType == BORDER_REFLECT || borderType == BORDER_REFLECT_101),
ocl_boxFilter3x3_8UC1(_src, _dst, ddepth, ksize, anchor, borderType, normalize))
CV_OCL_RUN(_dst.isUMat(), ocl_boxFilter(_src, _dst, ddepth, ksize, anchor, borderType, normalize))
Mat src = _src.getMat();
int stype = src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype);
if( ddepth < 0 )
ddepth = sdepth;
_dst.create( src.size(), CV_MAKETYPE(ddepth, cn) );
Mat dst = _dst.getMat();
if( borderType != BORDER_CONSTANT && normalize && (borderType & BORDER_ISOLATED) != 0 )
{
if( src.rows == 1 )
ksize.height = 1;
if( src.cols == 1 )
ksize.width = 1;
}
Point ofs;
Size wsz(src.cols, src.rows);
if(!(borderType&BORDER_ISOLATED))
src.locateROI( wsz, ofs );
CALL_HAL(boxFilter, cv_hal_boxFilter, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, ddepth, cn,
ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, ksize.width, ksize.height,
anchor.x, anchor.y, normalize, borderType&~BORDER_ISOLATED);
CV_OVX_RUN(true,
openvx_boxfilter(src, dst, ddepth, ksize, anchor, normalize, borderType))
CV_IPP_RUN_FAST(ipp_boxfilter(src, dst, ksize, anchor, normalize, borderType));
borderType = (borderType&~BORDER_ISOLATED);
Ptr<FilterEngine> f = createBoxFilter( src.type(), dst.type(),
ksize, anchor, normalize, borderType );
f->apply( src, dst, wsz, ofs );
}
void blur(InputArray src, OutputArray dst,
Size ksize, Point anchor, int borderType)
{
CV_INSTRUMENT_REGION();
boxFilter( src, dst, -1, ksize, anchor, true, borderType );
}
/****************************************************************************************\
Squared Box Filter
\****************************************************************************************/
static Ptr<BaseRowFilter> getSqrRowSumFilter(int srcType, int sumType, int ksize, int anchor)
{
CV_INSTRUMENT_REGION();
CV_CPU_DISPATCH(getSqrRowSumFilter, (srcType, sumType, ksize, anchor),
CV_CPU_DISPATCH_MODES_ALL);
}
void sqrBoxFilter(InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType)
{
CV_INSTRUMENT_REGION();
int srcType = _src.type(), sdepth = CV_MAT_DEPTH(srcType), cn = CV_MAT_CN(srcType);
Size size = _src.size();
if( ddepth < 0 )
ddepth = sdepth < CV_32F ? CV_32F : CV_64F;
if( borderType != BORDER_CONSTANT && normalize )
{
if( size.height == 1 )
ksize.height = 1;
if( size.width == 1 )
ksize.width = 1;
}
CV_OCL_RUN(_dst.isUMat() && _src.dims() <= 2,
ocl_boxFilter(_src, _dst, ddepth, ksize, anchor, borderType, normalize, true))
int sumDepth = CV_64F;
if( sdepth == CV_8U )
sumDepth = CV_32S;
int sumType = CV_MAKETYPE( sumDepth, cn ), dstType = CV_MAKETYPE(ddepth, cn);
Mat src = _src.getMat();
_dst.create( size, dstType );
Mat dst = _dst.getMat();
Ptr<BaseRowFilter> rowFilter = getSqrRowSumFilter(srcType, sumType, ksize.width, anchor.x );
Ptr<BaseColumnFilter> columnFilter = getColumnSumFilter(sumType,
dstType, ksize.height, anchor.y,
normalize ? 1./(ksize.width*ksize.height) : 1);
Ptr<FilterEngine> f = makePtr<FilterEngine>(Ptr<BaseFilter>(), rowFilter, columnFilter,
srcType, dstType, sumType, borderType );
Point ofs;
Size wsz(src.cols, src.rows);
src.locateROI( wsz, ofs );
f->apply( src, dst, wsz, ofs );
}
} // namespace

549
modules/imgproc/src/box_filter.cpp → modules/imgproc/src/box_filter.simd.hpp
View File

@ -42,21 +42,25 @@
//M*/
#include "precomp.hpp"
#include <vector>
#include "opencv2/core/hal/intrin.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "opencv2/core/openvx/ovx_defs.hpp"
namespace cv {
CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
// forward declarations
Ptr<BaseRowFilter> getRowSumFilter(int srcType, int sumType, int ksize, int anchor);
Ptr<BaseColumnFilter> getColumnSumFilter(int sumType, int dstType, int ksize, int anchor, double scale);
Ptr<FilterEngine> createBoxFilter(int srcType, int dstType, Size ksize,
Point anchor, bool normalize, int borderType);
namespace cv
{
Ptr<BaseRowFilter> getSqrRowSumFilter(int srcType, int sumType, int ksize, int anchor);
#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
/****************************************************************************************\
Box Filter
\****************************************************************************************/
namespace {
template<typename T, typename ST>
struct RowSum :
public BaseRowFilter
@ -70,6 +74,8 @@ struct RowSum :
virtual void operator()(const uchar* src, uchar* dst, int width, int cn) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
const T* S = (const T*)src;
ST* D = (ST*)dst;
int i = 0, k, ksz_cn = ksize*cn;
@ -183,6 +189,8 @@ struct ColumnSum :
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int i;
ST* SUM;
bool haveScale = scale != 1;
@ -281,6 +289,8 @@ struct ColumnSum<int, uchar> :
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
@ -408,9 +418,6 @@ struct ColumnSum<int, uchar> :
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
@ -452,6 +459,8 @@ public BaseColumnFilter
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
const int ds = divScale;
const int dd = divDelta;
ushort* SUM;
@ -586,9 +595,6 @@ public BaseColumnFilter
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
@ -616,6 +622,8 @@ struct ColumnSum<int, short> :
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int i;
int* SUM;
bool haveScale = scale != 1;
@ -739,9 +747,6 @@ struct ColumnSum<int, short> :
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
@ -767,6 +772,8 @@ struct ColumnSum<int, ushort> :
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
@ -888,9 +895,6 @@ struct ColumnSum<int, ushort> :
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
@ -915,6 +919,8 @@ struct ColumnSum<int, int> :
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
@ -1022,9 +1028,6 @@ struct ColumnSum<int, int> :
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
@ -1050,6 +1053,8 @@ struct ColumnSum<int, float> :
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
@ -1154,9 +1159,6 @@ struct ColumnSum<int, float> :
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
@ -1164,243 +1166,13 @@ struct ColumnSum<int, float> :
std::vector<int> sum;
};
#ifdef HAVE_OPENCL
} // namespace anon
static bool ocl_boxFilter3x3_8UC1( InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor, int borderType, bool normalize )
Ptr<BaseRowFilter> getRowSumFilter(int srcType, int sumType, int ksize, int anchor)
{
const ocl::Device & dev = ocl::Device::getDefault();
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
CV_INSTRUMENT_REGION();
if (ddepth < 0)
ddepth = sdepth;
if (anchor.x < 0)
anchor.x = ksize.width / 2;
if (anchor.y < 0)
anchor.y = ksize.height / 2;
if ( !(dev.isIntel() && (type == CV_8UC1) &&
(_src.offset() == 0) && (_src.step() % 4 == 0) &&
(_src.cols() % 16 == 0) && (_src.rows() % 2 == 0) &&
(anchor.x == 1) && (anchor.y == 1) &&
(ksize.width == 3) && (ksize.height == 3)) )
return false;
float alpha = 1.0f / (ksize.height * ksize.width);
Size size = _src.size();
size_t globalsize[2] = { 0, 0 };
size_t localsize[2] = { 0, 0 };
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
globalsize[0] = size.width / 16;
globalsize[1] = size.height / 2;
char build_opts[1024];
sprintf(build_opts, "-D %s %s", borderMap[borderType], normalize ? "-D NORMALIZE" : "");
ocl::Kernel kernel("boxFilter3x3_8UC1_cols16_rows2", cv::ocl::imgproc::boxFilter3x3_oclsrc, build_opts);
if (kernel.empty())
return false;
UMat src = _src.getUMat();
_dst.create(size, CV_MAKETYPE(ddepth, cn));
if (!(_dst.offset() == 0 && _dst.step() % 4 == 0))
return false;
UMat dst = _dst.getUMat();
int idxArg = kernel.set(0, ocl::KernelArg::PtrReadOnly(src));
idxArg = kernel.set(idxArg, (int)src.step);
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst));
idxArg = kernel.set(idxArg, (int)dst.step);
idxArg = kernel.set(idxArg, (int)dst.rows);
idxArg = kernel.set(idxArg, (int)dst.cols);
if (normalize)
idxArg = kernel.set(idxArg, (float)alpha);
return kernel.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false);
}
static bool ocl_boxFilter( InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor, int borderType, bool normalize, bool sqr = false )
{
const ocl::Device & dev = ocl::Device::getDefault();
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type), esz = CV_ELEM_SIZE(type);
bool doubleSupport = dev.doubleFPConfig() > 0;
if (ddepth < 0)
ddepth = sdepth;
if (cn > 4 || (!doubleSupport && (sdepth == CV_64F || ddepth == CV_64F)) ||
_src.offset() % esz != 0 || _src.step() % esz != 0)
return false;
if (anchor.x < 0)
anchor.x = ksize.width / 2;
if (anchor.y < 0)
anchor.y = ksize.height / 2;
int computeUnits = ocl::Device::getDefault().maxComputeUnits();
float alpha = 1.0f / (ksize.height * ksize.width);
Size size = _src.size(), wholeSize;
bool isolated = (borderType & BORDER_ISOLATED) != 0;
borderType &= ~BORDER_ISOLATED;
int wdepth = std::max(CV_32F, std::max(ddepth, sdepth)),
wtype = CV_MAKE_TYPE(wdepth, cn), dtype = CV_MAKE_TYPE(ddepth, cn);
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
size_t globalsize[2] = { (size_t)size.width, (size_t)size.height };
size_t localsize_general[2] = { 0, 1 }, * localsize = NULL;
UMat src = _src.getUMat();
if (!isolated)
{
Point ofs;
src.locateROI(wholeSize, ofs);
}
int h = isolated ? size.height : wholeSize.height;
int w = isolated ? size.width : wholeSize.width;
size_t maxWorkItemSizes[32];
ocl::Device::getDefault().maxWorkItemSizes(maxWorkItemSizes);
int tryWorkItems = (int)maxWorkItemSizes[0];
ocl::Kernel kernel;
if (dev.isIntel() && !(dev.type() & ocl::Device::TYPE_CPU) &&
((ksize.width < 5 && ksize.height < 5 && esz <= 4) ||
(ksize.width == 5 && ksize.height == 5 && cn == 1)))
{
if (w < ksize.width || h < ksize.height)
return false;
// Figure out what vector size to use for loading the pixels.
int pxLoadNumPixels = cn != 1 || size.width % 4 ? 1 : 4;
int pxLoadVecSize = cn * pxLoadNumPixels;
// Figure out how many pixels per work item to compute in X and Y
// directions. Too many and we run out of registers.
int pxPerWorkItemX = 1, pxPerWorkItemY = 1;
if (cn <= 2 && ksize.width <= 4 && ksize.height <= 4)
{
pxPerWorkItemX = size.width % 8 ? size.width % 4 ? size.width % 2 ? 1 : 2 : 4 : 8;
pxPerWorkItemY = size.height % 2 ? 1 : 2;
}
else if (cn < 4 || (ksize.width <= 4 && ksize.height <= 4))
{
pxPerWorkItemX = size.width % 2 ? 1 : 2;
pxPerWorkItemY = size.height % 2 ? 1 : 2;
}
globalsize[0] = size.width / pxPerWorkItemX;
globalsize[1] = size.height / pxPerWorkItemY;
// Need some padding in the private array for pixels
int privDataWidth = roundUp(pxPerWorkItemX + ksize.width - 1, pxLoadNumPixels);
// Make the global size a nice round number so the runtime can pick
// from reasonable choices for the workgroup size
const int wgRound = 256;
globalsize[0] = roundUp(globalsize[0], wgRound);
char build_options[1024], cvt[2][40];
sprintf(build_options, "-D cn=%d "
"-D ANCHOR_X=%d -D ANCHOR_Y=%d -D KERNEL_SIZE_X=%d -D KERNEL_SIZE_Y=%d "
"-D PX_LOAD_VEC_SIZE=%d -D PX_LOAD_NUM_PX=%d "
"-D PX_PER_WI_X=%d -D PX_PER_WI_Y=%d -D PRIV_DATA_WIDTH=%d -D %s -D %s "
"-D PX_LOAD_X_ITERATIONS=%d -D PX_LOAD_Y_ITERATIONS=%d "
"-D srcT=%s -D srcT1=%s -D dstT=%s -D dstT1=%s -D WT=%s -D WT1=%s "
"-D convertToWT=%s -D convertToDstT=%s%s%s -D PX_LOAD_FLOAT_VEC_CONV=convert_%s -D OP_BOX_FILTER",
cn, anchor.x, anchor.y, ksize.width, ksize.height,
pxLoadVecSize, pxLoadNumPixels,
pxPerWorkItemX, pxPerWorkItemY, privDataWidth, borderMap[borderType],
isolated ? "BORDER_ISOLATED" : "NO_BORDER_ISOLATED",
privDataWidth / pxLoadNumPixels, pxPerWorkItemY + ksize.height - 1,
ocl::typeToStr(type), ocl::typeToStr(sdepth), ocl::typeToStr(dtype),
ocl::typeToStr(ddepth), ocl::typeToStr(wtype), ocl::typeToStr(wdepth),
ocl::convertTypeStr(sdepth, wdepth, cn, cvt[0]),
ocl::convertTypeStr(wdepth, ddepth, cn, cvt[1]),
normalize ? " -D NORMALIZE" : "", sqr ? " -D SQR" : "",
ocl::typeToStr(CV_MAKE_TYPE(wdepth, pxLoadVecSize)) //PX_LOAD_FLOAT_VEC_CONV
);
if (!kernel.create("filterSmall", cv::ocl::imgproc::filterSmall_oclsrc, build_options))
return false;
}
else
{
localsize = localsize_general;
for ( ; ; )
{
int BLOCK_SIZE_X = tryWorkItems, BLOCK_SIZE_Y = std::min(ksize.height * 10, size.height);
while (BLOCK_SIZE_X > 32 && BLOCK_SIZE_X >= ksize.width * 2 && BLOCK_SIZE_X > size.width * 2)
BLOCK_SIZE_X /= 2;
while (BLOCK_SIZE_Y < BLOCK_SIZE_X / 8 && BLOCK_SIZE_Y * computeUnits * 32 < size.height)
BLOCK_SIZE_Y *= 2;
if (ksize.width > BLOCK_SIZE_X || w < ksize.width || h < ksize.height)
return false;
char cvt[2][50];
String opts = format("-D LOCAL_SIZE_X=%d -D BLOCK_SIZE_Y=%d -D ST=%s -D DT=%s -D WT=%s -D convertToDT=%s -D convertToWT=%s"
" -D ANCHOR_X=%d -D ANCHOR_Y=%d -D KERNEL_SIZE_X=%d -D KERNEL_SIZE_Y=%d -D %s%s%s%s%s"
" -D ST1=%s -D DT1=%s -D cn=%d",
BLOCK_SIZE_X, BLOCK_SIZE_Y, ocl::typeToStr(type), ocl::typeToStr(CV_MAKE_TYPE(ddepth, cn)),
ocl::typeToStr(CV_MAKE_TYPE(wdepth, cn)),
ocl::convertTypeStr(wdepth, ddepth, cn, cvt[0]),
ocl::convertTypeStr(sdepth, wdepth, cn, cvt[1]),
anchor.x, anchor.y, ksize.width, ksize.height, borderMap[borderType],
isolated ? " -D BORDER_ISOLATED" : "", doubleSupport ? " -D DOUBLE_SUPPORT" : "",
normalize ? " -D NORMALIZE" : "", sqr ? " -D SQR" : "",
ocl::typeToStr(sdepth), ocl::typeToStr(ddepth), cn);
localsize[0] = BLOCK_SIZE_X;
globalsize[0] = divUp(size.width, BLOCK_SIZE_X - (ksize.width - 1)) * BLOCK_SIZE_X;
globalsize[1] = divUp(size.height, BLOCK_SIZE_Y);
kernel.create("boxFilter", cv::ocl::imgproc::boxFilter_oclsrc, opts);
if (kernel.empty())
return false;
size_t kernelWorkGroupSize = kernel.workGroupSize();
if (localsize[0] <= kernelWorkGroupSize)
break;
if (BLOCK_SIZE_X < (int)kernelWorkGroupSize)
return false;
tryWorkItems = (int)kernelWorkGroupSize;
}
}
_dst.create(size, CV_MAKETYPE(ddepth, cn));
UMat dst = _dst.getUMat();
int idxArg = kernel.set(0, ocl::KernelArg::PtrReadOnly(src));
idxArg = kernel.set(idxArg, (int)src.step);
int srcOffsetX = (int)((src.offset % src.step) / src.elemSize());
int srcOffsetY = (int)(src.offset / src.step);
int srcEndX = isolated ? srcOffsetX + size.width : wholeSize.width;
int srcEndY = isolated ? srcOffsetY + size.height : wholeSize.height;
idxArg = kernel.set(idxArg, srcOffsetX);
idxArg = kernel.set(idxArg, srcOffsetY);
idxArg = kernel.set(idxArg, srcEndX);
idxArg = kernel.set(idxArg, srcEndY);
idxArg = kernel.set(idxArg, ocl::KernelArg::WriteOnly(dst));
if (normalize)
idxArg = kernel.set(idxArg, (float)alpha);
return kernel.run(2, globalsize, localsize, false);
}
#endif
}
cv::Ptr<cv::BaseRowFilter> cv::getRowSumFilter(int srcType, int sumType, int ksize, int anchor)
{
int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(sumType);
CV_Assert( CV_MAT_CN(sumType) == CV_MAT_CN(srcType) );
@ -1434,9 +1206,10 @@ cv::Ptr<cv::BaseRowFilter> cv::getRowSumFilter(int srcType, int sumType, int ksi
}
cv::Ptr<cv::BaseColumnFilter> cv::getColumnSumFilter(int sumType, int dstType, int ksize,
int anchor, double scale)
Ptr<BaseColumnFilter> getColumnSumFilter(int sumType, int dstType, int ksize, int anchor, double scale)
{
CV_INSTRUMENT_REGION();
int sdepth = CV_MAT_DEPTH(sumType), ddepth = CV_MAT_DEPTH(dstType);
CV_Assert( CV_MAT_CN(sumType) == CV_MAT_CN(dstType) );
@ -1474,9 +1247,11 @@ cv::Ptr<cv::BaseColumnFilter> cv::getColumnSumFilter(int sumType, int dstType, i
}
cv::Ptr<cv::FilterEngine> cv::createBoxFilter( int srcType, int dstType, Size ksize,
Ptr<FilterEngine> createBoxFilter(int srcType, int dstType, Size ksize,
Point anchor, bool normalize, int borderType)
{
CV_INSTRUMENT_REGION();
int sdepth = CV_MAT_DEPTH(srcType);
int cn = CV_MAT_CN(srcType), sumType = CV_64F;
if( sdepth == CV_8U && CV_MAT_DEPTH(dstType) == CV_8U &&
@ -1496,201 +1271,11 @@ cv::Ptr<cv::FilterEngine> cv::createBoxFilter( int srcType, int dstType, Size ks
srcType, dstType, sumType, borderType );
}
#ifdef HAVE_OPENVX
namespace cv
{
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_BOX_3x3>(int w, int h) { return w*h < 640 * 480; }
}
static bool openvx_boxfilter(InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType)
{
if (ddepth < 0)
ddepth = CV_8UC1;
if (_src.type() != CV_8UC1 || ddepth != CV_8U || !normalize ||
_src.cols() < 3 || _src.rows() < 3 ||
ksize.width != 3 || ksize.height != 3 ||
(anchor.x >= 0 && anchor.x != 1) ||
(anchor.y >= 0 && anchor.y != 1) ||
ovx::skipSmallImages<VX_KERNEL_BOX_3x3>(_src.cols(), _src.rows()))
return false;
Mat src = _src.getMat();
if ((borderType & BORDER_ISOLATED) == 0 && src.isSubmatrix())
return false; //Process isolated borders only
vx_enum border;
switch (borderType & ~BORDER_ISOLATED)
{
case BORDER_CONSTANT:
border = VX_BORDER_CONSTANT;
break;
case BORDER_REPLICATE:
border = VX_BORDER_REPLICATE;
break;
default:
return false;
}
_dst.create(src.size(), CV_8UC1);
Mat dst = _dst.getMat();
try
{
ivx::Context ctx = ovx::getOpenVXContext();
Mat a;
if (dst.data != src.data)
a = src;
else
src.copyTo(a);
ivx::Image
ia = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(a.cols, a.rows, 1, (vx_int32)(a.step)), a.data),
ib = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(dst.cols, dst.rows, 1, (vx_int32)(dst.step)), dst.data);
//ATTENTION: VX_CONTEXT_IMMEDIATE_BORDER attribute change could lead to strange issues in multi-threaded environments
//since OpenVX standard says nothing about thread-safety for now
ivx::border_t prevBorder = ctx.immediateBorder();
ctx.setImmediateBorder(border, (vx_uint8)(0));
ivx::IVX_CHECK_STATUS(vxuBox3x3(ctx, ia, ib));
ctx.setImmediateBorder(prevBorder);
}
catch (const ivx::RuntimeError & e)
{
VX_DbgThrow(e.what());
}
catch (const ivx::WrapperError & e)
{
VX_DbgThrow(e.what());
}
return true;
}
}
#endif
#if defined(HAVE_IPP) && OPENCV_IPP_REDUCE_SIZE == 0
namespace cv
{
static bool ipp_boxfilter(Mat &src, Mat &dst, Size ksize, Point anchor, bool normalize, int borderType)
{
#ifdef HAVE_IPP_IW
CV_INSTRUMENT_REGION_IPP();
#if IPP_VERSION_X100 < 201801
// Problem with SSE42 optimization for 16s and some 8u modes
if(ipp::getIppTopFeatures() == ippCPUID_SSE42 && (((src.depth() == CV_16S || src.depth() == CV_16U) && (src.channels() == 3 || src.channels() == 4)) || (src.depth() == CV_8U && src.channels() == 3 && (ksize.width > 5 || ksize.height > 5))))
return false;
// Other optimizations has some degradations too
if((((src.depth() == CV_16S || src.depth() == CV_16U) && (src.channels() == 4)) || (src.depth() == CV_8U && src.channels() == 1 && (ksize.width > 5 || ksize.height > 5))))
return false;
#endif
if(!normalize)
return false;
if(!ippiCheckAnchor(anchor, ksize))
return false;
try
{
::ipp::IwiImage iwSrc = ippiGetImage(src);
::ipp::IwiImage iwDst = ippiGetImage(dst);
::ipp::IwiSize iwKSize = ippiGetSize(ksize);
::ipp::IwiBorderSize borderSize(iwKSize);
::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize));
if(!ippBorder)
return false;
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterBox, iwSrc, iwDst, iwKSize, ::ipp::IwDefault(), ippBorder);
}
catch (const ::ipp::IwException &)
{
return false;
}
return true;
#else
CV_UNUSED(src); CV_UNUSED(dst); CV_UNUSED(ksize); CV_UNUSED(anchor); CV_UNUSED(normalize); CV_UNUSED(borderType);
return false;
#endif
}
}
#endif
void cv::boxFilter( InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType )
{
CV_INSTRUMENT_REGION();
CV_OCL_RUN(_dst.isUMat() &&
(borderType == BORDER_REPLICATE || borderType == BORDER_CONSTANT ||
borderType == BORDER_REFLECT || borderType == BORDER_REFLECT_101),
ocl_boxFilter3x3_8UC1(_src, _dst, ddepth, ksize, anchor, borderType, normalize))
CV_OCL_RUN(_dst.isUMat(), ocl_boxFilter(_src, _dst, ddepth, ksize, anchor, borderType, normalize))
Mat src = _src.getMat();
int stype = src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype);
if( ddepth < 0 )
ddepth = sdepth;
_dst.create( src.size(), CV_MAKETYPE(ddepth, cn) );
Mat dst = _dst.getMat();
if( borderType != BORDER_CONSTANT && normalize && (borderType & BORDER_ISOLATED) != 0 )
{
if( src.rows == 1 )
ksize.height = 1;
if( src.cols == 1 )
ksize.width = 1;
}
Point ofs;
Size wsz(src.cols, src.rows);
if(!(borderType&BORDER_ISOLATED))
src.locateROI( wsz, ofs );
CALL_HAL(boxFilter, cv_hal_boxFilter, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, ddepth, cn,
ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, ksize.width, ksize.height,
anchor.x, anchor.y, normalize, borderType&~BORDER_ISOLATED);
CV_OVX_RUN(true,
openvx_boxfilter(src, dst, ddepth, ksize, anchor, normalize, borderType))
#if OPENCV_IPP_REDUCE_SIZE == 0
CV_IPP_RUN_FAST(ipp_boxfilter(src, dst, ksize, anchor, normalize, borderType));
#endif
borderType = (borderType&~BORDER_ISOLATED);
Ptr<FilterEngine> f = createBoxFilter( src.type(), dst.type(),
ksize, anchor, normalize, borderType );
f->apply( src, dst, wsz, ofs );
}
void cv::blur( InputArray src, OutputArray dst,
Size ksize, Point anchor, int borderType )
{
CV_INSTRUMENT_REGION();
boxFilter( src, dst, -1, ksize, anchor, true, borderType );
}
/****************************************************************************************\
Squared Box Filter
\****************************************************************************************/
namespace cv
{
namespace {
template<typename T, typename ST>
struct SqrRowSum :
@ -1705,6 +1290,8 @@ struct SqrRowSum :
virtual void operator()(const uchar* src, uchar* dst, int width, int cn) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
const T* S = (const T*)src;
ST* D = (ST*)dst;
int i = 0, k, ksz_cn = ksize*cn;
@ -1729,7 +1316,9 @@ struct SqrRowSum :
}
};
static Ptr<BaseRowFilter> getSqrRowSumFilter(int srcType, int sumType, int ksize, int anchor)
} // namespace anon
Ptr<BaseRowFilter> getSqrRowSumFilter(int srcType, int sumType, int ksize, int anchor)
{
int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(sumType);
CV_Assert( CV_MAT_CN(sumType) == CV_MAT_CN(srcType) );
@ -1755,52 +1344,6 @@ static Ptr<BaseRowFilter> getSqrRowSumFilter(int srcType, int sumType, int ksize
srcType, sumType));
}
}
void cv::sqrBoxFilter( InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType )
{
CV_INSTRUMENT_REGION();
int srcType = _src.type(), sdepth = CV_MAT_DEPTH(srcType), cn = CV_MAT_CN(srcType);
Size size = _src.size();
if( ddepth < 0 )
ddepth = sdepth < CV_32F ? CV_32F : CV_64F;
if( borderType != BORDER_CONSTANT && normalize )
{
if( size.height == 1 )
ksize.height = 1;
if( size.width == 1 )
ksize.width = 1;
}
CV_OCL_RUN(_dst.isUMat() && _src.dims() <= 2,
ocl_boxFilter(_src, _dst, ddepth, ksize, anchor, borderType, normalize, true))
int sumDepth = CV_64F;
if( sdepth == CV_8U )
sumDepth = CV_32S;
int sumType = CV_MAKETYPE( sumDepth, cn ), dstType = CV_MAKETYPE(ddepth, cn);
Mat src = _src.getMat();
_dst.create( size, dstType );
Mat dst = _dst.getMat();
Ptr<BaseRowFilter> rowFilter = getSqrRowSumFilter(srcType, sumType, ksize.width, anchor.x );
Ptr<BaseColumnFilter> columnFilter = getColumnSumFilter(sumType,
dstType, ksize.height, anchor.y,
normalize ? 1./(ksize.width*ksize.height) : 1);
Ptr<FilterEngine> f = makePtr<FilterEngine>(Ptr<BaseFilter>(), rowFilter, columnFilter,
srcType, dstType, sumType, borderType );
Point ofs;
Size wsz(src.cols, src.rows);
src.locateROI( wsz, ofs );
f->apply( src, dst, wsz, ofs );
}
/* End of file. */
#endif
CV_CPU_OPTIMIZATION_NAMESPACE_END
} // namespace

1
modules/imgproc/src/color.cpp
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@ -3,6 +3,7 @@
// of this distribution and at http://opencv.org/license.html
#include "precomp.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "color.hpp"
namespace cv

133
modules/imgproc/src/color.hpp
View File

@ -3,63 +3,17 @@
// of this distribution and at http://opencv.org/license.html
#include "opencv2/imgproc.hpp"
#include "opencv2/core/utility.hpp"
#include <limits>
#include "opencl_kernels_imgproc.hpp"
#include "hal_replacement.hpp"
#include "opencv2/core/hal/intrin.hpp"
#include "opencv2/core/softfloat.hpp"
#define CV_DESCALE(x,n) (((x) + (1 << ((n)-1))) >> (n))
namespace cv
{
//constants for conversion from/to RGB and Gray, YUV, YCrCb according to BT.601
const float B2YF = 0.114f;
const float G2YF = 0.587f;
const float R2YF = 0.299f;
enum
{
gray_shift = 15,
yuv_shift = 14,
xyz_shift = 12,
R2Y = 4899, // == R2YF*16384
G2Y = 9617, // == G2YF*16384
B2Y = 1868, // == B2YF*16384
RY15 = 9798, // == R2YF*32768 + 0.5
GY15 = 19235, // == G2YF*32768 + 0.5
BY15 = 3735, // == B2YF*32768 + 0.5
BLOCK_SIZE = 256
};
template<typename _Tp> struct ColorChannel
{
typedef float worktype_f;
static _Tp max() { return std::numeric_limits<_Tp>::max(); }
static _Tp half() { return (_Tp)(max()/2 + 1); }
};
template<> struct ColorChannel<float>
{
typedef float worktype_f;
static float max() { return 1.f; }
static float half() { return 0.5f; }
};
/*template<> struct ColorChannel<double>
{
typedef double worktype_f;
static double max() { return 1.; }
static double half() { return 0.5; }
};*/
namespace cv {
//
// Helper functions
//
namespace {
namespace impl {
#include "color.simd_helpers.hpp"
inline bool isHSV(int code)
{
@ -213,40 +167,9 @@ inline int uIndex(int code)
}
} // namespace::
using namespace impl;
template<int i0, int i1 = -1, int i2 = -1>
struct Set
{
static bool contains(int i)
{
return (i == i0 || i == i1 || i == i2);
}
};
template<int i0, int i1>
struct Set<i0, i1, -1>
{
static bool contains(int i)
{
return (i == i0 || i == i1);
}
};
template<int i0>
struct Set<i0, -1, -1>
{
static bool contains(int i)
{
return (i == i0);
}
};
enum SizePolicy
{
TO_YUV, FROM_YUV, NONE
};
template< typename VScn, typename VDcn, typename VDepth, SizePolicy sizePolicy = NONE >
/*template< typename VScn, typename VDcn, typename VDepth, SizePolicy sizePolicy = NONE >
struct CvtHelper
{
CvtHelper(InputArray _src, OutputArray _dst, int dcn)
@ -286,7 +209,7 @@ struct CvtHelper
Mat src, dst;
int depth, scn;
Size dstSz;
};
};*/
#ifdef HAVE_OPENCL
@ -384,49 +307,7 @@ struct OclHelper
#endif
///////////////////////////// Top-level template function ////////////////////////////////
template <typename Cvt>
class CvtColorLoop_Invoker : public ParallelLoopBody
{
typedef typename Cvt::channel_type _Tp;
public:
CvtColorLoop_Invoker(const uchar * src_data_, size_t src_step_, uchar * dst_data_, size_t dst_step_, int width_, const Cvt& _cvt) :
ParallelLoopBody(), src_data(src_data_), src_step(src_step_), dst_data(dst_data_), dst_step(dst_step_),
width(width_), cvt(_cvt)
{
}
virtual void operator()(const Range& range) const CV_OVERRIDE
{
CV_TRACE_FUNCTION();
const uchar* yS = src_data + static_cast<size_t>(range.start) * src_step;
uchar* yD = dst_data + static_cast<size_t>(range.start) * dst_step;
for( int i = range.start; i < range.end; ++i, yS += src_step, yD += dst_step )
cvt(reinterpret_cast<const _Tp*>(yS), reinterpret_cast<_Tp*>(yD), width);
}
private:
const uchar * src_data;
const size_t src_step;
uchar * dst_data;
const size_t dst_step;
const int width;
const Cvt& cvt;
const CvtColorLoop_Invoker& operator= (const CvtColorLoop_Invoker&);
};
template <typename Cvt>
void CvtColorLoop(const uchar * src_data, size_t src_step, uchar * dst_data, size_t dst_step, int width, int height, const Cvt& cvt)
{
parallel_for_(Range(0, height),
CvtColorLoop_Invoker<Cvt>(src_data, src_step, dst_data, dst_step, width, cvt),
(width * height) / static_cast<double>(1<<16));
}
#if defined (HAVE_IPP) && (IPP_VERSION_X100 >= 700)
# define NEED_IPP 1

171
modules/imgproc/src/color.simd_helpers.hpp Normal file
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@ -0,0 +1,171 @@
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#define CV_DESCALE(x,n) (((x) + (1 << ((n)-1))) >> (n))
namespace {
//constants for conversion from/to RGB and Gray, YUV, YCrCb according to BT.601
static const float B2YF = 0.114f;
static const float G2YF = 0.587f;
static const float R2YF = 0.299f;
enum
{
gray_shift = 15,
yuv_shift = 14,
xyz_shift = 12,
R2Y = 4899, // == R2YF*16384
G2Y = 9617, // == G2YF*16384
B2Y = 1868, // == B2YF*16384
RY15 = 9798, // == R2YF*32768 + 0.5
GY15 = 19235, // == G2YF*32768 + 0.5
BY15 = 3735, // == B2YF*32768 + 0.5
BLOCK_SIZE = 256
};
template<typename _Tp> struct ColorChannel
{
typedef float worktype_f;
static inline _Tp max() { return std::numeric_limits<_Tp>::max(); }
static inline _Tp half() { return (_Tp)(max()/2 + 1); }
};
template<> struct ColorChannel<float>
{
typedef float worktype_f;
static inline float max() { return 1.f; }
static inline float half() { return 0.5f; }
};
/*template<> struct ColorChannel<double>
{
typedef double worktype_f;
static double max() { return 1.; }
static double half() { return 0.5; }
};*/
template<int i0, int i1 = -1, int i2 = -1>
struct Set
{
static inline bool contains(int i)
{
return (i == i0 || i == i1 || i == i2);
}
};
template<int i0, int i1>
struct Set<i0, i1, -1>
{
static inline bool contains(int i)
{
return (i == i0 || i == i1);
}
};
template<int i0>
struct Set<i0, -1, -1>
{
static inline bool contains(int i)
{
return (i == i0);
}
};
enum SizePolicy
{
TO_YUV, FROM_YUV, NONE
};
template< typename VScn, typename VDcn, typename VDepth, SizePolicy sizePolicy = NONE >
struct CvtHelper
{
CvtHelper(InputArray _src, OutputArray _dst, int dcn)
{
CV_Assert(!_src.empty());
int stype = _src.type();
scn = CV_MAT_CN(stype), depth = CV_MAT_DEPTH(stype);
CV_Check(scn, VScn::contains(scn), "Invalid number of channels in input image");
CV_Check(dcn, VDcn::contains(dcn), "Invalid number of channels in output image");
CV_CheckDepth(depth, VDepth::contains(depth), "Unsupported depth of input image");
if (_src.getObj() == _dst.getObj()) // inplace processing (#6653)
_src.copyTo(src);
else
src = _src.getMat();
Size sz = src.size();
switch (sizePolicy)
{
case TO_YUV:
CV_Assert( sz.width % 2 == 0 && sz.height % 2 == 0);
dstSz = Size(sz.width, sz.height / 2 * 3);
break;
case FROM_YUV:
CV_Assert( sz.width % 2 == 0 && sz.height % 3 == 0);
dstSz = Size(sz.width, sz.height * 2 / 3);
break;
case NONE:
default:
dstSz = sz;
break;
}
_dst.create(dstSz, CV_MAKETYPE(depth, dcn));
dst = _dst.getMat();
}
Mat src, dst;
int depth, scn;
Size dstSz;
};
///////////////////////////// Top-level template function ////////////////////////////////
template <typename Cvt>
class CvtColorLoop_Invoker : public ParallelLoopBody
{
typedef typename Cvt::channel_type _Tp;
public:
CvtColorLoop_Invoker(const uchar * src_data_, size_t src_step_, uchar * dst_data_, size_t dst_step_, int width_, const Cvt& _cvt) :
ParallelLoopBody(), src_data(src_data_), src_step(src_step_), dst_data(dst_data_), dst_step(dst_step_),
width(width_), cvt(_cvt)
{
}
virtual void operator()(const Range& range) const CV_OVERRIDE
{
CV_TRACE_FUNCTION();
const uchar* yS = src_data + static_cast<size_t>(range.start) * src_step;
uchar* yD = dst_data + static_cast<size_t>(range.start) * dst_step;
for( int i = range.start; i < range.end; ++i, yS += src_step, yD += dst_step )
cvt(reinterpret_cast<const _Tp*>(yS), reinterpret_cast<_Tp*>(yD), width);
}
private:
const uchar * src_data;
const size_t src_step;
uchar * dst_data;
const size_t dst_step;
const int width;
const Cvt& cvt;
CvtColorLoop_Invoker(const CvtColorLoop_Invoker&); // = delete;
const CvtColorLoop_Invoker& operator= (const CvtColorLoop_Invoker&); // = delete;
};
template <typename Cvt> static inline
void CvtColorLoop(const uchar * src_data, size_t src_step, uchar * dst_data, size_t dst_step, int width, int height, const Cvt& cvt)
{
CV_AVX_GUARD
parallel_for_(Range(0, height),
CvtColorLoop_Invoker<Cvt>(src_data, src_step, dst_data, dst_step, width, cvt),
(width * height) / static_cast<double>(1<<16));
}
} //namespace

358
modules/imgproc/src/color_hsv.dispatch.cpp Normal file
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@ -0,0 +1,358 @@
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#include "precomp.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "color.hpp"
#include "color_hsv.simd.hpp"
#include "color_hsv.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
namespace cv {
//
// IPP functions
//
#if NEED_IPP
#if !IPP_DISABLE_RGB_HSV
static ippiGeneralFunc ippiRGB2HSVTab[] =
{
(ippiGeneralFunc)ippiRGBToHSV_8u_C3R, 0, (ippiGeneralFunc)ippiRGBToHSV_16u_C3R, 0,
0, 0, 0, 0
};
#endif
static ippiGeneralFunc ippiHSV2RGBTab[] =
{
(ippiGeneralFunc)ippiHSVToRGB_8u_C3R, 0, (ippiGeneralFunc)ippiHSVToRGB_16u_C3R, 0,
0, 0, 0, 0
};
static ippiGeneralFunc ippiRGB2HLSTab[] =
{
(ippiGeneralFunc)ippiRGBToHLS_8u_C3R, 0, (ippiGeneralFunc)ippiRGBToHLS_16u_C3R, 0,
0, (ippiGeneralFunc)ippiRGBToHLS_32f_C3R, 0, 0
};
static ippiGeneralFunc ippiHLS2RGBTab[] =
{
(ippiGeneralFunc)ippiHLSToRGB_8u_C3R, 0, (ippiGeneralFunc)ippiHLSToRGB_16u_C3R, 0,
0, (ippiGeneralFunc)ippiHLSToRGB_32f_C3R, 0, 0
};
#endif
//
// HAL functions
//
namespace hal
{
// 8u, 32f
void cvtBGRtoHSV(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int scn, bool swapBlue, bool isFullRange, bool isHSV)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGRtoHSV, cv_hal_cvtBGRtoHSV, src_data, src_step, dst_data, dst_step, width, height, depth, scn, swapBlue, isFullRange, isHSV);
#if defined(HAVE_IPP) && IPP_VERSION_X100 >= 700
CV_IPP_CHECK()
{
if(depth == CV_8U && isFullRange)
{
if (isHSV)
{
#if !IPP_DISABLE_RGB_HSV // breaks OCL accuracy tests
if(scn == 3 && !swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKE_TYPE(depth, scn), dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC3RTab[depth], ippiRGB2HSVTab[depth], 2, 1, 0, depth)) )
return;
}
else if(scn == 4 && !swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC4C3RTab[depth], ippiRGB2HSVTab[depth], 2, 1, 0, depth)) )
return;
}
else if(scn == 4 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC4C3RTab[depth], ippiRGB2HSVTab[depth], 0, 1, 2, depth)) )
return;
}
#endif
}
else
{
if(scn == 3 && !swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKE_TYPE(depth, scn), dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC3RTab[depth], ippiRGB2HLSTab[depth], 2, 1, 0, depth)) )
return;
}
else if(scn == 4 && !swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC4C3RTab[depth], ippiRGB2HLSTab[depth], 2, 1, 0, depth)) )
return;
}
else if(scn == 3 && swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKE_TYPE(depth, scn), dst_data, dst_step, width, height,
IPPGeneralFunctor(ippiRGB2HLSTab[depth])) )
return;
}
else if(scn == 4 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC4C3RTab[depth], ippiRGB2HLSTab[depth], 0, 1, 2, depth)) )
return;
}
}
}
}
#endif
CV_CPU_DISPATCH(cvtBGRtoHSV, (src_data, src_step, dst_data, dst_step, width, height, depth, scn, swapBlue, isFullRange, isHSV),
CV_CPU_DISPATCH_MODES_ALL);
}
// 8u, 32f
void cvtHSVtoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int dcn, bool swapBlue, bool isFullRange, bool isHSV)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtHSVtoBGR, cv_hal_cvtHSVtoBGR, src_data, src_step, dst_data, dst_step, width, height, depth, dcn, swapBlue, isFullRange, isHSV);
#if defined(HAVE_IPP) && IPP_VERSION_X100 >= 700
CV_IPP_CHECK()
{
if (depth == CV_8U && isFullRange)
{
if (isHSV)
{
if(dcn == 3 && !swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKETYPE(depth, 3), dst_data, dst_step, width, height,
IPPGeneralReorderFunctor(ippiHSV2RGBTab[depth], ippiSwapChannelsC3RTab[depth], 2, 1, 0, depth)) )
return;
}
else if(dcn == 4 && !swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor(ippiHSV2RGBTab[depth], ippiSwapChannelsC3C4RTab[depth], 2, 1, 0, depth)) )
return;
}
else if(dcn == 3 && swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKETYPE(depth, 3), dst_data, dst_step, width, height,
IPPGeneralFunctor(ippiHSV2RGBTab[depth])) )
return;
}
else if(dcn == 4 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor(ippiHSV2RGBTab[depth], ippiSwapChannelsC3C4RTab[depth], 0, 1, 2, depth)) )
return;
}
}
else
{
if(dcn == 3 && !swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKETYPE(depth, 3), dst_data, dst_step, width, height,
IPPGeneralReorderFunctor(ippiHLS2RGBTab[depth], ippiSwapChannelsC3RTab[depth], 2, 1, 0, depth)) )
return;
}
else if(dcn == 4 && !swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor(ippiHLS2RGBTab[depth], ippiSwapChannelsC3C4RTab[depth], 2, 1, 0, depth)) )
return;
}
else if(dcn == 3 && swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKETYPE(depth, 3), dst_data, dst_step, width, height,
IPPGeneralFunctor(ippiHLS2RGBTab[depth])) )
return;
}
else if(dcn == 4 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor(ippiHLS2RGBTab[depth], ippiSwapChannelsC3C4RTab[depth], 0, 1, 2, depth)) )
return;
}
}
}
}
#endif
CV_CPU_DISPATCH(cvtHSVtoBGR, (src_data, src_step, dst_data, dst_step, width, height, depth, dcn, swapBlue, isFullRange, isHSV),
CV_CPU_DISPATCH_MODES_ALL);
}
} // namespace hal
//
// OCL calls
//
#ifdef HAVE_OPENCL
bool oclCvtColorHSV2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx, bool full )
{
OclHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_32F> > h(_src, _dst, dcn);
int hrange = _src.depth() == CV_32F ? 360 : (!full ? 180 : 255);
if(!h.createKernel("HSV2RGB", ocl::imgproc::color_hsv_oclsrc,
format("-D dcn=%d -D bidx=%d -D hrange=%d -D hscale=%ff", dcn, bidx, hrange, 6.f/hrange)))
{
return false;
}
return h.run();
}
bool oclCvtColorHLS2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx, bool full )
{
OclHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_32F> > h(_src, _dst, dcn);
int hrange = _src.depth() == CV_32F ? 360 : (!full ? 180 : 255);
if(!h.createKernel("HLS2RGB", ocl::imgproc::color_hsv_oclsrc,
format("-D dcn=%d -D bidx=%d -D hrange=%d -D hscale=%ff", dcn, bidx, hrange, 6.f/hrange)))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR2HLS( InputArray _src, OutputArray _dst, int bidx, bool full )
{
OclHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_32F> > h(_src, _dst, 3);
float hscale = (_src.depth() == CV_32F ? 360.f : (!full ? 180.f : 256.f))/360.f;
if(!h.createKernel("RGB2HLS", ocl::imgproc::color_hsv_oclsrc,
format("-D hscale=%ff -D bidx=%d -D dcn=3", hscale, bidx)))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR2HSV( InputArray _src, OutputArray _dst, int bidx, bool full )
{
OclHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_32F> > h(_src, _dst, 3);
int hrange = _src.depth() == CV_32F ? 360 : (!full ? 180 : 256);
cv::String options = (_src.depth() == CV_8U ?
format("-D hrange=%d -D bidx=%d -D dcn=3", hrange, bidx) :
format("-D hscale=%ff -D bidx=%d -D dcn=3", hrange*(1.f/360.f), bidx));
if(!h.createKernel("RGB2HSV", ocl::imgproc::color_hsv_oclsrc, options))
{
return false;
}
if(_src.depth() == CV_8U)
{
static UMat sdiv_data;
static UMat hdiv_data180;
static UMat hdiv_data256;
static int sdiv_table[256];
static int hdiv_table180[256];
static int hdiv_table256[256];
static volatile bool initialized180 = false, initialized256 = false;
volatile bool & initialized = hrange == 180 ? initialized180 : initialized256;
if (!initialized)
{
int * const hdiv_table = hrange == 180 ? hdiv_table180 : hdiv_table256, hsv_shift = 12;
UMat & hdiv_data = hrange == 180 ? hdiv_data180 : hdiv_data256;
sdiv_table[0] = hdiv_table180[0] = hdiv_table256[0] = 0;
int v = 255 << hsv_shift;
if (!initialized180 && !initialized256)
{
for(int i = 1; i < 256; i++ )
sdiv_table[i] = saturate_cast<int>(v/(1.*i));
Mat(1, 256, CV_32SC1, sdiv_table).copyTo(sdiv_data);
}
v = hrange << hsv_shift;
for (int i = 1; i < 256; i++ )
hdiv_table[i] = saturate_cast<int>(v/(6.*i));
Mat(1, 256, CV_32SC1, hdiv_table).copyTo(hdiv_data);
initialized = true;
}
h.setArg(ocl::KernelArg::PtrReadOnly(sdiv_data));
h.setArg(hrange == 256 ? ocl::KernelArg::PtrReadOnly(hdiv_data256) :
ocl::KernelArg::PtrReadOnly(hdiv_data180));
}
return h.run();
}
#endif
//
// HAL calls
//
void cvtColorBGR2HLS( InputArray _src, OutputArray _dst, bool swapb, bool fullRange )
{
CvtHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_32F> > h(_src, _dst, 3);
hal::cvtBGRtoHSV(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, h.scn, swapb, fullRange, false);
}
void cvtColorBGR2HSV( InputArray _src, OutputArray _dst, bool swapb, bool fullRange )
{
CvtHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_32F> > h(_src, _dst, 3);
hal::cvtBGRtoHSV(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, h.scn, swapb, fullRange, true);
}
void cvtColorHLS2BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb, bool fullRange)
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_32F> > h(_src, _dst, dcn);
hal::cvtHSVtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, dcn, swapb, fullRange, false);
}
void cvtColorHSV2BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb, bool fullRange)
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_32F> > h(_src, _dst, dcn);
hal::cvtHSVtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, dcn, swapb, fullRange, true);
}
} // namespace cv

346
modules/imgproc/src/color_hsv.cpp → modules/imgproc/src/color_hsv.simd.hpp
View File

@ -3,11 +3,31 @@
// of this distribution and at http://opencv.org/license.html
#include "precomp.hpp"
#include "color.hpp"
#include "opencv2/core/hal/intrin.hpp"
namespace cv
{
namespace cv {
namespace hal {
CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
// forward declarations
void cvtBGRtoHSV(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int scn, bool swapBlue, bool isFullRange, bool isHSV);
void cvtHSVtoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int dcn, bool swapBlue, bool isFullRange, bool isHSV);
#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
#if defined(CV_CPU_BASELINE_MODE)
// included in color.hpp
#else
#include "color.simd_helpers.hpp"
#endif
namespace {
////////////////////////////////////// RGB <-> HSV ///////////////////////////////////////
@ -1192,46 +1212,7 @@ struct HLS2RGB_b
#endif
};
//
// IPP functions
//
#if NEED_IPP
#if !IPP_DISABLE_RGB_HSV
static ippiGeneralFunc ippiRGB2HSVTab[] =
{
(ippiGeneralFunc)ippiRGBToHSV_8u_C3R, 0, (ippiGeneralFunc)ippiRGBToHSV_16u_C3R, 0,
0, 0, 0, 0
};
#endif
static ippiGeneralFunc ippiHSV2RGBTab[] =
{
(ippiGeneralFunc)ippiHSVToRGB_8u_C3R, 0, (ippiGeneralFunc)ippiHSVToRGB_16u_C3R, 0,
0, 0, 0, 0
};
static ippiGeneralFunc ippiRGB2HLSTab[] =
{
(ippiGeneralFunc)ippiRGBToHLS_8u_C3R, 0, (ippiGeneralFunc)ippiRGBToHLS_16u_C3R, 0,
0, (ippiGeneralFunc)ippiRGBToHLS_32f_C3R, 0, 0
};
static ippiGeneralFunc ippiHLS2RGBTab[] =
{
(ippiGeneralFunc)ippiHLSToRGB_8u_C3R, 0, (ippiGeneralFunc)ippiHLSToRGB_16u_C3R, 0,
0, (ippiGeneralFunc)ippiHLSToRGB_32f_C3R, 0, 0
};
#endif
//
// HAL functions
//
namespace hal
{
} // namespace anon
// 8u, 32f
void cvtBGRtoHSV(const uchar * src_data, size_t src_step,
@ -1241,67 +1222,6 @@ void cvtBGRtoHSV(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGRtoHSV, cv_hal_cvtBGRtoHSV, src_data, src_step, dst_data, dst_step, width, height, depth, scn, swapBlue, isFullRange, isHSV);
#if defined(HAVE_IPP) && IPP_VERSION_X100 >= 700
CV_IPP_CHECK()
{
if(depth == CV_8U && isFullRange)
{
if (isHSV)
{
#if !IPP_DISABLE_RGB_HSV // breaks OCL accuracy tests
if(scn == 3 && !swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKE_TYPE(depth, scn), dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC3RTab[depth], ippiRGB2HSVTab[depth], 2, 1, 0, depth)) )
return;
}
else if(scn == 4 && !swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC4C3RTab[depth], ippiRGB2HSVTab[depth], 2, 1, 0, depth)) )
return;
}
else if(scn == 4 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC4C3RTab[depth], ippiRGB2HSVTab[depth], 0, 1, 2, depth)) )
return;
}
#endif
}
else
{
if(scn == 3 && !swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKE_TYPE(depth, scn), dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC3RTab[depth], ippiRGB2HLSTab[depth], 2, 1, 0, depth)) )
return;
}
else if(scn == 4 && !swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC4C3RTab[depth], ippiRGB2HLSTab[depth], 2, 1, 0, depth)) )
return;
}
else if(scn == 3 && swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKE_TYPE(depth, scn), dst_data, dst_step, width, height,
IPPGeneralFunctor(ippiRGB2HLSTab[depth])) )
return;
}
else if(scn == 4 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC4C3RTab[depth], ippiRGB2HLSTab[depth], 0, 1, 2, depth)) )
return;
}
}
}
}
#endif
int hrange = depth == CV_32F ? 360 : isFullRange ? 256 : 180;
int blueIdx = swapBlue ? 2 : 0;
if(isHSV)
@ -1328,71 +1248,6 @@ void cvtHSVtoBGR(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtHSVtoBGR, cv_hal_cvtHSVtoBGR, src_data, src_step, dst_data, dst_step, width, height, depth, dcn, swapBlue, isFullRange, isHSV);
#if defined(HAVE_IPP) && IPP_VERSION_X100 >= 700
CV_IPP_CHECK()
{
if (depth == CV_8U && isFullRange)
{
if (isHSV)
{
if(dcn == 3 && !swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKETYPE(depth, 3), dst_data, dst_step, width, height,
IPPGeneralReorderFunctor(ippiHSV2RGBTab[depth], ippiSwapChannelsC3RTab[depth], 2, 1, 0, depth)) )
return;
}
else if(dcn == 4 && !swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor(ippiHSV2RGBTab[depth], ippiSwapChannelsC3C4RTab[depth], 2, 1, 0, depth)) )
return;
}
else if(dcn == 3 && swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKETYPE(depth, 3), dst_data, dst_step, width, height,
IPPGeneralFunctor(ippiHSV2RGBTab[depth])) )
return;
}
else if(dcn == 4 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor(ippiHSV2RGBTab[depth], ippiSwapChannelsC3C4RTab[depth], 0, 1, 2, depth)) )
return;
}
}
else
{
if(dcn == 3 && !swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKETYPE(depth, 3), dst_data, dst_step, width, height,
IPPGeneralReorderFunctor(ippiHLS2RGBTab[depth], ippiSwapChannelsC3RTab[depth], 2, 1, 0, depth)) )
return;
}
else if(dcn == 4 && !swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor(ippiHLS2RGBTab[depth], ippiSwapChannelsC3C4RTab[depth], 2, 1, 0, depth)) )
return;
}
else if(dcn == 3 && swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKETYPE(depth, 3), dst_data, dst_step, width, height,
IPPGeneralFunctor(ippiHLS2RGBTab[depth])) )
return;
}
else if(dcn == 4 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor(ippiHLS2RGBTab[depth], ippiSwapChannelsC3C4RTab[depth], 0, 1, 2, depth)) )
return;
}
}
}
}
#endif
int hrange = depth == CV_32F ? 360 : isFullRange ? 255 : 180;
int blueIdx = swapBlue ? 2 : 0;
if(isHSV)
@ -1411,155 +1266,6 @@ void cvtHSVtoBGR(const uchar * src_data, size_t src_step,
}
}
} // namespace hal
//
// OCL calls
//
#ifdef HAVE_OPENCL
bool oclCvtColorHSV2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx, bool full )
{
OclHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_32F> > h(_src, _dst, dcn);
int hrange = _src.depth() == CV_32F ? 360 : (!full ? 180 : 255);
if(!h.createKernel("HSV2RGB", ocl::imgproc::color_hsv_oclsrc,
format("-D dcn=%d -D bidx=%d -D hrange=%d -D hscale=%ff", dcn, bidx, hrange, 6.f/hrange)))
{
return false;
}
return h.run();
}
bool oclCvtColorHLS2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx, bool full )
{
OclHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_32F> > h(_src, _dst, dcn);
int hrange = _src.depth() == CV_32F ? 360 : (!full ? 180 : 255);
if(!h.createKernel("HLS2RGB", ocl::imgproc::color_hsv_oclsrc,
format("-D dcn=%d -D bidx=%d -D hrange=%d -D hscale=%ff", dcn, bidx, hrange, 6.f/hrange)))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR2HLS( InputArray _src, OutputArray _dst, int bidx, bool full )
{
OclHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_32F> > h(_src, _dst, 3);
float hscale = (_src.depth() == CV_32F ? 360.f : (!full ? 180.f : 256.f))/360.f;
if(!h.createKernel("RGB2HLS", ocl::imgproc::color_hsv_oclsrc,
format("-D hscale=%ff -D bidx=%d -D dcn=3", hscale, bidx)))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR2HSV( InputArray _src, OutputArray _dst, int bidx, bool full )
{
OclHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_32F> > h(_src, _dst, 3);
int hrange = _src.depth() == CV_32F ? 360 : (!full ? 180 : 256);
cv::String options = (_src.depth() == CV_8U ?
format("-D hrange=%d -D bidx=%d -D dcn=3", hrange, bidx) :
format("-D hscale=%ff -D bidx=%d -D dcn=3", hrange*(1.f/360.f), bidx));
if(!h.createKernel("RGB2HSV", ocl::imgproc::color_hsv_oclsrc, options))
{
return false;
}
if(_src.depth() == CV_8U)
{
static UMat sdiv_data;
static UMat hdiv_data180;
static UMat hdiv_data256;
static int sdiv_table[256];
static int hdiv_table180[256];
static int hdiv_table256[256];
static volatile bool initialized180 = false, initialized256 = false;
volatile bool & initialized = hrange == 180 ? initialized180 : initialized256;
if (!initialized)
{
int * const hdiv_table = hrange == 180 ? hdiv_table180 : hdiv_table256, hsv_shift = 12;
UMat & hdiv_data = hrange == 180 ? hdiv_data180 : hdiv_data256;
sdiv_table[0] = hdiv_table180[0] = hdiv_table256[0] = 0;
int v = 255 << hsv_shift;
if (!initialized180 && !initialized256)
{
for(int i = 1; i < 256; i++ )
sdiv_table[i] = saturate_cast<int>(v/(1.*i));
Mat(1, 256, CV_32SC1, sdiv_table).copyTo(sdiv_data);
}
v = hrange << hsv_shift;
for (int i = 1; i < 256; i++ )
hdiv_table[i] = saturate_cast<int>(v/(6.*i));
Mat(1, 256, CV_32SC1, hdiv_table).copyTo(hdiv_data);
initialized = true;
}
h.setArg(ocl::KernelArg::PtrReadOnly(sdiv_data));
h.setArg(hrange == 256 ? ocl::KernelArg::PtrReadOnly(hdiv_data256) :
ocl::KernelArg::PtrReadOnly(hdiv_data180));
}
return h.run();
}
#endif
//
// HAL calls
//
void cvtColorBGR2HLS( InputArray _src, OutputArray _dst, bool swapb, bool fullRange )
{
CvtHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_32F> > h(_src, _dst, 3);
hal::cvtBGRtoHSV(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, h.scn, swapb, fullRange, false);
}
void cvtColorBGR2HSV( InputArray _src, OutputArray _dst, bool swapb, bool fullRange )
{
CvtHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_32F> > h(_src, _dst, 3);
hal::cvtBGRtoHSV(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, h.scn, swapb, fullRange, true);
}
void cvtColorHLS2BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb, bool fullRange)
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_32F> > h(_src, _dst, dcn);
hal::cvtHSVtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, dcn, swapb, fullRange, false);
}
void cvtColorHSV2BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb, bool fullRange)
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_32F> > h(_src, _dst, dcn);
hal::cvtHSVtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, dcn, swapb, fullRange, true);
}
} // namespace cv
CV_CPU_OPTIMIZATION_NAMESPACE_END
}} // namespace

4
modules/imgproc/src/color_lab.cpp
View File

@ -9,6 +9,10 @@
\**********************************************************************************/
#include "precomp.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "opencv2/core/hal/intrin.hpp"
#include "opencv2/core/softfloat.hpp"
#include "color.hpp"
using cv::softfloat;

619
modules/imgproc/src/color_rgb.dispatch.cpp Normal file
View File

@ -0,0 +1,619 @@
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#include "precomp.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "color.hpp"
#include "color_rgb.simd.hpp"
#include "color_rgb.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
#define IPP_DISABLE_CVTCOLOR_GRAY2BGR_8UC3 1
namespace cv {
//
// IPP functions
//
#if NEED_IPP
static const ippiColor2GrayFunc ippiColor2GrayC3Tab[] =
{
(ippiColor2GrayFunc)ippiColorToGray_8u_C3C1R, 0, (ippiColor2GrayFunc)ippiColorToGray_16u_C3C1R, 0,
0, (ippiColor2GrayFunc)ippiColorToGray_32f_C3C1R, 0, 0
};
static const ippiColor2GrayFunc ippiColor2GrayC4Tab[] =
{
(ippiColor2GrayFunc)ippiColorToGray_8u_AC4C1R, 0, (ippiColor2GrayFunc)ippiColorToGray_16u_AC4C1R, 0,
0, (ippiColor2GrayFunc)ippiColorToGray_32f_AC4C1R, 0, 0
};
static const ippiGeneralFunc ippiRGB2GrayC3Tab[] =
{
(ippiGeneralFunc)ippiRGBToGray_8u_C3C1R, 0, (ippiGeneralFunc)ippiRGBToGray_16u_C3C1R, 0,
0, (ippiGeneralFunc)ippiRGBToGray_32f_C3C1R, 0, 0
};
static const ippiGeneralFunc ippiRGB2GrayC4Tab[] =
{
(ippiGeneralFunc)ippiRGBToGray_8u_AC4C1R, 0, (ippiGeneralFunc)ippiRGBToGray_16u_AC4C1R, 0,
0, (ippiGeneralFunc)ippiRGBToGray_32f_AC4C1R, 0, 0
};
#if !IPP_DISABLE_CVTCOLOR_GRAY2BGR_8UC3
static IppStatus ippiGrayToRGB_C1C3R(const Ipp8u* pSrc, int srcStep, Ipp8u* pDst, int dstStep, IppiSize roiSize)
{
return CV_INSTRUMENT_FUN_IPP(ippiGrayToRGB_8u_C1C3R, pSrc, srcStep, pDst, dstStep, roiSize);
}
#endif
static IppStatus ippiGrayToRGB_C1C3R(const Ipp16u* pSrc, int srcStep, Ipp16u* pDst, int dstStep, IppiSize roiSize)
{
return CV_INSTRUMENT_FUN_IPP(ippiGrayToRGB_16u_C1C3R, pSrc, srcStep, pDst, dstStep, roiSize);
}
static IppStatus ippiGrayToRGB_C1C3R(const Ipp32f* pSrc, int srcStep, Ipp32f* pDst, int dstStep, IppiSize roiSize)
{
return CV_INSTRUMENT_FUN_IPP(ippiGrayToRGB_32f_C1C3R, pSrc, srcStep, pDst, dstStep, roiSize);
}
static IppStatus ippiGrayToRGB_C1C4R(const Ipp8u* pSrc, int srcStep, Ipp8u* pDst, int dstStep, IppiSize roiSize, Ipp8u aval)
{
return CV_INSTRUMENT_FUN_IPP(ippiGrayToRGB_8u_C1C4R, pSrc, srcStep, pDst, dstStep, roiSize, aval);
}
static IppStatus ippiGrayToRGB_C1C4R(const Ipp16u* pSrc, int srcStep, Ipp16u* pDst, int dstStep, IppiSize roiSize, Ipp16u aval)
{
return CV_INSTRUMENT_FUN_IPP(ippiGrayToRGB_16u_C1C4R, pSrc, srcStep, pDst, dstStep, roiSize, aval);
}
static IppStatus ippiGrayToRGB_C1C4R(const Ipp32f* pSrc, int srcStep, Ipp32f* pDst, int dstStep, IppiSize roiSize, Ipp32f aval)
{
return CV_INSTRUMENT_FUN_IPP(ippiGrayToRGB_32f_C1C4R, pSrc, srcStep, pDst, dstStep, roiSize, aval);
}
struct IPPColor2GrayFunctor
{
IPPColor2GrayFunctor(ippiColor2GrayFunc _func) :
ippiColorToGray(_func)
{
coeffs[0] = B2YF;
coeffs[1] = G2YF;
coeffs[2] = R2YF;
}
bool operator()(const void *src, int srcStep, void *dst, int dstStep, int cols, int rows) const
{
return ippiColorToGray ? CV_INSTRUMENT_FUN_IPP(ippiColorToGray, src, srcStep, dst, dstStep, ippiSize(cols, rows), coeffs) >= 0 : false;
}
private:
ippiColor2GrayFunc ippiColorToGray;
Ipp32f coeffs[3];
};
template <typename T>
struct IPPGray2BGRFunctor
{
IPPGray2BGRFunctor(){}
bool operator()(const void *src, int srcStep, void *dst, int dstStep, int cols, int rows) const
{
return ippiGrayToRGB_C1C3R((T*)src, srcStep, (T*)dst, dstStep, ippiSize(cols, rows)) >= 0;
}
};
template <typename T>
struct IPPGray2BGRAFunctor
{
IPPGray2BGRAFunctor()
{
alpha = ColorChannel<T>::max();
}
bool operator()(const void *src, int srcStep, void *dst, int dstStep, int cols, int rows) const
{
return ippiGrayToRGB_C1C4R((T*)src, srcStep, (T*)dst, dstStep, ippiSize(cols, rows), alpha) >= 0;
}
T alpha;
};
static IppStatus CV_STDCALL ippiSwapChannels_8u_C3C4Rf(const Ipp8u* pSrc, int srcStep, Ipp8u* pDst, int dstStep,
IppiSize roiSize, const int *dstOrder)
{
return CV_INSTRUMENT_FUN_IPP(ippiSwapChannels_8u_C3C4R, pSrc, srcStep, pDst, dstStep, roiSize, dstOrder, MAX_IPP8u);
}
static IppStatus CV_STDCALL ippiSwapChannels_16u_C3C4Rf(const Ipp16u* pSrc, int srcStep, Ipp16u* pDst, int dstStep,
IppiSize roiSize, const int *dstOrder)
{
return CV_INSTRUMENT_FUN_IPP(ippiSwapChannels_16u_C3C4R, pSrc, srcStep, pDst, dstStep, roiSize, dstOrder, MAX_IPP16u);
}
static IppStatus CV_STDCALL ippiSwapChannels_32f_C3C4Rf(const Ipp32f* pSrc, int srcStep, Ipp32f* pDst, int dstStep,
IppiSize roiSize, const int *dstOrder)
{
return CV_INSTRUMENT_FUN_IPP(ippiSwapChannels_32f_C3C4R, pSrc, srcStep, pDst, dstStep, roiSize, dstOrder, MAX_IPP32f);
}
// shared
ippiReorderFunc ippiSwapChannelsC3C4RTab[] =
{
(ippiReorderFunc)ippiSwapChannels_8u_C3C4Rf, 0, (ippiReorderFunc)ippiSwapChannels_16u_C3C4Rf, 0,
0, (ippiReorderFunc)ippiSwapChannels_32f_C3C4Rf, 0, 0
};
static ippiGeneralFunc ippiCopyAC4C3RTab[] =
{
(ippiGeneralFunc)ippiCopy_8u_AC4C3R, 0, (ippiGeneralFunc)ippiCopy_16u_AC4C3R, 0,
0, (ippiGeneralFunc)ippiCopy_32f_AC4C3R, 0, 0
};
// shared
ippiReorderFunc ippiSwapChannelsC4C3RTab[] =
{
(ippiReorderFunc)ippiSwapChannels_8u_C4C3R, 0, (ippiReorderFunc)ippiSwapChannels_16u_C4C3R, 0,
0, (ippiReorderFunc)ippiSwapChannels_32f_C4C3R, 0, 0
};
// shared
ippiReorderFunc ippiSwapChannelsC3RTab[] =
{
(ippiReorderFunc)ippiSwapChannels_8u_C3R, 0, (ippiReorderFunc)ippiSwapChannels_16u_C3R, 0,
0, (ippiReorderFunc)ippiSwapChannels_32f_C3R, 0, 0
};
#if IPP_VERSION_X100 >= 810
static ippiReorderFunc ippiSwapChannelsC4RTab[] =
{
(ippiReorderFunc)ippiSwapChannels_8u_C4R, 0, (ippiReorderFunc)ippiSwapChannels_16u_C4R, 0,
0, (ippiReorderFunc)ippiSwapChannels_32f_C4R, 0, 0
};
#endif
#endif
//
// HAL functions
//
namespace hal {
// 8u, 16u, 32f
void cvtBGRtoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int scn, int dcn, bool swapBlue)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGRtoBGR, cv_hal_cvtBGRtoBGR, src_data, src_step, dst_data, dst_step, width, height, depth, scn, dcn, swapBlue);
#if defined(HAVE_IPP) && IPP_VERSION_X100 >= 700
CV_IPP_CHECK()
{
if(scn == 3 && dcn == 4 && !swapBlue)
{
if ( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderFunctor(ippiSwapChannelsC3C4RTab[depth], 0, 1, 2)) )
return;
}
else if(scn == 4 && dcn == 3 && !swapBlue)
{
if ( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralFunctor(ippiCopyAC4C3RTab[depth])) )
return;
}
else if(scn == 3 && dcn == 4 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderFunctor(ippiSwapChannelsC3C4RTab[depth], 2, 1, 0)) )
return;
}
else if(scn == 4 && dcn == 3 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderFunctor(ippiSwapChannelsC4C3RTab[depth], 2, 1, 0)) )
return;
}
else if(scn == 3 && dcn == 3 && swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKETYPE(depth, scn), dst_data, dst_step, width, height,
IPPReorderFunctor(ippiSwapChannelsC3RTab[depth], 2, 1, 0)) )
return;
}
#if IPP_VERSION_X100 >= 810
else if(scn == 4 && dcn == 4 && swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKETYPE(depth, scn), dst_data, dst_step, width, height,
IPPReorderFunctor(ippiSwapChannelsC4RTab[depth], 2, 1, 0)) )
return;
}
}
#endif
#endif
CV_CPU_DISPATCH(cvtBGRtoBGR, (src_data, src_step, dst_data, dst_step, width, height, depth, scn, dcn, swapBlue),
CV_CPU_DISPATCH_MODES_ALL);
}
// only 8u
void cvtBGRtoBGR5x5(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int scn, bool swapBlue, int greenBits)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGRtoBGR5x5, cv_hal_cvtBGRtoBGR5x5, src_data, src_step, dst_data, dst_step, width, height, scn, swapBlue, greenBits);
CV_CPU_DISPATCH(cvtBGRtoBGR5x5, (src_data, src_step, dst_data, dst_step, width, height, scn, swapBlue, greenBits),
CV_CPU_DISPATCH_MODES_ALL);
}
// only 8u
void cvtBGR5x5toBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int dcn, bool swapBlue, int greenBits)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGR5x5toBGR, cv_hal_cvtBGR5x5toBGR, src_data, src_step, dst_data, dst_step, width, height, dcn, swapBlue, greenBits);
CV_CPU_DISPATCH(cvtBGR5x5toBGR, (src_data, src_step, dst_data, dst_step, width, height, dcn, swapBlue, greenBits),
CV_CPU_DISPATCH_MODES_ALL);
}
// 8u, 16u, 32f
void cvtBGRtoGray(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int scn, bool swapBlue)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGRtoGray, cv_hal_cvtBGRtoGray, src_data, src_step, dst_data, dst_step, width, height, depth, scn, swapBlue);
#if defined(HAVE_IPP) && IPP_VERSION_X100 >= 700
CV_IPP_CHECK()
{
if(depth == CV_32F && scn == 3 && !swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPColor2GrayFunctor(ippiColor2GrayC3Tab[depth])) )
return;
}
else if(depth == CV_32F && scn == 3 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralFunctor(ippiRGB2GrayC3Tab[depth])) )
return;
}
else if(depth == CV_32F && scn == 4 && !swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPColor2GrayFunctor(ippiColor2GrayC4Tab[depth])) )
return;
}
else if(depth == CV_32F && scn == 4 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralFunctor(ippiRGB2GrayC4Tab[depth])) )
return;
}
}
#endif
CV_CPU_DISPATCH(cvtBGRtoGray, (src_data, src_step, dst_data, dst_step, width, height, depth, scn, swapBlue),
CV_CPU_DISPATCH_MODES_ALL);
}
// 8u, 16u, 32f
void cvtGraytoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int dcn)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtGraytoBGR, cv_hal_cvtGraytoBGR, src_data, src_step, dst_data, dst_step, width, height, depth, dcn);
#if defined(HAVE_IPP) && IPP_VERSION_X100 >= 700
CV_IPP_CHECK()
{
bool ippres = false;
if(dcn == 3)
{
if( depth == CV_8U )
{
#if !IPP_DISABLE_CVTCOLOR_GRAY2BGR_8UC3
ippres = CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height, IPPGray2BGRFunctor<Ipp8u>());
#endif
}
else if( depth == CV_16U )
ippres = CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height, IPPGray2BGRFunctor<Ipp16u>());
else
ippres = CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height, IPPGray2BGRFunctor<Ipp32f>());
}
else if(dcn == 4)
{
if( depth == CV_8U )
ippres = CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height, IPPGray2BGRAFunctor<Ipp8u>());
else if( depth == CV_16U )
ippres = CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height, IPPGray2BGRAFunctor<Ipp16u>());
else
ippres = CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height, IPPGray2BGRAFunctor<Ipp32f>());
}
if(ippres)
return;
}
#endif
CV_CPU_DISPATCH(cvtGraytoBGR, (src_data, src_step, dst_data, dst_step, width, height, depth, dcn),
CV_CPU_DISPATCH_MODES_ALL);
}
// only 8u
void cvtBGR5x5toGray(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int greenBits)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGR5x5toGray, cv_hal_cvtBGR5x5toGray, src_data, src_step, dst_data, dst_step, width, height, greenBits);
CV_CPU_DISPATCH(cvtBGR5x5toGray, (src_data, src_step, dst_data, dst_step, width, height, greenBits),
CV_CPU_DISPATCH_MODES_ALL);
}
// only 8u
void cvtGraytoBGR5x5(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int greenBits)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtGraytoBGR5x5, cv_hal_cvtGraytoBGR5x5, src_data, src_step, dst_data, dst_step, width, height, greenBits);
CV_CPU_DISPATCH(cvtGraytoBGR5x5, (src_data, src_step, dst_data, dst_step, width, height, greenBits),
CV_CPU_DISPATCH_MODES_ALL);
}
void cvtRGBAtoMultipliedRGBA(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtRGBAtoMultipliedRGBA, cv_hal_cvtRGBAtoMultipliedRGBA, src_data, src_step, dst_data, dst_step, width, height);
#ifdef HAVE_IPP
CV_IPP_CHECK()
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralFunctor((ippiGeneralFunc)ippiAlphaPremul_8u_AC4R)))
return;
}
#endif
CV_CPU_DISPATCH(cvtRGBAtoMultipliedRGBA, (src_data, src_step, dst_data, dst_step, width, height),
CV_CPU_DISPATCH_MODES_ALL);
}
void cvtMultipliedRGBAtoRGBA(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtMultipliedRGBAtoRGBA, cv_hal_cvtMultipliedRGBAtoRGBA, src_data, src_step, dst_data, dst_step, width, height);
CV_CPU_DISPATCH(cvtMultipliedRGBAtoRGBA, (src_data, src_step, dst_data, dst_step, width, height),
CV_CPU_DISPATCH_MODES_ALL);
}
} // namespace hal
//
// OCL calls
//
#ifdef HAVE_OPENCL
bool oclCvtColorBGR2BGR( InputArray _src, OutputArray _dst, int dcn, bool reverse )
{
OclHelper< Set<3, 4>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
if(!h.createKernel("RGB", ocl::imgproc::color_rgb_oclsrc,
format("-D dcn=%d -D bidx=0 -D %s", dcn, reverse ? "REVERSE" : "ORDER")))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR25x5( InputArray _src, OutputArray _dst, int bidx, int gbits )
{
OclHelper< Set<3, 4>, Set<2>, Set<CV_8U> > h(_src, _dst, 2);
if(!h.createKernel("RGB2RGB5x5", ocl::imgproc::color_rgb_oclsrc,
format("-D dcn=2 -D bidx=%d -D greenbits=%d", bidx, gbits)))
{
return false;
}
return h.run();
}
bool oclCvtColor5x52BGR( InputArray _src, OutputArray _dst, int dcn, int bidx, int gbits)
{
OclHelper< Set<2>, Set<3, 4>, Set<CV_8U> > h(_src, _dst, dcn);
if(!h.createKernel("RGB5x52RGB", ocl::imgproc::color_rgb_oclsrc,
format("-D dcn=%d -D bidx=%d -D greenbits=%d", dcn, bidx, gbits)))
{
return false;
}
return h.run();
}
bool oclCvtColor5x52Gray( InputArray _src, OutputArray _dst, int gbits)
{
OclHelper< Set<2>, Set<1>, Set<CV_8U> > h(_src, _dst, 1);
if(!h.createKernel("BGR5x52Gray", ocl::imgproc::color_rgb_oclsrc,
format("-D dcn=1 -D bidx=0 -D greenbits=%d", gbits)))
{
return false;
}
return h.run();
}
bool oclCvtColorGray25x5( InputArray _src, OutputArray _dst, int gbits)
{
OclHelper< Set<1>, Set<2>, Set<CV_8U> > h(_src, _dst, 2);
if(!h.createKernel("Gray2BGR5x5", ocl::imgproc::color_rgb_oclsrc,
format("-D dcn=2 -D bidx=0 -D greenbits=%d", gbits)))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR2Gray( InputArray _src, OutputArray _dst, int bidx)
{
OclHelper< Set<3, 4>, Set<1>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, 1);
int stripeSize = 1;
if(!h.createKernel("RGB2Gray", ocl::imgproc::color_rgb_oclsrc,
format("-D dcn=1 -D bidx=%d -D STRIPE_SIZE=%d", bidx, stripeSize)))
{
return false;
}
h.globalSize[0] = (h.src.cols + stripeSize - 1)/stripeSize;
return h.run();
}
bool oclCvtColorGray2BGR( InputArray _src, OutputArray _dst, int dcn)
{
OclHelper< Set<1>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
if(!h.createKernel("Gray2RGB", ocl::imgproc::color_rgb_oclsrc,
format("-D bidx=0 -D dcn=%d", dcn)))
{
return false;
}
return h.run();
}
bool oclCvtColorRGBA2mRGBA( InputArray _src, OutputArray _dst)
{
OclHelper< Set<4>, Set<4>, Set<CV_8U> > h(_src, _dst, 4);
if(!h.createKernel("RGBA2mRGBA", ocl::imgproc::color_rgb_oclsrc,
"-D dcn=4 -D bidx=3"))
{
return false;
}
return h.run();
}
bool oclCvtColormRGBA2RGBA( InputArray _src, OutputArray _dst)
{
OclHelper< Set<4>, Set<4>, Set<CV_8U> > h(_src, _dst, 4);
if(!h.createKernel("mRGBA2RGBA", ocl::imgproc::color_rgb_oclsrc,
"-D dcn=4 -D bidx=3"))
{
return false;
}
return h.run();
}
#endif
//
// HAL calls
//
void cvtColorBGR2BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb)
{
CvtHelper< Set<3, 4>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
hal::cvtBGRtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, h.scn, dcn, swapb);
}
void cvtColorBGR25x5( InputArray _src, OutputArray _dst, bool swapb, int gbits)
{
CvtHelper< Set<3, 4>, Set<2>, Set<CV_8U> > h(_src, _dst, 2);
hal::cvtBGRtoBGR5x5(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.scn, swapb, gbits);
}
void cvtColor5x52BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb, int gbits)
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<2>, Set<3, 4>, Set<CV_8U> > h(_src, _dst, dcn);
hal::cvtBGR5x5toBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
dcn, swapb, gbits);
}
void cvtColorBGR2Gray( InputArray _src, OutputArray _dst, bool swapb)
{
CvtHelper< Set<3, 4>, Set<1>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, 1);
hal::cvtBGRtoGray(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, h.scn, swapb);
}
void cvtColorGray2BGR( InputArray _src, OutputArray _dst, int dcn)
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<1>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
hal::cvtGraytoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows, h.depth, dcn);
}
void cvtColor5x52Gray( InputArray _src, OutputArray _dst, int gbits)
{
CvtHelper< Set<2>, Set<1>, Set<CV_8U> > h(_src, _dst, 1);
hal::cvtBGR5x5toGray(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows, gbits);
}
void cvtColorGray25x5( InputArray _src, OutputArray _dst, int gbits)
{
CvtHelper< Set<1>, Set<2>, Set<CV_8U> > h(_src, _dst, 2);
hal::cvtGraytoBGR5x5(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows, gbits);
}
void cvtColorRGBA2mRGBA( InputArray _src, OutputArray _dst)
{
CvtHelper< Set<4>, Set<4>, Set<CV_8U> > h(_src, _dst, 4);
hal::cvtRGBAtoMultipliedRGBA(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows);
}
void cvtColormRGBA2RGBA( InputArray _src, OutputArray _dst)
{
CvtHelper< Set<4>, Set<4>, Set<CV_8U> > h(_src, _dst, 4);
hal::cvtMultipliedRGBAtoRGBA(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows);
}
} // namespace cv

552
modules/imgproc/src/color_rgb.cpp → modules/imgproc/src/color_rgb.simd.hpp
View File

@ -3,13 +3,58 @@
// of this distribution and at http://opencv.org/license.html
#include "precomp.hpp"
#include "color.hpp"
#include "opencv2/core/hal/intrin.hpp"
#define IPP_DISABLE_CVTCOLOR_GRAY2BGR_8UC3 1
namespace cv {
namespace hal {
CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
// forward declarations
namespace cv
{
void cvtBGRtoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int scn, int dcn, bool swapBlue);
void cvtBGRtoBGR5x5(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int scn, bool swapBlue, int greenBits);
void cvtBGR5x5toBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int dcn, bool swapBlue, int greenBits);
void cvtBGRtoGray(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int scn, bool swapBlue);
void cvtGraytoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int dcn);
void cvtBGR5x5toGray(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int greenBits);
void cvtGraytoBGR5x5(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int greenBits);
void cvtRGBAtoMultipliedRGBA(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height);
void cvtMultipliedRGBAtoRGBA(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height);
#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
#if defined(CV_CPU_BASELINE_MODE)
// included in color.hpp
#else
#include "color.simd_helpers.hpp"
#endif
namespace {
////////////////// Various 3/4-channel to 3/4-channel RGB transformations /////////////////
template<typename _Tp> struct v_type;
@ -1041,172 +1086,7 @@ struct mRGBA2RGBA<uchar>
}
}
};
//
// IPP functions
//
#if NEED_IPP
static ippiColor2GrayFunc ippiColor2GrayC3Tab[] =
{
(ippiColor2GrayFunc)ippiColorToGray_8u_C3C1R, 0, (ippiColor2GrayFunc)ippiColorToGray_16u_C3C1R, 0,
0, (ippiColor2GrayFunc)ippiColorToGray_32f_C3C1R, 0, 0
};
static ippiColor2GrayFunc ippiColor2GrayC4Tab[] =
{
(ippiColor2GrayFunc)ippiColorToGray_8u_AC4C1R, 0, (ippiColor2GrayFunc)ippiColorToGray_16u_AC4C1R, 0,
0, (ippiColor2GrayFunc)ippiColorToGray_32f_AC4C1R, 0, 0
};
static ippiGeneralFunc ippiRGB2GrayC3Tab[] =
{
(ippiGeneralFunc)ippiRGBToGray_8u_C3C1R, 0, (ippiGeneralFunc)ippiRGBToGray_16u_C3C1R, 0,
0, (ippiGeneralFunc)ippiRGBToGray_32f_C3C1R, 0, 0
};
static ippiGeneralFunc ippiRGB2GrayC4Tab[] =
{
(ippiGeneralFunc)ippiRGBToGray_8u_AC4C1R, 0, (ippiGeneralFunc)ippiRGBToGray_16u_AC4C1R, 0,
0, (ippiGeneralFunc)ippiRGBToGray_32f_AC4C1R, 0, 0
};
#if !IPP_DISABLE_CVTCOLOR_GRAY2BGR_8UC3
static IppStatus ippiGrayToRGB_C1C3R(const Ipp8u* pSrc, int srcStep, Ipp8u* pDst, int dstStep, IppiSize roiSize)
{
return CV_INSTRUMENT_FUN_IPP(ippiGrayToRGB_8u_C1C3R, pSrc, srcStep, pDst, dstStep, roiSize);
}
#endif
static IppStatus ippiGrayToRGB_C1C3R(const Ipp16u* pSrc, int srcStep, Ipp16u* pDst, int dstStep, IppiSize roiSize)
{
return CV_INSTRUMENT_FUN_IPP(ippiGrayToRGB_16u_C1C3R, pSrc, srcStep, pDst, dstStep, roiSize);
}
static IppStatus ippiGrayToRGB_C1C3R(const Ipp32f* pSrc, int srcStep, Ipp32f* pDst, int dstStep, IppiSize roiSize)
{
return CV_INSTRUMENT_FUN_IPP(ippiGrayToRGB_32f_C1C3R, pSrc, srcStep, pDst, dstStep, roiSize);
}
static IppStatus ippiGrayToRGB_C1C4R(const Ipp8u* pSrc, int srcStep, Ipp8u* pDst, int dstStep, IppiSize roiSize, Ipp8u aval)
{
return CV_INSTRUMENT_FUN_IPP(ippiGrayToRGB_8u_C1C4R, pSrc, srcStep, pDst, dstStep, roiSize, aval);
}
static IppStatus ippiGrayToRGB_C1C4R(const Ipp16u* pSrc, int srcStep, Ipp16u* pDst, int dstStep, IppiSize roiSize, Ipp16u aval)
{
return CV_INSTRUMENT_FUN_IPP(ippiGrayToRGB_16u_C1C4R, pSrc, srcStep, pDst, dstStep, roiSize, aval);
}
static IppStatus ippiGrayToRGB_C1C4R(const Ipp32f* pSrc, int srcStep, Ipp32f* pDst, int dstStep, IppiSize roiSize, Ipp32f aval)
{
return CV_INSTRUMENT_FUN_IPP(ippiGrayToRGB_32f_C1C4R, pSrc, srcStep, pDst, dstStep, roiSize, aval);
}
struct IPPColor2GrayFunctor
{
IPPColor2GrayFunctor(ippiColor2GrayFunc _func) :
ippiColorToGray(_func)
{
coeffs[0] = B2YF;
coeffs[1] = G2YF;
coeffs[2] = R2YF;
}
bool operator()(const void *src, int srcStep, void *dst, int dstStep, int cols, int rows) const
{
return ippiColorToGray ? CV_INSTRUMENT_FUN_IPP(ippiColorToGray, src, srcStep, dst, dstStep, ippiSize(cols, rows), coeffs) >= 0 : false;
}
private:
ippiColor2GrayFunc ippiColorToGray;
Ipp32f coeffs[3];
};
template <typename T>
struct IPPGray2BGRFunctor
{
IPPGray2BGRFunctor(){}
bool operator()(const void *src, int srcStep, void *dst, int dstStep, int cols, int rows) const
{
return ippiGrayToRGB_C1C3R((T*)src, srcStep, (T*)dst, dstStep, ippiSize(cols, rows)) >= 0;
}
};
template <typename T>
struct IPPGray2BGRAFunctor
{
IPPGray2BGRAFunctor()
{
alpha = ColorChannel<T>::max();
}
bool operator()(const void *src, int srcStep, void *dst, int dstStep, int cols, int rows) const
{
return ippiGrayToRGB_C1C4R((T*)src, srcStep, (T*)dst, dstStep, ippiSize(cols, rows), alpha) >= 0;
}
T alpha;
};
static IppStatus CV_STDCALL ippiSwapChannels_8u_C3C4Rf(const Ipp8u* pSrc, int srcStep, Ipp8u* pDst, int dstStep,
IppiSize roiSize, const int *dstOrder)
{
return CV_INSTRUMENT_FUN_IPP(ippiSwapChannels_8u_C3C4R, pSrc, srcStep, pDst, dstStep, roiSize, dstOrder, MAX_IPP8u);
}
static IppStatus CV_STDCALL ippiSwapChannels_16u_C3C4Rf(const Ipp16u* pSrc, int srcStep, Ipp16u* pDst, int dstStep,
IppiSize roiSize, const int *dstOrder)
{
return CV_INSTRUMENT_FUN_IPP(ippiSwapChannels_16u_C3C4R, pSrc, srcStep, pDst, dstStep, roiSize, dstOrder, MAX_IPP16u);
}
static IppStatus CV_STDCALL ippiSwapChannels_32f_C3C4Rf(const Ipp32f* pSrc, int srcStep, Ipp32f* pDst, int dstStep,
IppiSize roiSize, const int *dstOrder)
{
return CV_INSTRUMENT_FUN_IPP(ippiSwapChannels_32f_C3C4R, pSrc, srcStep, pDst, dstStep, roiSize, dstOrder, MAX_IPP32f);
}
// shared
ippiReorderFunc ippiSwapChannelsC3C4RTab[] =
{
(ippiReorderFunc)ippiSwapChannels_8u_C3C4Rf, 0, (ippiReorderFunc)ippiSwapChannels_16u_C3C4Rf, 0,
0, (ippiReorderFunc)ippiSwapChannels_32f_C3C4Rf, 0, 0
};
static ippiGeneralFunc ippiCopyAC4C3RTab[] =
{
(ippiGeneralFunc)ippiCopy_8u_AC4C3R, 0, (ippiGeneralFunc)ippiCopy_16u_AC4C3R, 0,
0, (ippiGeneralFunc)ippiCopy_32f_AC4C3R, 0, 0
};
// shared
ippiReorderFunc ippiSwapChannelsC4C3RTab[] =
{
(ippiReorderFunc)ippiSwapChannels_8u_C4C3R, 0, (ippiReorderFunc)ippiSwapChannels_16u_C4C3R, 0,
0, (ippiReorderFunc)ippiSwapChannels_32f_C4C3R, 0, 0
};
// shared
ippiReorderFunc ippiSwapChannelsC3RTab[] =
{
(ippiReorderFunc)ippiSwapChannels_8u_C3R, 0, (ippiReorderFunc)ippiSwapChannels_16u_C3R, 0,
0, (ippiReorderFunc)ippiSwapChannels_32f_C3R, 0, 0
};
#if IPP_VERSION_X100 >= 810
static ippiReorderFunc ippiSwapChannelsC4RTab[] =
{
(ippiReorderFunc)ippiSwapChannels_8u_C4R, 0, (ippiReorderFunc)ippiSwapChannels_16u_C4R, 0,
0, (ippiReorderFunc)ippiSwapChannels_32f_C4R, 0, 0
};
#endif
#endif
//
// HAL functions
//
namespace hal
{
} // namespace anon
// 8u, 16u, 32f
void cvtBGRtoBGR(const uchar * src_data, size_t src_step,
@ -1216,52 +1096,6 @@ void cvtBGRtoBGR(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGRtoBGR, cv_hal_cvtBGRtoBGR, src_data, src_step, dst_data, dst_step, width, height, depth, scn, dcn, swapBlue);
#if defined(HAVE_IPP) && IPP_VERSION_X100 >= 700
CV_IPP_CHECK()
{
if(scn == 3 && dcn == 4 && !swapBlue)
{
if ( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderFunctor(ippiSwapChannelsC3C4RTab[depth], 0, 1, 2)) )
return;
}
else if(scn == 4 && dcn == 3 && !swapBlue)
{
if ( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralFunctor(ippiCopyAC4C3RTab[depth])) )
return;
}
else if(scn == 3 && dcn == 4 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderFunctor(ippiSwapChannelsC3C4RTab[depth], 2, 1, 0)) )
return;
}
else if(scn == 4 && dcn == 3 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderFunctor(ippiSwapChannelsC4C3RTab[depth], 2, 1, 0)) )
return;
}
else if(scn == 3 && dcn == 3 && swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKETYPE(depth, scn), dst_data, dst_step, width, height,
IPPReorderFunctor(ippiSwapChannelsC3RTab[depth], 2, 1, 0)) )
return;
}
#if IPP_VERSION_X100 >= 810
else if(scn == 4 && dcn == 4 && swapBlue)
{
if( CvtColorIPPLoopCopy(src_data, src_step, CV_MAKETYPE(depth, scn), dst_data, dst_step, width, height,
IPPReorderFunctor(ippiSwapChannelsC4RTab[depth], 2, 1, 0)) )
return;
}
}
#endif
#endif
int blueIdx = swapBlue ? 2 : 0;
if( depth == CV_8U )
CvtColorLoop(src_data, src_step, dst_data, dst_step, width, height, RGB2RGB<uchar>(scn, dcn, blueIdx));
@ -1279,8 +1113,6 @@ void cvtBGRtoBGR5x5(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGRtoBGR5x5, cv_hal_cvtBGRtoBGR5x5, src_data, src_step, dst_data, dst_step, width, height, scn, swapBlue, greenBits);
CvtColorLoop(src_data, src_step, dst_data, dst_step, width, height, RGB2RGB5x5(scn, swapBlue ? 2 : 0, greenBits));
}
@ -1292,8 +1124,6 @@ void cvtBGR5x5toBGR(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGR5x5toBGR, cv_hal_cvtBGR5x5toBGR, src_data, src_step, dst_data, dst_step, width, height, dcn, swapBlue, greenBits);
CvtColorLoop(src_data, src_step, dst_data, dst_step, width, height, RGB5x52RGB(dcn, swapBlue ? 2 : 0, greenBits));
}
@ -1305,38 +1135,6 @@ void cvtBGRtoGray(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGRtoGray, cv_hal_cvtBGRtoGray, src_data, src_step, dst_data, dst_step, width, height, depth, scn, swapBlue);
#if defined(HAVE_IPP) && IPP_VERSION_X100 >= 700
CV_IPP_CHECK()
{
if(depth == CV_32F && scn == 3 && !swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPColor2GrayFunctor(ippiColor2GrayC3Tab[depth])) )
return;
}
else if(depth == CV_32F && scn == 3 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralFunctor(ippiRGB2GrayC3Tab[depth])) )
return;
}
else if(depth == CV_32F && scn == 4 && !swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPColor2GrayFunctor(ippiColor2GrayC4Tab[depth])) )
return;
}
else if(depth == CV_32F && scn == 4 && swapBlue)
{
if( CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralFunctor(ippiRGB2GrayC4Tab[depth])) )
return;
}
}
#endif
int blueIdx = swapBlue ? 2 : 0;
if( depth == CV_8U )
CvtColorLoop(src_data, src_step, dst_data, dst_step, width, height, RGB2Gray<uchar>(scn, blueIdx, 0));
@ -1354,39 +1152,6 @@ void cvtGraytoBGR(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtGraytoBGR, cv_hal_cvtGraytoBGR, src_data, src_step, dst_data, dst_step, width, height, depth, dcn);
#if defined(HAVE_IPP) && IPP_VERSION_X100 >= 700
CV_IPP_CHECK()
{
bool ippres = false;
if(dcn == 3)
{
if( depth == CV_8U )
{
#if !IPP_DISABLE_CVTCOLOR_GRAY2BGR_8UC3
ippres = CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height, IPPGray2BGRFunctor<Ipp8u>());
#endif
}
else if( depth == CV_16U )
ippres = CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height, IPPGray2BGRFunctor<Ipp16u>());
else
ippres = CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height, IPPGray2BGRFunctor<Ipp32f>());
}
else if(dcn == 4)
{
if( depth == CV_8U )
ippres = CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height, IPPGray2BGRAFunctor<Ipp8u>());
else if( depth == CV_16U )
ippres = CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height, IPPGray2BGRAFunctor<Ipp16u>());
else
ippres = CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height, IPPGray2BGRAFunctor<Ipp32f>());
}
if(ippres)
return;
}
#endif
if( depth == CV_8U )
CvtColorLoop(src_data, src_step, dst_data, dst_step, width, height, Gray2RGB<uchar>(dcn));
else if( depth == CV_16U )
@ -1403,7 +1168,6 @@ void cvtBGR5x5toGray(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGR5x5toGray, cv_hal_cvtBGR5x5toGray, src_data, src_step, dst_data, dst_step, width, height, greenBits);
CvtColorLoop(src_data, src_step, dst_data, dst_step, width, height, RGB5x52Gray(greenBits));
}
@ -1415,7 +1179,6 @@ void cvtGraytoBGR5x5(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtGraytoBGR5x5, cv_hal_cvtGraytoBGR5x5, src_data, src_step, dst_data, dst_step, width, height, greenBits);
CvtColorLoop(src_data, src_step, dst_data, dst_step, width, height, Gray2RGB5x5(greenBits));
}
@ -1425,17 +1188,6 @@ void cvtRGBAtoMultipliedRGBA(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtRGBAtoMultipliedRGBA, cv_hal_cvtRGBAtoMultipliedRGBA, src_data, src_step, dst_data, dst_step, width, height);
#ifdef HAVE_IPP
CV_IPP_CHECK()
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralFunctor((ippiGeneralFunc)ippiAlphaPremul_8u_AC4R)))
return;
}
#endif
CvtColorLoop(src_data, src_step, dst_data, dst_step, width, height, RGBA2mRGBA<uchar>());
}
@ -1445,209 +1197,9 @@ void cvtMultipliedRGBAtoRGBA(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtMultipliedRGBAtoRGBA, cv_hal_cvtMultipliedRGBAtoRGBA, src_data, src_step, dst_data, dst_step, width, height);
CvtColorLoop(src_data, src_step, dst_data, dst_step, width, height, mRGBA2RGBA<uchar>());
}
} // namespace hal
//
// OCL calls
//
#ifdef HAVE_OPENCL
bool oclCvtColorBGR2BGR( InputArray _src, OutputArray _dst, int dcn, bool reverse )
{
OclHelper< Set<3, 4>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
if(!h.createKernel("RGB", ocl::imgproc::color_rgb_oclsrc,
format("-D dcn=%d -D bidx=0 -D %s", dcn, reverse ? "REVERSE" : "ORDER")))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR25x5( InputArray _src, OutputArray _dst, int bidx, int gbits )
{
OclHelper< Set<3, 4>, Set<2>, Set<CV_8U> > h(_src, _dst, 2);
if(!h.createKernel("RGB2RGB5x5", ocl::imgproc::color_rgb_oclsrc,
format("-D dcn=2 -D bidx=%d -D greenbits=%d", bidx, gbits)))
{
return false;
}
return h.run();
}
bool oclCvtColor5x52BGR( InputArray _src, OutputArray _dst, int dcn, int bidx, int gbits)
{
OclHelper< Set<2>, Set<3, 4>, Set<CV_8U> > h(_src, _dst, dcn);
if(!h.createKernel("RGB5x52RGB", ocl::imgproc::color_rgb_oclsrc,
format("-D dcn=%d -D bidx=%d -D greenbits=%d", dcn, bidx, gbits)))
{
return false;
}
return h.run();
}
bool oclCvtColor5x52Gray( InputArray _src, OutputArray _dst, int gbits)
{
OclHelper< Set<2>, Set<1>, Set<CV_8U> > h(_src, _dst, 1);
if(!h.createKernel("BGR5x52Gray", ocl::imgproc::color_rgb_oclsrc,
format("-D dcn=1 -D bidx=0 -D greenbits=%d", gbits)))
{
return false;
}
return h.run();
}
bool oclCvtColorGray25x5( InputArray _src, OutputArray _dst, int gbits)
{
OclHelper< Set<1>, Set<2>, Set<CV_8U> > h(_src, _dst, 2);
if(!h.createKernel("Gray2BGR5x5", ocl::imgproc::color_rgb_oclsrc,
format("-D dcn=2 -D bidx=0 -D greenbits=%d", gbits)))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR2Gray( InputArray _src, OutputArray _dst, int bidx)
{
OclHelper< Set<3, 4>, Set<1>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, 1);
int stripeSize = 1;
if(!h.createKernel("RGB2Gray", ocl::imgproc::color_rgb_oclsrc,
format("-D dcn=1 -D bidx=%d -D STRIPE_SIZE=%d", bidx, stripeSize)))
{
return false;
}
h.globalSize[0] = (h.src.cols + stripeSize - 1)/stripeSize;
return h.run();
}
bool oclCvtColorGray2BGR( InputArray _src, OutputArray _dst, int dcn)
{
OclHelper< Set<1>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
if(!h.createKernel("Gray2RGB", ocl::imgproc::color_rgb_oclsrc,
format("-D bidx=0 -D dcn=%d", dcn)))
{
return false;
}
return h.run();
}
bool oclCvtColorRGBA2mRGBA( InputArray _src, OutputArray _dst)
{
OclHelper< Set<4>, Set<4>, Set<CV_8U> > h(_src, _dst, 4);
if(!h.createKernel("RGBA2mRGBA", ocl::imgproc::color_rgb_oclsrc,
"-D dcn=4 -D bidx=3"))
{
return false;
}
return h.run();
}
bool oclCvtColormRGBA2RGBA( InputArray _src, OutputArray _dst)
{
OclHelper< Set<4>, Set<4>, Set<CV_8U> > h(_src, _dst, 4);
if(!h.createKernel("mRGBA2RGBA", ocl::imgproc::color_rgb_oclsrc,
"-D dcn=4 -D bidx=3"))
{
return false;
}
return h.run();
}
#endif
//
// HAL calls
//
void cvtColorBGR2BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb)
{
CvtHelper< Set<3, 4>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
hal::cvtBGRtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, h.scn, dcn, swapb);
}
void cvtColorBGR25x5( InputArray _src, OutputArray _dst, bool swapb, int gbits)
{
CvtHelper< Set<3, 4>, Set<2>, Set<CV_8U> > h(_src, _dst, 2);
hal::cvtBGRtoBGR5x5(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.scn, swapb, gbits);
}
void cvtColor5x52BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb, int gbits)
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<2>, Set<3, 4>, Set<CV_8U> > h(_src, _dst, dcn);
hal::cvtBGR5x5toBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
dcn, swapb, gbits);
}
void cvtColorBGR2Gray( InputArray _src, OutputArray _dst, bool swapb)
{
CvtHelper< Set<3, 4>, Set<1>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, 1);
hal::cvtBGRtoGray(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, h.scn, swapb);
}
void cvtColorGray2BGR( InputArray _src, OutputArray _dst, int dcn)
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<1>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
hal::cvtGraytoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows, h.depth, dcn);
}
void cvtColor5x52Gray( InputArray _src, OutputArray _dst, int gbits)
{
CvtHelper< Set<2>, Set<1>, Set<CV_8U> > h(_src, _dst, 1);
hal::cvtBGR5x5toGray(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows, gbits);
}
void cvtColorGray25x5( InputArray _src, OutputArray _dst, int gbits)
{
CvtHelper< Set<1>, Set<2>, Set<CV_8U> > h(_src, _dst, 2);
hal::cvtGraytoBGR5x5(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows, gbits);
}
void cvtColorRGBA2mRGBA( InputArray _src, OutputArray _dst)
{
CvtHelper< Set<4>, Set<4>, Set<CV_8U> > h(_src, _dst, 4);
hal::cvtRGBAtoMultipliedRGBA(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows);
}
void cvtColormRGBA2RGBA( InputArray _src, OutputArray _dst)
{
CvtHelper< Set<4>, Set<4>, Set<CV_8U> > h(_src, _dst, 4);
hal::cvtMultipliedRGBAtoRGBA(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows);
}
} // namespace cv
CV_CPU_OPTIMIZATION_NAMESPACE_END
}} // namespace

417
modules/imgproc/src/color_yuv.dispatch.cpp Normal file
View File

@ -0,0 +1,417 @@
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#include "precomp.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "color.hpp"
#include "color_yuv.simd.hpp"
#include "color_yuv.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
namespace cv {
//
// HAL functions
//
namespace hal {
// 8u, 16u, 32f
void cvtBGRtoYUV(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int scn, bool swapBlue, bool isCbCr)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGRtoYUV, cv_hal_cvtBGRtoYUV, src_data, src_step, dst_data, dst_step, width, height, depth, scn, swapBlue, isCbCr);
#if defined(HAVE_IPP)
#if !IPP_DISABLE_RGB_YUV
CV_IPP_CHECK()
{
if (scn == 3 && depth == CV_8U && swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralFunctor((ippiGeneralFunc)ippiRGBToYUV_8u_C3R)))
return;
}
else if (scn == 3 && depth == CV_8U && !swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC3RTab[depth],
(ippiGeneralFunc)ippiRGBToYUV_8u_C3R, 2, 1, 0, depth)))
return;
}
else if (scn == 4 && depth == CV_8U && swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC4C3RTab[depth],
(ippiGeneralFunc)ippiRGBToYUV_8u_C3R, 0, 1, 2, depth)))
return;
}
else if (scn == 4 && depth == CV_8U && !swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC4C3RTab[depth],
(ippiGeneralFunc)ippiRGBToYUV_8u_C3R, 2, 1, 0, depth)))
return;
}
}
#endif
#endif
CV_CPU_DISPATCH(cvtBGRtoYUV, (src_data, src_step, dst_data, dst_step, width, height, depth, scn, swapBlue, isCbCr),
CV_CPU_DISPATCH_MODES_ALL);
}
void cvtYUVtoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int dcn, bool swapBlue, bool isCbCr)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtYUVtoBGR, cv_hal_cvtYUVtoBGR, src_data, src_step, dst_data, dst_step, width, height, depth, dcn, swapBlue, isCbCr);
#if defined(HAVE_IPP)
#if !IPP_DISABLE_YUV_RGB
CV_IPP_CHECK()
{
if (dcn == 3 && depth == CV_8U && swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralFunctor((ippiGeneralFunc)ippiYUVToRGB_8u_C3R)))
return;
}
else if (dcn == 3 && depth == CV_8U && !swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor((ippiGeneralFunc)ippiYUVToRGB_8u_C3R,
ippiSwapChannelsC3RTab[depth], 2, 1, 0, depth)))
return;
}
else if (dcn == 4 && depth == CV_8U && swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor((ippiGeneralFunc)ippiYUVToRGB_8u_C3R,
ippiSwapChannelsC3C4RTab[depth], 0, 1, 2, depth)))
return;
}
else if (dcn == 4 && depth == CV_8U && !swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor((ippiGeneralFunc)ippiYUVToRGB_8u_C3R,
ippiSwapChannelsC3C4RTab[depth], 2, 1, 0, depth)))
return;
}
}
#endif
#endif
CV_CPU_DISPATCH(cvtYUVtoBGR, (src_data, src_step, dst_data, dst_step, width, height, depth, dcn, swapBlue, isCbCr),
CV_CPU_DISPATCH_MODES_ALL);
}
void cvtTwoPlaneYUVtoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int dst_width, int dst_height,
int dcn, bool swapBlue, int uIdx)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtTwoPlaneYUVtoBGR, cv_hal_cvtTwoPlaneYUVtoBGR, src_data, src_step, dst_data, dst_step, dst_width, dst_height, dcn, swapBlue, uIdx);
CV_CPU_DISPATCH(cvtTwoPlaneYUVtoBGR, (src_data, src_step, dst_data, dst_step, dst_width, dst_height, dcn, swapBlue, uIdx),
CV_CPU_DISPATCH_MODES_ALL);
}
void cvtTwoPlaneYUVtoBGR(const uchar * y_data, const uchar * uv_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int dst_width, int dst_height,
int dcn, bool swapBlue, int uIdx)
{
CV_INSTRUMENT_REGION();
CV_CPU_DISPATCH(cvtTwoPlaneYUVtoBGR, (y_data, uv_data, src_step, dst_data, dst_step, dst_width, dst_height, dcn, swapBlue, uIdx),
CV_CPU_DISPATCH_MODES_ALL);
}
void cvtThreePlaneYUVtoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int dst_width, int dst_height,
int dcn, bool swapBlue, int uIdx)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtThreePlaneYUVtoBGR, cv_hal_cvtThreePlaneYUVtoBGR, src_data, src_step, dst_data, dst_step, dst_width, dst_height, dcn, swapBlue, uIdx);
CV_CPU_DISPATCH(cvtThreePlaneYUVtoBGR, (src_data, src_step, dst_data, dst_step, dst_width, dst_height, dcn, swapBlue, uIdx),
CV_CPU_DISPATCH_MODES_ALL);
}
void cvtBGRtoThreePlaneYUV(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int scn, bool swapBlue, int uIdx)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGRtoThreePlaneYUV, cv_hal_cvtBGRtoThreePlaneYUV, src_data, src_step, dst_data, dst_step, width, height, scn, swapBlue, uIdx);
CV_CPU_DISPATCH(cvtBGRtoThreePlaneYUV, (src_data, src_step, dst_data, dst_step, width, height, scn, swapBlue, uIdx),
CV_CPU_DISPATCH_MODES_ALL);
}
void cvtBGRtoTwoPlaneYUV(const uchar * src_data, size_t src_step,
uchar * y_data, uchar * uv_data, size_t dst_step,
int width, int height,
int scn, bool swapBlue, int uIdx)
{
CV_INSTRUMENT_REGION();
// TODO: add hal replacement method
CV_CPU_DISPATCH(cvtBGRtoTwoPlaneYUV, (src_data, src_step, y_data, uv_data, dst_step, width, height, scn, swapBlue, uIdx),
CV_CPU_DISPATCH_MODES_ALL);
}
void cvtOnePlaneYUVtoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int dcn, bool swapBlue, int uIdx, int ycn)
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtOnePlaneYUVtoBGR, cv_hal_cvtOnePlaneYUVtoBGR, src_data, src_step, dst_data, dst_step, width, height, dcn, swapBlue, uIdx, ycn);
CV_CPU_DISPATCH(cvtOnePlaneYUVtoBGR, (src_data, src_step, dst_data, dst_step, width, height, dcn, swapBlue, uIdx, ycn),
CV_CPU_DISPATCH_MODES_ALL);
}
} // namespace hal
//
// OCL calls
//
#ifdef HAVE_OPENCL
bool oclCvtColorYUV2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx )
{
OclHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
if(!h.createKernel("YUV2RGB", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=%d -D bidx=%d", dcn, bidx)))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR2YUV( InputArray _src, OutputArray _dst, int bidx )
{
OclHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, 3);
if(!h.createKernel("RGB2YUV", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=3 -D bidx=%d", bidx)))
{
return false;
}
return h.run();
}
bool oclCvtcolorYCrCb2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx)
{
OclHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
if(!h.createKernel("YCrCb2RGB", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=%d -D bidx=%d", dcn, bidx)))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR2YCrCb( InputArray _src, OutputArray _dst, int bidx)
{
OclHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, 3);
if(!h.createKernel("RGB2YCrCb", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=3 -D bidx=%d", bidx)))
{
return false;
}
return h.run();
}
bool oclCvtColorOnePlaneYUV2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx, int uidx, int yidx )
{
OclHelper< Set<2>, Set<3, 4>, Set<CV_8U> > h(_src, _dst, dcn);
bool optimized = _src.offset() % 4 == 0 && _src.step() % 4 == 0;
if(!h.createKernel("YUV2RGB_422", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=%d -D bidx=%d -D uidx=%d -D yidx=%d%s", dcn, bidx, uidx, yidx,
optimized ? " -D USE_OPTIMIZED_LOAD" : "")))
{
return false;
}
return h.run();
}
bool oclCvtColorYUV2Gray_420( InputArray _src, OutputArray _dst )
{
OclHelper< Set<1>, Set<1>, Set<CV_8U>, FROM_YUV> h(_src, _dst, 1);
h.src.rowRange(0, _dst.rows()).copyTo(_dst);
return true;
}
bool oclCvtColorTwoPlaneYUV2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx, int uidx )
{
OclHelper< Set<1>, Set<3, 4>, Set<CV_8U>, FROM_YUV > h(_src, _dst, dcn);
if(!h.createKernel("YUV2RGB_NVx", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=%d -D bidx=%d -D uidx=%d", dcn, bidx, uidx)))
{
return false;
}
return h.run();
}
bool oclCvtColorThreePlaneYUV2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx, int uidx )
{
OclHelper< Set<1>, Set<3, 4>, Set<CV_8U>, FROM_YUV > h(_src, _dst, dcn);
if(!h.createKernel("YUV2RGB_YV12_IYUV", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=%d -D bidx=%d -D uidx=%d%s", dcn, bidx, uidx,
_src.isContinuous() ? " -D SRC_CONT" : "")))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR2ThreePlaneYUV( InputArray _src, OutputArray _dst, int bidx, int uidx )
{
OclHelper< Set<3, 4>, Set<1>, Set<CV_8U>, TO_YUV > h(_src, _dst, 1);
if(!h.createKernel("RGB2YUV_YV12_IYUV", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=1 -D bidx=%d -D uidx=%d", bidx, uidx)))
{
return false;
}
return h.run();
}
#endif
//
// HAL calls
//
void cvtColorBGR2YUV(InputArray _src, OutputArray _dst, bool swapb, bool crcb)
{
CvtHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, 3);
hal::cvtBGRtoYUV(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, h.scn, swapb, crcb);
}
void cvtColorYUV2BGR(InputArray _src, OutputArray _dst, int dcn, bool swapb, bool crcb)
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
hal::cvtYUVtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, dcn, swapb, crcb);
}
void cvtColorOnePlaneYUV2BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb, int uidx, int ycn)
{
CvtHelper< Set<2>, Set<3, 4>, Set<CV_8U> > h(_src, _dst, dcn);
hal::cvtOnePlaneYUVtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
dcn, swapb, uidx, ycn);
}
void cvtColorYUV2Gray_ch( InputArray _src, OutputArray _dst, int coi )
{
CV_Assert( _src.channels() == 2 && _src.depth() == CV_8U );
extractChannel(_src, _dst, coi);
}
void cvtColorBGR2ThreePlaneYUV( InputArray _src, OutputArray _dst, bool swapb, int uidx)
{
CvtHelper< Set<3, 4>, Set<1>, Set<CV_8U>, TO_YUV > h(_src, _dst, 1);
hal::cvtBGRtoThreePlaneYUV(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.scn, swapb, uidx);
}
void cvtColorYUV2Gray_420( InputArray _src, OutputArray _dst )
{
CvtHelper< Set<1>, Set<1>, Set<CV_8U>, FROM_YUV > h(_src, _dst, 1);
#ifdef HAVE_IPP
#if IPP_VERSION_X100 >= 201700
if (CV_INSTRUMENT_FUN_IPP(ippiCopy_8u_C1R_L, h.src.data, (IppSizeL)h.src.step, h.dst.data, (IppSizeL)h.dst.step,
ippiSizeL(h.dstSz.width, h.dstSz.height)) >= 0)
return;
#endif
#endif
h.src(Range(0, h.dstSz.height), Range::all()).copyTo(h.dst);
}
void cvtColorThreePlaneYUV2BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb, int uidx)
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<1>, Set<3, 4>, Set<CV_8U>, FROM_YUV> h(_src, _dst, dcn);
hal::cvtThreePlaneYUVtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.dst.cols, h.dst.rows,
dcn, swapb, uidx);
}
// http://www.fourcc.org/yuv.php#NV21 == yuv420sp -> a plane of 8 bit Y samples followed by an interleaved V/U plane containing 8 bit 2x2 subsampled chroma samples
// http://www.fourcc.org/yuv.php#NV12 -> a plane of 8 bit Y samples followed by an interleaved U/V plane containing 8 bit 2x2 subsampled colour difference samples
void cvtColorTwoPlaneYUV2BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb, int uidx )
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<1>, Set<3, 4>, Set<CV_8U>, FROM_YUV> h(_src, _dst, dcn);
hal::cvtTwoPlaneYUVtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.dst.cols, h.dst.rows,
dcn, swapb, uidx);
}
void cvtColorTwoPlaneYUV2BGRpair( InputArray _ysrc, InputArray _uvsrc, OutputArray _dst, int dcn, bool swapb, int uidx )
{
int stype = _ysrc.type();
int depth = CV_MAT_DEPTH(stype);
Size ysz = _ysrc.size(), uvs = _uvsrc.size();
CV_Assert( dcn == 3 || dcn == 4 );
CV_Assert( depth == CV_8U );
CV_Assert( ysz.width == uvs.width * 2 && ysz.height == uvs.height * 2 );
Mat ysrc = _ysrc.getMat(), uvsrc = _uvsrc.getMat();
_dst.create( ysz, CV_MAKETYPE(depth, dcn));
Mat dst = _dst.getMat();
hal::cvtTwoPlaneYUVtoBGR(ysrc.data, uvsrc.data, ysrc.step,
dst.data, dst.step, dst.cols, dst.rows,
dcn, swapb, uidx);
}
} // namespace cv

364
modules/imgproc/src/color_yuv.cpp → modules/imgproc/src/color_yuv.simd.hpp
View File

@ -3,11 +3,54 @@
// of this distribution and at http://opencv.org/license.html
#include "precomp.hpp"
#include "color.hpp"
#include "opencv2/core/hal/intrin.hpp"
namespace cv
{
namespace cv {
namespace hal {
CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
// forward declarations
void cvtBGRtoYUV(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int scn, bool swapBlue, bool isCbCr);
void cvtYUVtoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int depth, int dcn, bool swapBlue, bool isCbCr);
void cvtTwoPlaneYUVtoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int dst_width, int dst_height,
int dcn, bool swapBlue, int uIdx);
void cvtTwoPlaneYUVtoBGR(const uchar * y_data, const uchar * uv_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int dst_width, int dst_height,
int dcn, bool swapBlue, int uIdx);
void cvtThreePlaneYUVtoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int dst_width, int dst_height,
int dcn, bool swapBlue, int uIdx);
void cvtBGRtoThreePlaneYUV(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int scn, bool swapBlue, int uIdx);
void cvtBGRtoTwoPlaneYUV(const uchar * src_data, size_t src_step,
uchar * y_data, uchar * uv_data, size_t dst_step,
int width, int height,
int scn, bool swapBlue, int uIdx);
void cvtOnePlaneYUVtoBGR(const uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int dcn, bool swapBlue, int uIdx, int ycn);
#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
#if defined(CV_CPU_BASELINE_MODE)
// included in color.hpp
#else
#include "color.simd_helpers.hpp"
#endif
namespace {
//constants for conversion from/to RGB and YUV, YCrCb according to BT.601
//to YCbCr
@ -1738,12 +1781,8 @@ inline void cvtYUV422toRGB(uchar * dst_data, size_t dst_step, const uchar * src_
converter(Range(0, height));
}
//
// HAL functions
//
} // namespace anon
namespace hal
{
// 8u, 16u, 32f
void cvtBGRtoYUV(const uchar * src_data, size_t src_step,
@ -1753,43 +1792,6 @@ void cvtBGRtoYUV(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGRtoYUV, cv_hal_cvtBGRtoYUV, src_data, src_step, dst_data, dst_step, width, height, depth, scn, swapBlue, isCbCr);
#if defined(HAVE_IPP)
#if !IPP_DISABLE_RGB_YUV
CV_IPP_CHECK()
{
if (scn == 3 && depth == CV_8U && swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralFunctor((ippiGeneralFunc)ippiRGBToYUV_8u_C3R)))
return;
}
else if (scn == 3 && depth == CV_8U && !swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC3RTab[depth],
(ippiGeneralFunc)ippiRGBToYUV_8u_C3R, 2, 1, 0, depth)))
return;
}
else if (scn == 4 && depth == CV_8U && swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC4C3RTab[depth],
(ippiGeneralFunc)ippiRGBToYUV_8u_C3R, 0, 1, 2, depth)))
return;
}
else if (scn == 4 && depth == CV_8U && !swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPReorderGeneralFunctor(ippiSwapChannelsC4C3RTab[depth],
(ippiGeneralFunc)ippiRGBToYUV_8u_C3R, 2, 1, 0, depth)))
return;
}
}
#endif
#endif
int blueIdx = swapBlue ? 2 : 0;
if( depth == CV_8U )
CvtColorLoop(src_data, src_step, dst_data, dst_step, width, height, RGB2YCrCb_i<uchar>(scn, blueIdx, isCbCr));
@ -1806,44 +1808,6 @@ void cvtYUVtoBGR(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtYUVtoBGR, cv_hal_cvtYUVtoBGR, src_data, src_step, dst_data, dst_step, width, height, depth, dcn, swapBlue, isCbCr);
#if defined(HAVE_IPP)
#if !IPP_DISABLE_YUV_RGB
CV_IPP_CHECK()
{
if (dcn == 3 && depth == CV_8U && swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralFunctor((ippiGeneralFunc)ippiYUVToRGB_8u_C3R)))
return;
}
else if (dcn == 3 && depth == CV_8U && !swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor((ippiGeneralFunc)ippiYUVToRGB_8u_C3R,
ippiSwapChannelsC3RTab[depth], 2, 1, 0, depth)))
return;
}
else if (dcn == 4 && depth == CV_8U && swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor((ippiGeneralFunc)ippiYUVToRGB_8u_C3R,
ippiSwapChannelsC3C4RTab[depth], 0, 1, 2, depth)))
return;
}
else if (dcn == 4 && depth == CV_8U && !swapBlue && !isCbCr)
{
if (CvtColorIPPLoop(src_data, src_step, dst_data, dst_step, width, height,
IPPGeneralReorderFunctor((ippiGeneralFunc)ippiYUVToRGB_8u_C3R,
ippiSwapChannelsC3C4RTab[depth], 2, 1, 0, depth)))
return;
}
}
#endif
#endif
int blueIdx = swapBlue ? 2 : 0;
if( depth == CV_8U )
CvtColorLoop(src_data, src_step, dst_data, dst_step, width, height, YCrCb2RGB_i<uchar>(dcn, blueIdx, isCbCr));
@ -1860,7 +1824,6 @@ void cvtTwoPlaneYUVtoBGR(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtTwoPlaneYUVtoBGR, cv_hal_cvtTwoPlaneYUVtoBGR, src_data, src_step, dst_data, dst_step, dst_width, dst_height, dcn, swapBlue, uIdx);
const uchar* uv = src_data + src_step * static_cast<size_t>(dst_height);
cvtTwoPlaneYUVtoBGR(src_data, uv, src_step, dst_data, dst_step, dst_width, dst_height, dcn, swapBlue, uIdx);
}
@ -1880,8 +1843,6 @@ void cvtTwoPlaneYUVtoBGR(const uchar * y_data, const uchar * uv_data, size_t src
{
CV_INSTRUMENT_REGION();
// TODO: add hal replacement method
int blueIdx = swapBlue ? 2 : 0;
cvt_2plane_yuv_ptr_t cvtPtr;
@ -1919,7 +1880,6 @@ void cvtThreePlaneYUVtoBGR(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtThreePlaneYUVtoBGR, cv_hal_cvtThreePlaneYUVtoBGR, src_data, src_step, dst_data, dst_step, dst_width, dst_height, dcn, swapBlue, uIdx);
const uchar* u = src_data + src_step * static_cast<size_t>(dst_height);
const uchar* v = src_data + src_step * static_cast<size_t>(dst_height + dst_height/4) + (dst_width/2) * ((dst_height % 4)/2);
@ -1949,7 +1909,6 @@ void cvtBGRtoThreePlaneYUV(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtBGRtoThreePlaneYUV, cv_hal_cvtBGRtoThreePlaneYUV, src_data, src_step, dst_data, dst_step, width, height, scn, swapBlue, uIdx);
uchar * uv_data = dst_data + dst_step * height;
RGB8toYUV420pInvoker cvt(src_data, src_step, dst_data, uv_data, dst_step, width, height,
@ -1968,8 +1927,6 @@ void cvtBGRtoTwoPlaneYUV(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
// TODO: add hal replacement method
RGB8toYUV420pInvoker cvt(src_data, src_step, y_data, uv_data, dst_step, width, height,
scn, swapBlue, uIdx == 2, true);
@ -1993,8 +1950,6 @@ void cvtOnePlaneYUVtoBGR(const uchar * src_data, size_t src_step,
{
CV_INSTRUMENT_REGION();
CALL_HAL(cvtOnePlaneYUVtoBGR, cv_hal_cvtOnePlaneYUVtoBGR, src_data, src_step, dst_data, dst_step, width, height, dcn, swapBlue, uIdx, ycn);
cvt_1plane_yuv_ptr_t cvtPtr;
int blueIdx = swapBlue ? 2 : 0;
switch(dcn*1000 + blueIdx*100 + uIdx*10 + ycn)
@ -2017,227 +1972,6 @@ void cvtOnePlaneYUVtoBGR(const uchar * src_data, size_t src_step,
cvtPtr(dst_data, dst_step, src_data, src_step, width, height);
}
} // namespace hal
//
// OCL calls
//
#ifdef HAVE_OPENCL
bool oclCvtColorYUV2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx )
{
OclHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
if(!h.createKernel("YUV2RGB", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=%d -D bidx=%d", dcn, bidx)))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR2YUV( InputArray _src, OutputArray _dst, int bidx )
{
OclHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, 3);
if(!h.createKernel("RGB2YUV", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=3 -D bidx=%d", bidx)))
{
return false;
}
return h.run();
}
bool oclCvtcolorYCrCb2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx)
{
OclHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
if(!h.createKernel("YCrCb2RGB", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=%d -D bidx=%d", dcn, bidx)))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR2YCrCb( InputArray _src, OutputArray _dst, int bidx)
{
OclHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, 3);
if(!h.createKernel("RGB2YCrCb", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=3 -D bidx=%d", bidx)))
{
return false;
}
return h.run();
}
bool oclCvtColorOnePlaneYUV2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx, int uidx, int yidx )
{
OclHelper< Set<2>, Set<3, 4>, Set<CV_8U> > h(_src, _dst, dcn);
bool optimized = _src.offset() % 4 == 0 && _src.step() % 4 == 0;
if(!h.createKernel("YUV2RGB_422", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=%d -D bidx=%d -D uidx=%d -D yidx=%d%s", dcn, bidx, uidx, yidx,
optimized ? " -D USE_OPTIMIZED_LOAD" : "")))
{
return false;
}
return h.run();
}
bool oclCvtColorYUV2Gray_420( InputArray _src, OutputArray _dst )
{
OclHelper< Set<1>, Set<1>, Set<CV_8U>, FROM_YUV> h(_src, _dst, 1);
h.src.rowRange(0, _dst.rows()).copyTo(_dst);
return true;
}
bool oclCvtColorTwoPlaneYUV2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx, int uidx )
{
OclHelper< Set<1>, Set<3, 4>, Set<CV_8U>, FROM_YUV > h(_src, _dst, dcn);
if(!h.createKernel("YUV2RGB_NVx", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=%d -D bidx=%d -D uidx=%d", dcn, bidx, uidx)))
{
return false;
}
return h.run();
}
bool oclCvtColorThreePlaneYUV2BGR( InputArray _src, OutputArray _dst, int dcn, int bidx, int uidx )
{
OclHelper< Set<1>, Set<3, 4>, Set<CV_8U>, FROM_YUV > h(_src, _dst, dcn);
if(!h.createKernel("YUV2RGB_YV12_IYUV", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=%d -D bidx=%d -D uidx=%d%s", dcn, bidx, uidx,
_src.isContinuous() ? " -D SRC_CONT" : "")))
{
return false;
}
return h.run();
}
bool oclCvtColorBGR2ThreePlaneYUV( InputArray _src, OutputArray _dst, int bidx, int uidx )
{
OclHelper< Set<3, 4>, Set<1>, Set<CV_8U>, TO_YUV > h(_src, _dst, 1);
if(!h.createKernel("RGB2YUV_YV12_IYUV", ocl::imgproc::color_yuv_oclsrc,
format("-D dcn=1 -D bidx=%d -D uidx=%d", bidx, uidx)))
{
return false;
}
return h.run();
}
#endif
//
// HAL calls
//
void cvtColorBGR2YUV(InputArray _src, OutputArray _dst, bool swapb, bool crcb)
{
CvtHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, 3);
hal::cvtBGRtoYUV(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, h.scn, swapb, crcb);
}
void cvtColorYUV2BGR(InputArray _src, OutputArray _dst, int dcn, bool swapb, bool crcb)
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<3>, Set<3, 4>, Set<CV_8U, CV_16U, CV_32F> > h(_src, _dst, dcn);
hal::cvtYUVtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.depth, dcn, swapb, crcb);
}
void cvtColorOnePlaneYUV2BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb, int uidx, int ycn)
{
CvtHelper< Set<2>, Set<3, 4>, Set<CV_8U> > h(_src, _dst, dcn);
hal::cvtOnePlaneYUVtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
dcn, swapb, uidx, ycn);
}
void cvtColorYUV2Gray_ch( InputArray _src, OutputArray _dst, int coi )
{
CV_Assert( _src.channels() == 2 && _src.depth() == CV_8U );
extractChannel(_src, _dst, coi);
}
void cvtColorBGR2ThreePlaneYUV( InputArray _src, OutputArray _dst, bool swapb, int uidx)
{
CvtHelper< Set<3, 4>, Set<1>, Set<CV_8U>, TO_YUV > h(_src, _dst, 1);
hal::cvtBGRtoThreePlaneYUV(h.src.data, h.src.step, h.dst.data, h.dst.step, h.src.cols, h.src.rows,
h.scn, swapb, uidx);
}
void cvtColorYUV2Gray_420( InputArray _src, OutputArray _dst )
{
CvtHelper< Set<1>, Set<1>, Set<CV_8U>, FROM_YUV > h(_src, _dst, 1);
#ifdef HAVE_IPP
#if IPP_VERSION_X100 >= 201700
if (CV_INSTRUMENT_FUN_IPP(ippiCopy_8u_C1R_L, h.src.data, (IppSizeL)h.src.step, h.dst.data, (IppSizeL)h.dst.step,
ippiSizeL(h.dstSz.width, h.dstSz.height)) >= 0)
return;
#endif
#endif
h.src(Range(0, h.dstSz.height), Range::all()).copyTo(h.dst);
}
void cvtColorThreePlaneYUV2BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb, int uidx)
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<1>, Set<3, 4>, Set<CV_8U>, FROM_YUV> h(_src, _dst, dcn);
hal::cvtThreePlaneYUVtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.dst.cols, h.dst.rows,
dcn, swapb, uidx);
}
// http://www.fourcc.org/yuv.php#NV21 == yuv420sp -> a plane of 8 bit Y samples followed by an interleaved V/U plane containing 8 bit 2x2 subsampled chroma samples
// http://www.fourcc.org/yuv.php#NV12 -> a plane of 8 bit Y samples followed by an interleaved U/V plane containing 8 bit 2x2 subsampled colour difference samples
void cvtColorTwoPlaneYUV2BGR( InputArray _src, OutputArray _dst, int dcn, bool swapb, int uidx )
{
if(dcn <= 0) dcn = 3;
CvtHelper< Set<1>, Set<3, 4>, Set<CV_8U>, FROM_YUV> h(_src, _dst, dcn);
hal::cvtTwoPlaneYUVtoBGR(h.src.data, h.src.step, h.dst.data, h.dst.step, h.dst.cols, h.dst.rows,
dcn, swapb, uidx);
}
void cvtColorTwoPlaneYUV2BGRpair( InputArray _ysrc, InputArray _uvsrc, OutputArray _dst, int dcn, bool swapb, int uidx )
{
int stype = _ysrc.type();
int depth = CV_MAT_DEPTH(stype);
Size ysz = _ysrc.size(), uvs = _uvsrc.size();
CV_Assert( dcn == 3 || dcn == 4 );
CV_Assert( depth == CV_8U );
CV_Assert( ysz.width == uvs.width * 2 && ysz.height == uvs.height * 2 );
Mat ysrc = _ysrc.getMat(), uvsrc = _uvsrc.getMat();
_dst.create( ysz, CV_MAKETYPE(depth, dcn));
Mat dst = _dst.getMat();
hal::cvtTwoPlaneYUVtoBGR(ysrc.data, uvsrc.data, ysrc.step,
dst.data, dst.step, dst.cols, dst.rows,
dcn, swapb, uidx);
}
} // namespace cv
CV_CPU_OPTIMIZATION_NAMESPACE_END
}} // namespace

197
modules/imgproc/src/filter.avx2.cpp
View File

@ -1,197 +0,0 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#include "filter.hpp"
namespace cv
{
int RowVec_32f_AVX(const float* src0, const float* _kx, float* dst, int width, int cn, int _ksize)
{
int i = 0, k;
for (; i <= width - 8; i += 8)
{
const float* src = src0 + i;
__m256 f, x0;
__m256 s0 = _mm256_set1_ps(0.0f);
for (k = 0; k < _ksize; k++, src += cn)
{
f = _mm256_set1_ps(_kx[k]);
x0 = _mm256_loadu_ps(src);
#if CV_FMA3
s0 = _mm256_fmadd_ps(x0, f, s0);
#else
s0 = _mm256_add_ps(s0, _mm256_mul_ps(x0, f));
#endif
}
_mm256_storeu_ps(dst + i, s0);
}
_mm256_zeroupper();
return i;
}
int SymmColumnVec_32f_Symm_AVX(const float** src, const float* ky, float* dst, float delta, int width, int ksize2)
{
int i = 0, k;
const float *S, *S2;
const __m128 d4 = _mm_set1_ps(delta);
const __m256 d8 = _mm256_set1_ps(delta);
for( ; i <= width - 16; i += 16 )
{
__m256 f = _mm256_set1_ps(ky[0]);
__m256 s0, s1;
__m256 x0;
S = src[0] + i;
s0 = _mm256_loadu_ps(S);
#if CV_FMA3
s0 = _mm256_fmadd_ps(s0, f, d8);
#else
s0 = _mm256_add_ps(_mm256_mul_ps(s0, f), d8);
#endif
s1 = _mm256_loadu_ps(S+8);
#if CV_FMA3
s1 = _mm256_fmadd_ps(s1, f, d8);
#else
s1 = _mm256_add_ps(_mm256_mul_ps(s1, f), d8);
#endif
for( k = 1; k <= ksize2; k++ )
{
S = src[k] + i;
S2 = src[-k] + i;
f = _mm256_set1_ps(ky[k]);
x0 = _mm256_add_ps(_mm256_loadu_ps(S), _mm256_loadu_ps(S2));
#if CV_FMA3
s0 = _mm256_fmadd_ps(x0, f, s0);
#else
s0 = _mm256_add_ps(s0, _mm256_mul_ps(x0, f));
#endif
x0 = _mm256_add_ps(_mm256_loadu_ps(S+8), _mm256_loadu_ps(S2+8));
#if CV_FMA3
s1 = _mm256_fmadd_ps(x0, f, s1);
#else
s1 = _mm256_add_ps(s1, _mm256_mul_ps(x0, f));
#endif
}
_mm256_storeu_ps(dst + i, s0);
_mm256_storeu_ps(dst + i + 8, s1);
}
for( ; i <= width - 4; i += 4 )
{
__m128 f = _mm_set1_ps(ky[0]);
__m128 x0, s0 = _mm_load_ps(src[0] + i);
s0 = _mm_add_ps(_mm_mul_ps(s0, f), d4);
for( k = 1; k <= ksize2; k++ )
{
f = _mm_set1_ps(ky[k]);
x0 = _mm_add_ps(_mm_load_ps(src[k]+i), _mm_load_ps(src[-k] + i));
s0 = _mm_add_ps(s0, _mm_mul_ps(x0, f));
}
_mm_storeu_ps(dst + i, s0);
}
_mm256_zeroupper();
return i;
}
int SymmColumnVec_32f_Unsymm_AVX(const float** src, const float* ky, float* dst, float delta, int width, int ksize2)
{
int i = 0, k;
const float *S2;
const __m128 d4 = _mm_set1_ps(delta);
const __m256 d8 = _mm256_set1_ps(delta);
for (; i <= width - 16; i += 16)
{
__m256 f, s0 = d8, s1 = d8;
__m256 x0;
for (k = 1; k <= ksize2; k++)
{
const float *S = src[k] + i;
S2 = src[-k] + i;
f = _mm256_set1_ps(ky[k]);
x0 = _mm256_sub_ps(_mm256_loadu_ps(S), _mm256_loadu_ps(S2));
#if CV_FMA3
s0 = _mm256_fmadd_ps(x0, f, s0);
#else
s0 = _mm256_add_ps(s0, _mm256_mul_ps(x0, f));
#endif
x0 = _mm256_sub_ps(_mm256_loadu_ps(S + 8), _mm256_loadu_ps(S2 + 8));
#if CV_FMA3
s1 = _mm256_fmadd_ps(x0, f, s1);
#else
s1 = _mm256_add_ps(s1, _mm256_mul_ps(x0, f));
#endif
}
_mm256_storeu_ps(dst + i, s0);
_mm256_storeu_ps(dst + i + 8, s1);
}
for (; i <= width - 4; i += 4)
{
__m128 f, x0, s0 = d4;
for (k = 1; k <= ksize2; k++)
{
f = _mm_set1_ps(ky[k]);
x0 = _mm_sub_ps(_mm_load_ps(src[k] + i), _mm_load_ps(src[-k] + i));
s0 = _mm_add_ps(s0, _mm_mul_ps(x0, f));
}
_mm_storeu_ps(dst + i, s0);
}
_mm256_zeroupper();
return i;
}
}
/* End of file. */

1432
modules/imgproc/src/filter.dispatch.cpp Normal file
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File diff suppressed because it is too large Load Diff

8
modules/imgproc/src/filter.hpp
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@ -45,17 +45,13 @@
namespace cv
{
#if CV_TRY_AVX2
int RowVec_32f_AVX(const float* src0, const float* _kx, float* dst, int width, int cn, int _ksize);
int SymmColumnVec_32f_Symm_AVX(const float** src, const float* ky, float* dst, float delta, int width, int ksize2);
int SymmColumnVec_32f_Unsymm_AVX(const float** src, const float* ky, float* dst, float delta, int width, int ksize2);
#endif
#ifdef HAVE_OPENCL
bool ocl_sepFilter2D( InputArray _src, OutputArray _dst, int ddepth,
InputArray _kernelX, InputArray _kernelY, Point anchor,
double delta, int borderType );
#endif
void preprocess2DKernel(const Mat& kernel, std::vector<Point>& coords, std::vector<uchar>& coeffs);
}
#endif

1666
modules/imgproc/src/filter.cpp → modules/imgproc/src/filter.simd.hpp
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File diff suppressed because it is too large Load Diff

5
modules/imgproc/src/fixedpoint.inl.hpp
View File

@ -9,10 +9,7 @@
#ifndef _CV_FIXEDPOINT_HPP_
#define _CV_FIXEDPOINT_HPP_
#include "opencv2/core/softfloat.hpp"
namespace
{
namespace {
class fixedpoint64
{

317
modules/imgproc/src/median_blur.dispatch.cpp Normal file
View File

@ -0,0 +1,317 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, 2018, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2014-2015, Itseez Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#include <vector>
#include "opencv2/core/hal/intrin.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "opencv2/core/openvx/ovx_defs.hpp"
#include "median_blur.simd.hpp"
#include "median_blur.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
namespace cv {
#ifdef HAVE_OPENCL
#define DIVUP(total, grain) ((total + grain - 1) / (grain))
static bool ocl_medianFilter(InputArray _src, OutputArray _dst, int m)
{
size_t localsize[2] = { 16, 16 };
size_t globalsize[2];
int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if ( !((depth == CV_8U || depth == CV_16U || depth == CV_16S || depth == CV_32F) && cn <= 4 && (m == 3 || m == 5)) )
return false;
Size imgSize = _src.size();
bool useOptimized = (1 == cn) &&
(size_t)imgSize.width >= localsize[0] * 8 &&
(size_t)imgSize.height >= localsize[1] * 8 &&
imgSize.width % 4 == 0 &&
imgSize.height % 4 == 0 &&
(ocl::Device::getDefault().isIntel());
cv::String kname = format( useOptimized ? "medianFilter%d_u" : "medianFilter%d", m) ;
cv::String kdefs = useOptimized ?
format("-D T=%s -D T1=%s -D T4=%s%d -D cn=%d -D USE_4OPT", ocl::typeToStr(type),
ocl::typeToStr(depth), ocl::typeToStr(depth), cn*4, cn)
:
format("-D T=%s -D T1=%s -D cn=%d", ocl::typeToStr(type), ocl::typeToStr(depth), cn) ;
ocl::Kernel k(kname.c_str(), ocl::imgproc::medianFilter_oclsrc, kdefs.c_str() );
if (k.empty())
return false;
UMat src = _src.getUMat();
_dst.create(src.size(), type);
UMat dst = _dst.getUMat();
k.args(ocl::KernelArg::ReadOnlyNoSize(src), ocl::KernelArg::WriteOnly(dst));
if( useOptimized )
{
globalsize[0] = DIVUP(src.cols / 4, localsize[0]) * localsize[0];
globalsize[1] = DIVUP(src.rows / 4, localsize[1]) * localsize[1];
}
else
{
globalsize[0] = (src.cols + localsize[0] + 2) / localsize[0] * localsize[0];
globalsize[1] = (src.rows + localsize[1] - 1) / localsize[1] * localsize[1];
}
return k.run(2, globalsize, localsize, false);
}
#undef DIVUP
#endif
#ifdef HAVE_OPENVX
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_MEDIAN_3x3>(int w, int h) { return w*h < 1280 * 720; }
}
static bool openvx_medianFilter(InputArray _src, OutputArray _dst, int ksize)
{
if (_src.type() != CV_8UC1 || _dst.type() != CV_8U
#ifndef VX_VERSION_1_1
|| ksize != 3
#endif
)
return false;
Mat src = _src.getMat();
Mat dst = _dst.getMat();
if (
#ifdef VX_VERSION_1_1
ksize != 3 ? ovx::skipSmallImages<VX_KERNEL_NON_LINEAR_FILTER>(src.cols, src.rows) :
#endif
ovx::skipSmallImages<VX_KERNEL_MEDIAN_3x3>(src.cols, src.rows)
)
return false;
try
{
ivx::Context ctx = ovx::getOpenVXContext();
#ifdef VX_VERSION_1_1
if ((vx_size)ksize > ctx.nonlinearMaxDimension())
return false;
#endif
Mat a;
if (dst.data != src.data)
a = src;
else
src.copyTo(a);
ivx::Image
ia = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(a.cols, a.rows, 1, (vx_int32)(a.step)), a.data),
ib = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(dst.cols, dst.rows, 1, (vx_int32)(dst.step)), dst.data);
//ATTENTION: VX_CONTEXT_IMMEDIATE_BORDER attribute change could lead to strange issues in multi-threaded environments
//since OpenVX standard says nothing about thread-safety for now
ivx::border_t prevBorder = ctx.immediateBorder();
ctx.setImmediateBorder(VX_BORDER_REPLICATE);
#ifdef VX_VERSION_1_1
if (ksize == 3)
#endif
{
ivx::IVX_CHECK_STATUS(vxuMedian3x3(ctx, ia, ib));
}
#ifdef VX_VERSION_1_1
else
{
ivx::Matrix mtx;
if(ksize == 5)
mtx = ivx::Matrix::createFromPattern(ctx, VX_PATTERN_BOX, ksize, ksize);
else
{
vx_size supportedSize;
ivx::IVX_CHECK_STATUS(vxQueryContext(ctx, VX_CONTEXT_NONLINEAR_MAX_DIMENSION, &supportedSize, sizeof(supportedSize)));
if ((vx_size)ksize > supportedSize)
{
ctx.setImmediateBorder(prevBorder);
return false;
}
Mat mask(ksize, ksize, CV_8UC1, Scalar(255));
mtx = ivx::Matrix::create(ctx, VX_TYPE_UINT8, ksize, ksize);
mtx.copyFrom(mask);
}
ivx::IVX_CHECK_STATUS(vxuNonLinearFilter(ctx, VX_NONLINEAR_FILTER_MEDIAN, ia, mtx, ib));
}
#endif
ctx.setImmediateBorder(prevBorder);
}
catch (const ivx::RuntimeError & e)
{
VX_DbgThrow(e.what());
}
catch (const ivx::WrapperError & e)
{
VX_DbgThrow(e.what());
}
return true;
}
#endif
#ifdef HAVE_IPP
static bool ipp_medianFilter(Mat &src0, Mat &dst, int ksize)
{
CV_INSTRUMENT_REGION_IPP();
#if IPP_VERSION_X100 < 201801
// Degradations for big kernel
if(ksize > 7)
return false;
#endif
{
int bufSize;
IppiSize dstRoiSize = ippiSize(dst.cols, dst.rows), maskSize = ippiSize(ksize, ksize);
IppDataType ippType = ippiGetDataType(src0.type());
int channels = src0.channels();
IppAutoBuffer<Ipp8u> buffer;
if(src0.isSubmatrix())
return false;
Mat src;
if(dst.data != src0.data)
src = src0;
else
src0.copyTo(src);
if(ippiFilterMedianBorderGetBufferSize(dstRoiSize, maskSize, ippType, channels, &bufSize) < 0)
return false;
buffer.allocate(bufSize);
switch(ippType)
{
case ipp8u:
if(channels == 1)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_8u_C1R, src.ptr<Ipp8u>(), (int)src.step, dst.ptr<Ipp8u>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else if(channels == 3)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_8u_C3R, src.ptr<Ipp8u>(), (int)src.step, dst.ptr<Ipp8u>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else if(channels == 4)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_8u_C4R, src.ptr<Ipp8u>(), (int)src.step, dst.ptr<Ipp8u>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else
return false;
case ipp16u:
if(channels == 1)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_16u_C1R, src.ptr<Ipp16u>(), (int)src.step, dst.ptr<Ipp16u>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else if(channels == 3)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_16u_C3R, src.ptr<Ipp16u>(), (int)src.step, dst.ptr<Ipp16u>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else if(channels == 4)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_16u_C4R, src.ptr<Ipp16u>(), (int)src.step, dst.ptr<Ipp16u>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else
return false;
case ipp16s:
if(channels == 1)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_16s_C1R, src.ptr<Ipp16s>(), (int)src.step, dst.ptr<Ipp16s>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else if(channels == 3)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_16s_C3R, src.ptr<Ipp16s>(), (int)src.step, dst.ptr<Ipp16s>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else if(channels == 4)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_16s_C4R, src.ptr<Ipp16s>(), (int)src.step, dst.ptr<Ipp16s>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else
return false;
case ipp32f:
if(channels == 1)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_32f_C1R, src.ptr<Ipp32f>(), (int)src.step, dst.ptr<Ipp32f>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else
return false;
default:
return false;
}
}
}
#endif
void medianBlur( InputArray _src0, OutputArray _dst, int ksize )
{
CV_INSTRUMENT_REGION();
CV_Assert( (ksize % 2 == 1) && (_src0.dims() <= 2 ));
if( ksize <= 1 || _src0.empty() )
{
_src0.copyTo(_dst);
return;
}
CV_OCL_RUN(_dst.isUMat(),
ocl_medianFilter(_src0,_dst, ksize))
Mat src0 = _src0.getMat();
_dst.create( src0.size(), src0.type() );
Mat dst = _dst.getMat();
CALL_HAL(medianBlur, cv_hal_medianBlur, src0.data, src0.step, dst.data, dst.step, src0.cols, src0.rows, src0.depth(),
src0.channels(), ksize);
CV_OVX_RUN(true,
openvx_medianFilter(_src0, _dst, ksize))
CV_IPP_RUN_FAST(ipp_medianFilter(src0, dst, ksize));
#ifdef HAVE_TEGRA_OPTIMIZATION
if (tegra::useTegra() && tegra::medianBlur(src0, dst, ksize))
return;
#endif
CV_CPU_DISPATCH(medianBlur, (src0, dst, ksize),
CV_CPU_DISPATCH_MODES_ALL);
}
} // namespace
/* End of file. */

290
modules/imgproc/src/median_blur.cpp → modules/imgproc/src/median_blur.simd.hpp
View File

@ -46,9 +46,11 @@
#include <vector>
#include "opencv2/core/hal/intrin.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "opencv2/core/openvx/ovx_defs.hpp"
#ifdef _MSC_VER
#pragma warning(disable: 4244) // warning C4244: 'argument': conversion from 'int' to 'ushort', possible loss of data
// triggered on intrinsic code from medianBlur_8u_O1()
#endif
/*
* This file includes the code, contributed by Simon Perreault
@ -71,12 +73,18 @@
Median Filter
\****************************************************************************************/
namespace cv
{
namespace cv {
CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
// forward declarations
void medianBlur(const Mat& src0, /*const*/ Mat& dst, int ksize);
#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
static void
medianBlur_8u_O1( const Mat& _src, Mat& _dst, int ksize )
{
CV_INSTRUMENT_REGION();
typedef ushort HT;
/**
@ -330,9 +338,6 @@ medianBlur_8u_O1( const Mat& _src, Mat& _dst, int ksize )
}
}
}
#if CV_SIMD
vx_cleanup();
#endif
}
#undef HOP
@ -342,6 +347,8 @@ medianBlur_8u_O1( const Mat& _src, Mat& _dst, int ksize )
static void
medianBlur_8u_Om( const Mat& _src, Mat& _dst, int m )
{
CV_INSTRUMENT_REGION();
#define N 16
int zone0[4][N];
int zone1[4][N*N];
@ -671,6 +678,8 @@ template<class Op, class VecOp>
static void
medianBlur_SortNet( const Mat& _src, Mat& _dst, int m )
{
CV_INSTRUMENT_REGION();
typedef typename Op::value_type T;
typedef typename Op::arg_type WT;
typedef typename VecOp::arg_type VT;
@ -770,9 +779,6 @@ medianBlur_SortNet( const Mat& _src, Mat& _dst, int m )
limit = size.width;
}
}
#if CV_SIMD
vx_cleanup();
#endif
}
else if( m == 5 )
{
@ -934,268 +940,15 @@ medianBlur_SortNet( const Mat& _src, Mat& _dst, int m )
limit = size.width;
}
}
#if CV_SIMD
vx_cleanup();
#endif
}
}
#ifdef HAVE_OPENCL
} // namespace anon
#define DIVUP(total, grain) ((total + grain - 1) / (grain))
static bool ocl_medianFilter(InputArray _src, OutputArray _dst, int m)
{
size_t localsize[2] = { 16, 16 };
size_t globalsize[2];
int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if ( !((depth == CV_8U || depth == CV_16U || depth == CV_16S || depth == CV_32F) && cn <= 4 && (m == 3 || m == 5)) )
return false;
Size imgSize = _src.size();
bool useOptimized = (1 == cn) &&
(size_t)imgSize.width >= localsize[0] * 8 &&
(size_t)imgSize.height >= localsize[1] * 8 &&
imgSize.width % 4 == 0 &&
imgSize.height % 4 == 0 &&
(ocl::Device::getDefault().isIntel());
cv::String kname = format( useOptimized ? "medianFilter%d_u" : "medianFilter%d", m) ;
cv::String kdefs = useOptimized ?
format("-D T=%s -D T1=%s -D T4=%s%d -D cn=%d -D USE_4OPT", ocl::typeToStr(type),
ocl::typeToStr(depth), ocl::typeToStr(depth), cn*4, cn)
:
format("-D T=%s -D T1=%s -D cn=%d", ocl::typeToStr(type), ocl::typeToStr(depth), cn) ;
ocl::Kernel k(kname.c_str(), ocl::imgproc::medianFilter_oclsrc, kdefs.c_str() );
if (k.empty())
return false;
UMat src = _src.getUMat();
_dst.create(src.size(), type);
UMat dst = _dst.getUMat();
k.args(ocl::KernelArg::ReadOnlyNoSize(src), ocl::KernelArg::WriteOnly(dst));
if( useOptimized )
{
globalsize[0] = DIVUP(src.cols / 4, localsize[0]) * localsize[0];
globalsize[1] = DIVUP(src.rows / 4, localsize[1]) * localsize[1];
}
else
{
globalsize[0] = (src.cols + localsize[0] + 2) / localsize[0] * localsize[0];
globalsize[1] = (src.rows + localsize[1] - 1) / localsize[1] * localsize[1];
}
return k.run(2, globalsize, localsize, false);
}
#undef DIVUP
#endif
#ifdef HAVE_OPENVX
} // close anonymous namespace #13634
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_MEDIAN_3x3>(int w, int h) { return w*h < 1280 * 720; }
}
namespace { // reopen it
static bool openvx_medianFilter(InputArray _src, OutputArray _dst, int ksize)
{
if (_src.type() != CV_8UC1 || _dst.type() != CV_8U
#ifndef VX_VERSION_1_1
|| ksize != 3
#endif
)
return false;
Mat src = _src.getMat();
Mat dst = _dst.getMat();
if (
#ifdef VX_VERSION_1_1
ksize != 3 ? ovx::skipSmallImages<VX_KERNEL_NON_LINEAR_FILTER>(src.cols, src.rows) :
#endif
ovx::skipSmallImages<VX_KERNEL_MEDIAN_3x3>(src.cols, src.rows)
)
return false;
try
{
ivx::Context ctx = ovx::getOpenVXContext();
#ifdef VX_VERSION_1_1
if ((vx_size)ksize > ctx.nonlinearMaxDimension())
return false;
#endif
Mat a;
if (dst.data != src.data)
a = src;
else
src.copyTo(a);
ivx::Image
ia = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(a.cols, a.rows, 1, (vx_int32)(a.step)), a.data),
ib = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(dst.cols, dst.rows, 1, (vx_int32)(dst.step)), dst.data);
//ATTENTION: VX_CONTEXT_IMMEDIATE_BORDER attribute change could lead to strange issues in multi-threaded environments
//since OpenVX standard says nothing about thread-safety for now
ivx::border_t prevBorder = ctx.immediateBorder();
ctx.setImmediateBorder(VX_BORDER_REPLICATE);
#ifdef VX_VERSION_1_1
if (ksize == 3)
#endif
{
ivx::IVX_CHECK_STATUS(vxuMedian3x3(ctx, ia, ib));
}
#ifdef VX_VERSION_1_1
else
{
ivx::Matrix mtx;
if(ksize == 5)
mtx = ivx::Matrix::createFromPattern(ctx, VX_PATTERN_BOX, ksize, ksize);
else
{
vx_size supportedSize;
ivx::IVX_CHECK_STATUS(vxQueryContext(ctx, VX_CONTEXT_NONLINEAR_MAX_DIMENSION, &supportedSize, sizeof(supportedSize)));
if ((vx_size)ksize > supportedSize)
{
ctx.setImmediateBorder(prevBorder);
return false;
}
Mat mask(ksize, ksize, CV_8UC1, Scalar(255));
mtx = ivx::Matrix::create(ctx, VX_TYPE_UINT8, ksize, ksize);
mtx.copyFrom(mask);
}
ivx::IVX_CHECK_STATUS(vxuNonLinearFilter(ctx, VX_NONLINEAR_FILTER_MEDIAN, ia, mtx, ib));
}
#endif
ctx.setImmediateBorder(prevBorder);
}
catch (const ivx::RuntimeError & e)
{
VX_DbgThrow(e.what());
}
catch (const ivx::WrapperError & e)
{
VX_DbgThrow(e.what());
}
return true;
}
#endif
#if 0 //defined HAVE_IPP
static bool ipp_medianFilter(Mat &src0, Mat &dst, int ksize)
{
CV_INSTRUMENT_REGION_IPP();
#if IPP_VERSION_X100 < 201801
// Degradations for big kernel
if(ksize > 7)
return false;
#endif
{
int bufSize;
IppiSize dstRoiSize = ippiSize(dst.cols, dst.rows), maskSize = ippiSize(ksize, ksize);
IppDataType ippType = ippiGetDataType(src0.type());
int channels = src0.channels();
IppAutoBuffer<Ipp8u> buffer;
if(src0.isSubmatrix())
return false;
Mat src;
if(dst.data != src0.data)
src = src0;
else
src0.copyTo(src);
if(ippiFilterMedianBorderGetBufferSize(dstRoiSize, maskSize, ippType, channels, &bufSize) < 0)
return false;
buffer.allocate(bufSize);
switch(ippType)
{
case ipp8u:
if(channels == 1)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_8u_C1R, src.ptr<Ipp8u>(), (int)src.step, dst.ptr<Ipp8u>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else if(channels == 3)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_8u_C3R, src.ptr<Ipp8u>(), (int)src.step, dst.ptr<Ipp8u>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else if(channels == 4)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_8u_C4R, src.ptr<Ipp8u>(), (int)src.step, dst.ptr<Ipp8u>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else
return false;
case ipp16u:
if(channels == 1)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_16u_C1R, src.ptr<Ipp16u>(), (int)src.step, dst.ptr<Ipp16u>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else if(channels == 3)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_16u_C3R, src.ptr<Ipp16u>(), (int)src.step, dst.ptr<Ipp16u>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else if(channels == 4)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_16u_C4R, src.ptr<Ipp16u>(), (int)src.step, dst.ptr<Ipp16u>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else
return false;
case ipp16s:
if(channels == 1)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_16s_C1R, src.ptr<Ipp16s>(), (int)src.step, dst.ptr<Ipp16s>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else if(channels == 3)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_16s_C3R, src.ptr<Ipp16s>(), (int)src.step, dst.ptr<Ipp16s>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else if(channels == 4)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_16s_C4R, src.ptr<Ipp16s>(), (int)src.step, dst.ptr<Ipp16s>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else
return false;
case ipp32f:
if(channels == 1)
return CV_INSTRUMENT_FUN_IPP(ippiFilterMedianBorder_32f_C1R, src.ptr<Ipp32f>(), (int)src.step, dst.ptr<Ipp32f>(), (int)dst.step, dstRoiSize, maskSize, ippBorderRepl, 0, buffer) >= 0;
else
return false;
default:
return false;
}
}
}
#endif
}
void medianBlur( InputArray _src0, OutputArray _dst, int ksize )
void medianBlur(const Mat& src0, /*const*/ Mat& dst, int ksize)
{
CV_INSTRUMENT_REGION();
CV_Assert( (ksize % 2 == 1) && (_src0.dims() <= 2 ));
if( ksize <= 1 || _src0.empty() )
{
_src0.copyTo(_dst);
return;
}
CV_OCL_RUN(_dst.isUMat(),
ocl_medianFilter(_src0,_dst, ksize))
Mat src0 = _src0.getMat();
_dst.create( src0.size(), src0.type() );
Mat dst = _dst.getMat();
CALL_HAL(medianBlur, cv_hal_medianBlur, src0.data, src0.step, dst.data, dst.step, src0.cols, src0.rows, src0.depth(),
src0.channels(), ksize);
CV_OVX_RUN(true,
openvx_medianFilter(_src0, _dst, ksize))
//CV_IPP_RUN_FAST(ipp_medianFilter(src0, dst, ksize));
#ifdef HAVE_TEGRA_OPTIMIZATION
if (tegra::useTegra() && tegra::medianBlur(src0, dst, ksize))
return;
#endif
bool useSortNet = ksize == 3 || (ksize == 5
#if !(CV_SIMD)
&& ( src0.depth() > CV_8U || src0.channels() == 2 || src0.channels() > 4 )
@ -1225,6 +978,7 @@ void medianBlur( InputArray _src0, OutputArray _dst, int ksize )
}
else
{
// TODO AVX guard (external call)
cv::copyMakeBorder( src0, src, 0, 0, ksize/2, ksize/2, BORDER_REPLICATE|BORDER_ISOLATED);
int cn = src0.channels();
@ -1239,6 +993,6 @@ void medianBlur( InputArray _src0, OutputArray _dst, int ksize )
}
}
}
/* End of file. */
#endif
CV_CPU_OPTIMIZATION_NAMESPACE_END
} // namespace

794
modules/imgproc/src/morph.cpp → modules/imgproc/src/morph.dispatch.cpp
View File

@ -48,777 +48,47 @@
#include "opencv2/core/hal/intrin.hpp"
#include <opencv2/core/utils/configuration.private.hpp>
#include "morph.simd.hpp"
#include "morph.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
/****************************************************************************************\
Basic Morphological Operations: Erosion & Dilation
\****************************************************************************************/
using namespace std;
namespace cv
{
template<typename T> struct MinOp
{
typedef T type1;
typedef T type2;
typedef T rtype;
T operator ()(const T a, const T b) const { return std::min(a, b); }
};
template<typename T> struct MaxOp
{
typedef T type1;
typedef T type2;
typedef T rtype;
T operator ()(const T a, const T b) const { return std::max(a, b); }
};
#undef CV_MIN_8U
#undef CV_MAX_8U
#define CV_MIN_8U(a,b) ((a) - CV_FAST_CAST_8U((a) - (b)))
#define CV_MAX_8U(a,b) ((a) + CV_FAST_CAST_8U((b) - (a)))
template<> inline uchar MinOp<uchar>::operator ()(const uchar a, const uchar b) const { return CV_MIN_8U(a, b); }
template<> inline uchar MaxOp<uchar>::operator ()(const uchar a, const uchar b) const { return CV_MAX_8U(a, b); }
struct MorphRowNoVec
{
MorphRowNoVec(int, int) {}
int operator()(const uchar*, uchar*, int, int) const { return 0; }
};
struct MorphColumnNoVec
{
MorphColumnNoVec(int, int) {}
int operator()(const uchar**, uchar*, int, int, int) const { return 0; }
};
struct MorphNoVec
{
int operator()(uchar**, int, uchar*, int) const { return 0; }
};
#if CV_SIMD
template<class VecUpdate> struct MorphRowVec
{
typedef typename VecUpdate::vtype vtype;
typedef typename vtype::lane_type stype;
MorphRowVec(int _ksize, int _anchor) : ksize(_ksize), anchor(_anchor) {}
int operator()(const uchar* src, uchar* dst, int width, int cn) const
{
int i, k, _ksize = ksize*cn;
width *= cn;
VecUpdate updateOp;
for( i = 0; i <= width - 4*vtype::nlanes; i += 4*vtype::nlanes )
{
vtype s0 = vx_load((const stype*)src + i);
vtype s1 = vx_load((const stype*)src + i + vtype::nlanes);
vtype s2 = vx_load((const stype*)src + i + 2*vtype::nlanes);
vtype s3 = vx_load((const stype*)src + i + 3*vtype::nlanes);
for (k = cn; k < _ksize; k += cn)
{
s0 = updateOp(s0, vx_load((const stype*)src + i + k));
s1 = updateOp(s1, vx_load((const stype*)src + i + k + vtype::nlanes));
s2 = updateOp(s2, vx_load((const stype*)src + i + k + 2*vtype::nlanes));
s3 = updateOp(s3, vx_load((const stype*)src + i + k + 3*vtype::nlanes));
}
v_store((stype*)dst + i, s0);
v_store((stype*)dst + i + vtype::nlanes, s1);
v_store((stype*)dst + i + 2*vtype::nlanes, s2);
v_store((stype*)dst + i + 3*vtype::nlanes, s3);
}
if( i <= width - 2*vtype::nlanes )
{
vtype s0 = vx_load((const stype*)src + i);
vtype s1 = vx_load((const stype*)src + i + vtype::nlanes);
for( k = cn; k < _ksize; k += cn )
{
s0 = updateOp(s0, vx_load((const stype*)src + i + k));
s1 = updateOp(s1, vx_load((const stype*)src + i + k + vtype::nlanes));
}
v_store((stype*)dst + i, s0);
v_store((stype*)dst + i + vtype::nlanes, s1);
i += 2*vtype::nlanes;
}
if( i <= width - vtype::nlanes )
{
vtype s = vx_load((const stype*)src + i);
for( k = cn; k < _ksize; k += cn )
s = updateOp(s, vx_load((const stype*)src + i + k));
v_store((stype*)dst + i, s);
i += vtype::nlanes;
}
if( i <= width - vtype::nlanes/2 )
{
vtype s = vx_load_low((const stype*)src + i);
for( k = cn; k < _ksize; k += cn )
s = updateOp(s, vx_load_low((const stype*)src + i + k));
v_store_low((stype*)dst + i, s);
i += vtype::nlanes/2;
}
return i - i % cn;
}
int ksize, anchor;
};
template<class VecUpdate> struct MorphColumnVec
{
typedef typename VecUpdate::vtype vtype;
typedef typename vtype::lane_type stype;
MorphColumnVec(int _ksize, int _anchor) : ksize(_ksize), anchor(_anchor) {}
int operator()(const uchar** _src, uchar* _dst, int dststep, int count, int width) const
{
int i = 0, k, _ksize = ksize;
VecUpdate updateOp;
for( i = 0; i < count + ksize - 1; i++ )
CV_Assert( ((size_t)_src[i] & (CV_SIMD_WIDTH-1)) == 0 );
const stype** src = (const stype**)_src;
stype* dst = (stype*)_dst;
dststep /= sizeof(dst[0]);
for( ; _ksize > 1 && count > 1; count -= 2, dst += dststep*2, src += 2 )
{
for( i = 0; i <= width - 4*vtype::nlanes; i += 4*vtype::nlanes)
{
const stype* sptr = src[1] + i;
vtype s0 = vx_load_aligned(sptr);
vtype s1 = vx_load_aligned(sptr + vtype::nlanes);
vtype s2 = vx_load_aligned(sptr + 2*vtype::nlanes);
vtype s3 = vx_load_aligned(sptr + 3*vtype::nlanes);
for( k = 2; k < _ksize; k++ )
{
sptr = src[k] + i;
s0 = updateOp(s0, vx_load_aligned(sptr));
s1 = updateOp(s1, vx_load_aligned(sptr + vtype::nlanes));
s2 = updateOp(s2, vx_load_aligned(sptr + 2*vtype::nlanes));
s3 = updateOp(s3, vx_load_aligned(sptr + 3*vtype::nlanes));
}
sptr = src[0] + i;
v_store(dst + i, updateOp(s0, vx_load_aligned(sptr)));
v_store(dst + i + vtype::nlanes, updateOp(s1, vx_load_aligned(sptr + vtype::nlanes)));
v_store(dst + i + 2*vtype::nlanes, updateOp(s2, vx_load_aligned(sptr + 2*vtype::nlanes)));
v_store(dst + i + 3*vtype::nlanes, updateOp(s3, vx_load_aligned(sptr + 3*vtype::nlanes)));
sptr = src[k] + i;
v_store(dst + dststep + i, updateOp(s0, vx_load_aligned(sptr)));
v_store(dst + dststep + i + vtype::nlanes, updateOp(s1, vx_load_aligned(sptr + vtype::nlanes)));
v_store(dst + dststep + i + 2*vtype::nlanes, updateOp(s2, vx_load_aligned(sptr + 2*vtype::nlanes)));
v_store(dst + dststep + i + 3*vtype::nlanes, updateOp(s3, vx_load_aligned(sptr + 3*vtype::nlanes)));
}
if( i <= width - 2*vtype::nlanes )
{
const stype* sptr = src[1] + i;
vtype s0 = vx_load_aligned(sptr);
vtype s1 = vx_load_aligned(sptr + vtype::nlanes);
for( k = 2; k < _ksize; k++ )
{
sptr = src[k] + i;
s0 = updateOp(s0, vx_load_aligned(sptr));
s1 = updateOp(s1, vx_load_aligned(sptr + vtype::nlanes));
}
sptr = src[0] + i;
v_store(dst + i, updateOp(s0, vx_load_aligned(sptr)));
v_store(dst + i + vtype::nlanes, updateOp(s1, vx_load_aligned(sptr + vtype::nlanes)));
sptr = src[k] + i;
v_store(dst + dststep + i, updateOp(s0, vx_load_aligned(sptr)));
v_store(dst + dststep + i + vtype::nlanes, updateOp(s1, vx_load_aligned(sptr + vtype::nlanes)));
i += 2*vtype::nlanes;
}
if( i <= width - vtype::nlanes )
{
vtype s0 = vx_load_aligned(src[1] + i);
for( k = 2; k < _ksize; k++ )
s0 = updateOp(s0, vx_load_aligned(src[k] + i));
v_store(dst + i, updateOp(s0, vx_load_aligned(src[0] + i)));
v_store(dst + dststep + i, updateOp(s0, vx_load_aligned(src[k] + i)));
i += vtype::nlanes;
}
if( i <= width - vtype::nlanes/2 )
{
vtype s0 = vx_load_low(src[1] + i);
for( k = 2; k < _ksize; k++ )
s0 = updateOp(s0, vx_load_low(src[k] + i));
v_store_low(dst + i, updateOp(s0, vx_load_low(src[0] + i)));
v_store_low(dst + dststep + i, updateOp(s0, vx_load_low(src[k] + i)));
i += vtype::nlanes/2;
}
}
for( ; count > 0; count--, dst += dststep, src++ )
{
for( i = 0; i <= width - 4*vtype::nlanes; i += 4*vtype::nlanes)
{
const stype* sptr = src[0] + i;
vtype s0 = vx_load_aligned(sptr);
vtype s1 = vx_load_aligned(sptr + vtype::nlanes);
vtype s2 = vx_load_aligned(sptr + 2*vtype::nlanes);
vtype s3 = vx_load_aligned(sptr + 3*vtype::nlanes);
for( k = 1; k < _ksize; k++ )
{
sptr = src[k] + i;
s0 = updateOp(s0, vx_load_aligned(sptr));
s1 = updateOp(s1, vx_load_aligned(sptr + vtype::nlanes));
s2 = updateOp(s2, vx_load_aligned(sptr + 2*vtype::nlanes));
s3 = updateOp(s3, vx_load_aligned(sptr + 3*vtype::nlanes));
}
v_store(dst + i, s0);
v_store(dst + i + vtype::nlanes, s1);
v_store(dst + i + 2*vtype::nlanes, s2);
v_store(dst + i + 3*vtype::nlanes, s3);
}
if( i <= width - 2*vtype::nlanes )
{
const stype* sptr = src[0] + i;
vtype s0 = vx_load_aligned(sptr);
vtype s1 = vx_load_aligned(sptr + vtype::nlanes);
for( k = 1; k < _ksize; k++ )
{
sptr = src[k] + i;
s0 = updateOp(s0, vx_load_aligned(sptr));
s1 = updateOp(s1, vx_load_aligned(sptr + vtype::nlanes));
}
v_store(dst + i, s0);
v_store(dst + i + vtype::nlanes, s1);
i += 2*vtype::nlanes;
}
if( i <= width - vtype::nlanes )
{
vtype s0 = vx_load_aligned(src[0] + i);
for( k = 1; k < _ksize; k++ )
s0 = updateOp(s0, vx_load_aligned(src[k] + i));
v_store(dst + i, s0);
i += vtype::nlanes;
}
if( i <= width - vtype::nlanes/2 )
{
vtype s0 = vx_load_low(src[0] + i);
for( k = 1; k < _ksize; k++ )
s0 = updateOp(s0, vx_load_low(src[k] + i));
v_store_low(dst + i, s0);
i += vtype::nlanes/2;
}
}
return i;
}
int ksize, anchor;
};
template<class VecUpdate> struct MorphVec
{
typedef typename VecUpdate::vtype vtype;
typedef typename vtype::lane_type stype;
int operator()(uchar** _src, int nz, uchar* _dst, int width) const
{
const stype** src = (const stype**)_src;
stype* dst = (stype*)_dst;
int i, k;
VecUpdate updateOp;
for( i = 0; i <= width - 4*vtype::nlanes; i += 4*vtype::nlanes )
{
const stype* sptr = src[0] + i;
vtype s0 = vx_load(sptr);
vtype s1 = vx_load(sptr + vtype::nlanes);
vtype s2 = vx_load(sptr + 2*vtype::nlanes);
vtype s3 = vx_load(sptr + 3*vtype::nlanes);
for( k = 1; k < nz; k++ )
{
sptr = src[k] + i;
s0 = updateOp(s0, vx_load(sptr));
s1 = updateOp(s1, vx_load(sptr + vtype::nlanes));
s2 = updateOp(s2, vx_load(sptr + 2*vtype::nlanes));
s3 = updateOp(s3, vx_load(sptr + 3*vtype::nlanes));
}
v_store(dst + i, s0);
v_store(dst + i + vtype::nlanes, s1);
v_store(dst + i + 2*vtype::nlanes, s2);
v_store(dst + i + 3*vtype::nlanes, s3);
}
if( i <= width - 2*vtype::nlanes )
{
const stype* sptr = src[0] + i;
vtype s0 = vx_load(sptr);
vtype s1 = vx_load(sptr + vtype::nlanes);
for( k = 1; k < nz; k++ )
{
sptr = src[k] + i;
s0 = updateOp(s0, vx_load(sptr));
s1 = updateOp(s1, vx_load(sptr + vtype::nlanes));
}
v_store(dst + i, s0);
v_store(dst + i + vtype::nlanes, s1);
i += 2*vtype::nlanes;
}
if( i <= width - vtype::nlanes )
{
vtype s0 = vx_load(src[0] + i);
for( k = 1; k < nz; k++ )
s0 = updateOp(s0, vx_load(src[k] + i));
v_store(dst + i, s0);
i += vtype::nlanes;
}
if( i <= width - vtype::nlanes/2 )
{
vtype s0 = vx_load_low(src[0] + i);
for( k = 1; k < nz; k++ )
s0 = updateOp(s0, vx_load_low(src[k] + i));
v_store_low(dst + i, s0);
i += vtype::nlanes/2;
}
return i;
}
};
template <typename T> struct VMin
{
typedef T vtype;
vtype operator()(const vtype& a, const vtype& b) const { return v_min(a,b); }
};
template <typename T> struct VMax
{
typedef T vtype;
vtype operator()(const vtype& a, const vtype& b) const { return v_max(a,b); }
};
typedef MorphRowVec<VMin<v_uint8> > ErodeRowVec8u;
typedef MorphRowVec<VMax<v_uint8> > DilateRowVec8u;
typedef MorphRowVec<VMin<v_uint16> > ErodeRowVec16u;
typedef MorphRowVec<VMax<v_uint16> > DilateRowVec16u;
typedef MorphRowVec<VMin<v_int16> > ErodeRowVec16s;
typedef MorphRowVec<VMax<v_int16> > DilateRowVec16s;
typedef MorphRowVec<VMin<v_float32> > ErodeRowVec32f;
typedef MorphRowVec<VMax<v_float32> > DilateRowVec32f;
typedef MorphColumnVec<VMin<v_uint8> > ErodeColumnVec8u;
typedef MorphColumnVec<VMax<v_uint8> > DilateColumnVec8u;
typedef MorphColumnVec<VMin<v_uint16> > ErodeColumnVec16u;
typedef MorphColumnVec<VMax<v_uint16> > DilateColumnVec16u;
typedef MorphColumnVec<VMin<v_int16> > ErodeColumnVec16s;
typedef MorphColumnVec<VMax<v_int16> > DilateColumnVec16s;
typedef MorphColumnVec<VMin<v_float32> > ErodeColumnVec32f;
typedef MorphColumnVec<VMax<v_float32> > DilateColumnVec32f;
typedef MorphVec<VMin<v_uint8> > ErodeVec8u;
typedef MorphVec<VMax<v_uint8> > DilateVec8u;
typedef MorphVec<VMin<v_uint16> > ErodeVec16u;
typedef MorphVec<VMax<v_uint16> > DilateVec16u;
typedef MorphVec<VMin<v_int16> > ErodeVec16s;
typedef MorphVec<VMax<v_int16> > DilateVec16s;
typedef MorphVec<VMin<v_float32> > ErodeVec32f;
typedef MorphVec<VMax<v_float32> > DilateVec32f;
#else
typedef MorphRowNoVec ErodeRowVec8u;
typedef MorphRowNoVec DilateRowVec8u;
typedef MorphColumnNoVec ErodeColumnVec8u;
typedef MorphColumnNoVec DilateColumnVec8u;
typedef MorphRowNoVec ErodeRowVec16u;
typedef MorphRowNoVec DilateRowVec16u;
typedef MorphRowNoVec ErodeRowVec16s;
typedef MorphRowNoVec DilateRowVec16s;
typedef MorphRowNoVec ErodeRowVec32f;
typedef MorphRowNoVec DilateRowVec32f;
typedef MorphColumnNoVec ErodeColumnVec16u;
typedef MorphColumnNoVec DilateColumnVec16u;
typedef MorphColumnNoVec ErodeColumnVec16s;
typedef MorphColumnNoVec DilateColumnVec16s;
typedef MorphColumnNoVec ErodeColumnVec32f;
typedef MorphColumnNoVec DilateColumnVec32f;
typedef MorphNoVec ErodeVec8u;
typedef MorphNoVec DilateVec8u;
typedef MorphNoVec ErodeVec16u;
typedef MorphNoVec DilateVec16u;
typedef MorphNoVec ErodeVec16s;
typedef MorphNoVec DilateVec16s;
typedef MorphNoVec ErodeVec32f;
typedef MorphNoVec DilateVec32f;
#endif
typedef MorphRowNoVec ErodeRowVec64f;
typedef MorphRowNoVec DilateRowVec64f;
typedef MorphColumnNoVec ErodeColumnVec64f;
typedef MorphColumnNoVec DilateColumnVec64f;
typedef MorphNoVec ErodeVec64f;
typedef MorphNoVec DilateVec64f;
template<class Op, class VecOp> struct MorphRowFilter : public BaseRowFilter
{
typedef typename Op::rtype T;
MorphRowFilter( int _ksize, int _anchor ) : vecOp(_ksize, _anchor)
{
ksize = _ksize;
anchor = _anchor;
}
void operator()(const uchar* src, uchar* dst, int width, int cn) CV_OVERRIDE
{
int i, j, k, _ksize = ksize*cn;
const T* S = (const T*)src;
Op op;
T* D = (T*)dst;
if( _ksize == cn )
{
for( i = 0; i < width*cn; i++ )
D[i] = S[i];
return;
}
int i0 = vecOp(src, dst, width, cn);
width *= cn;
for( k = 0; k < cn; k++, S++, D++ )
{
for( i = i0; i <= width - cn*2; i += cn*2 )
{
const T* s = S + i;
T m = s[cn];
for( j = cn*2; j < _ksize; j += cn )
m = op(m, s[j]);
D[i] = op(m, s[0]);
D[i+cn] = op(m, s[j]);
}
for( ; i < width; i += cn )
{
const T* s = S + i;
T m = s[0];
for( j = cn; j < _ksize; j += cn )
m = op(m, s[j]);
D[i] = m;
}
}
}
VecOp vecOp;
};
template<class Op, class VecOp> struct MorphColumnFilter : public BaseColumnFilter
{
typedef typename Op::rtype T;
MorphColumnFilter( int _ksize, int _anchor ) : vecOp(_ksize, _anchor)
{
ksize = _ksize;
anchor = _anchor;
}
void operator()(const uchar** _src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
int i, k, _ksize = ksize;
const T** src = (const T**)_src;
T* D = (T*)dst;
Op op;
int i0 = vecOp(_src, dst, dststep, count, width);
dststep /= sizeof(D[0]);
for( ; _ksize > 1 && count > 1; count -= 2, D += dststep*2, src += 2 )
{
i = i0;
#if CV_ENABLE_UNROLLED
for( ; i <= width - 4; i += 4 )
{
const T* sptr = src[1] + i;
T s0 = sptr[0], s1 = sptr[1], s2 = sptr[2], s3 = sptr[3];
for( k = 2; k < _ksize; k++ )
{
sptr = src[k] + i;
s0 = op(s0, sptr[0]); s1 = op(s1, sptr[1]);
s2 = op(s2, sptr[2]); s3 = op(s3, sptr[3]);
}
sptr = src[0] + i;
D[i] = op(s0, sptr[0]);
D[i+1] = op(s1, sptr[1]);
D[i+2] = op(s2, sptr[2]);
D[i+3] = op(s3, sptr[3]);
sptr = src[k] + i;
D[i+dststep] = op(s0, sptr[0]);
D[i+dststep+1] = op(s1, sptr[1]);
D[i+dststep+2] = op(s2, sptr[2]);
D[i+dststep+3] = op(s3, sptr[3]);
}
#endif
for( ; i < width; i++ )
{
T s0 = src[1][i];
for( k = 2; k < _ksize; k++ )
s0 = op(s0, src[k][i]);
D[i] = op(s0, src[0][i]);
D[i+dststep] = op(s0, src[k][i]);
}
}
for( ; count > 0; count--, D += dststep, src++ )
{
i = i0;
#if CV_ENABLE_UNROLLED
for( ; i <= width - 4; i += 4 )
{
const T* sptr = src[0] + i;
T s0 = sptr[0], s1 = sptr[1], s2 = sptr[2], s3 = sptr[3];
for( k = 1; k < _ksize; k++ )
{
sptr = src[k] + i;
s0 = op(s0, sptr[0]); s1 = op(s1, sptr[1]);
s2 = op(s2, sptr[2]); s3 = op(s3, sptr[3]);
}
D[i] = s0; D[i+1] = s1;
D[i+2] = s2; D[i+3] = s3;
}
#endif
for( ; i < width; i++ )
{
T s0 = src[0][i];
for( k = 1; k < _ksize; k++ )
s0 = op(s0, src[k][i]);
D[i] = s0;
}
}
}
VecOp vecOp;
};
template<class Op, class VecOp> struct MorphFilter : BaseFilter
{
typedef typename Op::rtype T;
MorphFilter( const Mat& _kernel, Point _anchor )
{
anchor = _anchor;
ksize = _kernel.size();
CV_Assert( _kernel.type() == CV_8U );
std::vector<uchar> coeffs; // we do not really the values of non-zero
// kernel elements, just their locations
preprocess2DKernel( _kernel, coords, coeffs );
ptrs.resize( coords.size() );
}
void operator()(const uchar** src, uchar* dst, int dststep, int count, int width, int cn) CV_OVERRIDE
{
const Point* pt = &coords[0];
const T** kp = (const T**)&ptrs[0];
int i, k, nz = (int)coords.size();
Op op;
width *= cn;
for( ; count > 0; count--, dst += dststep, src++ )
{
T* D = (T*)dst;
for( k = 0; k < nz; k++ )
kp[k] = (const T*)src[pt[k].y] + pt[k].x*cn;
i = vecOp(&ptrs[0], nz, dst, width);
#if CV_ENABLE_UNROLLED
for( ; i <= width - 4; i += 4 )
{
const T* sptr = kp[0] + i;
T s0 = sptr[0], s1 = sptr[1], s2 = sptr[2], s3 = sptr[3];
for( k = 1; k < nz; k++ )
{
sptr = kp[k] + i;
s0 = op(s0, sptr[0]); s1 = op(s1, sptr[1]);
s2 = op(s2, sptr[2]); s3 = op(s3, sptr[3]);
}
D[i] = s0; D[i+1] = s1;
D[i+2] = s2; D[i+3] = s3;
}
#endif
for( ; i < width; i++ )
{
T s0 = kp[0][i];
for( k = 1; k < nz; k++ )
s0 = op(s0, kp[k][i]);
D[i] = s0;
}
}
}
std::vector<Point> coords;
std::vector<uchar*> ptrs;
VecOp vecOp;
};
}
namespace cv {
/////////////////////////////////// External Interface /////////////////////////////////////
cv::Ptr<cv::BaseRowFilter> cv::getMorphologyRowFilter(int op, int type, int ksize, int anchor)
Ptr<BaseRowFilter> getMorphologyRowFilter(int op, int type, int ksize, int anchor)
{
int depth = CV_MAT_DEPTH(type);
if( anchor < 0 )
anchor = ksize/2;
CV_Assert( op == MORPH_ERODE || op == MORPH_DILATE );
if( op == MORPH_ERODE )
{
if( depth == CV_8U )
return makePtr<MorphRowFilter<MinOp<uchar>,
ErodeRowVec8u> >(ksize, anchor);
if( depth == CV_16U )
return makePtr<MorphRowFilter<MinOp<ushort>,
ErodeRowVec16u> >(ksize, anchor);
if( depth == CV_16S )
return makePtr<MorphRowFilter<MinOp<short>,
ErodeRowVec16s> >(ksize, anchor);
if( depth == CV_32F )
return makePtr<MorphRowFilter<MinOp<float>,
ErodeRowVec32f> >(ksize, anchor);
if( depth == CV_64F )
return makePtr<MorphRowFilter<MinOp<double>,
ErodeRowVec64f> >(ksize, anchor);
}
else
{
if( depth == CV_8U )
return makePtr<MorphRowFilter<MaxOp<uchar>,
DilateRowVec8u> >(ksize, anchor);
if( depth == CV_16U )
return makePtr<MorphRowFilter<MaxOp<ushort>,
DilateRowVec16u> >(ksize, anchor);
if( depth == CV_16S )
return makePtr<MorphRowFilter<MaxOp<short>,
DilateRowVec16s> >(ksize, anchor);
if( depth == CV_32F )
return makePtr<MorphRowFilter<MaxOp<float>,
DilateRowVec32f> >(ksize, anchor);
if( depth == CV_64F )
return makePtr<MorphRowFilter<MaxOp<double>,
DilateRowVec64f> >(ksize, anchor);
CV_INSTRUMENT_REGION();
CV_CPU_DISPATCH(getMorphologyRowFilter, (op, type, ksize, anchor),
CV_CPU_DISPATCH_MODES_ALL);
}
CV_Error_( CV_StsNotImplemented, ("Unsupported data type (=%d)", type));
}
Ptr<BaseColumnFilter> getMorphologyColumnFilter(int op, int type, int ksize, int anchor)
{
CV_INSTRUMENT_REGION();
cv::Ptr<cv::BaseColumnFilter> cv::getMorphologyColumnFilter(int op, int type, int ksize, int anchor)
{
int depth = CV_MAT_DEPTH(type);
if( anchor < 0 )
anchor = ksize/2;
CV_Assert( op == MORPH_ERODE || op == MORPH_DILATE );
if( op == MORPH_ERODE )
{
if( depth == CV_8U )
return makePtr<MorphColumnFilter<MinOp<uchar>,
ErodeColumnVec8u> >(ksize, anchor);
if( depth == CV_16U )
return makePtr<MorphColumnFilter<MinOp<ushort>,
ErodeColumnVec16u> >(ksize, anchor);
if( depth == CV_16S )
return makePtr<MorphColumnFilter<MinOp<short>,
ErodeColumnVec16s> >(ksize, anchor);
if( depth == CV_32F )
return makePtr<MorphColumnFilter<MinOp<float>,
ErodeColumnVec32f> >(ksize, anchor);
if( depth == CV_64F )
return makePtr<MorphColumnFilter<MinOp<double>,
ErodeColumnVec64f> >(ksize, anchor);
}
else
{
if( depth == CV_8U )
return makePtr<MorphColumnFilter<MaxOp<uchar>,
DilateColumnVec8u> >(ksize, anchor);
if( depth == CV_16U )
return makePtr<MorphColumnFilter<MaxOp<ushort>,
DilateColumnVec16u> >(ksize, anchor);
if( depth == CV_16S )
return makePtr<MorphColumnFilter<MaxOp<short>,
DilateColumnVec16s> >(ksize, anchor);
if( depth == CV_32F )
return makePtr<MorphColumnFilter<MaxOp<float>,
DilateColumnVec32f> >(ksize, anchor);
if( depth == CV_64F )
return makePtr<MorphColumnFilter<MaxOp<double>,
DilateColumnVec64f> >(ksize, anchor);
}
CV_Error_( CV_StsNotImplemented, ("Unsupported data type (=%d)", type));
CV_CPU_DISPATCH(getMorphologyColumnFilter, (op, type, ksize, anchor),
CV_CPU_DISPATCH_MODES_ALL);
}
cv::Ptr<cv::BaseFilter> cv::getMorphologyFilter(int op, int type, InputArray _kernel, Point anchor)
Ptr<BaseFilter> getMorphologyFilter(int op, int type, InputArray _kernel, Point anchor)
{
CV_INSTRUMENT_REGION();
Mat kernel = _kernel.getMat();
int depth = CV_MAT_DEPTH(type);
anchor = normalizeAnchor(anchor, kernel.size());
CV_Assert( op == MORPH_ERODE || op == MORPH_DILATE );
if( op == MORPH_ERODE )
{
if( depth == CV_8U )
return makePtr<MorphFilter<MinOp<uchar>, ErodeVec8u> >(kernel, anchor);
if( depth == CV_16U )
return makePtr<MorphFilter<MinOp<ushort>, ErodeVec16u> >(kernel, anchor);
if( depth == CV_16S )
return makePtr<MorphFilter<MinOp<short>, ErodeVec16s> >(kernel, anchor);
if( depth == CV_32F )
return makePtr<MorphFilter<MinOp<float>, ErodeVec32f> >(kernel, anchor);
if( depth == CV_64F )
return makePtr<MorphFilter<MinOp<double>, ErodeVec64f> >(kernel, anchor);
}
else
{
if( depth == CV_8U )
return makePtr<MorphFilter<MaxOp<uchar>, DilateVec8u> >(kernel, anchor);
if( depth == CV_16U )
return makePtr<MorphFilter<MaxOp<ushort>, DilateVec16u> >(kernel, anchor);
if( depth == CV_16S )
return makePtr<MorphFilter<MaxOp<short>, DilateVec16s> >(kernel, anchor);
if( depth == CV_32F )
return makePtr<MorphFilter<MaxOp<float>, DilateVec32f> >(kernel, anchor);
if( depth == CV_64F )
return makePtr<MorphFilter<MaxOp<double>, DilateVec64f> >(kernel, anchor);
}
CV_Error_( CV_StsNotImplemented, ("Unsupported data type (=%d)", type));
CV_CPU_DISPATCH(getMorphologyFilter, (op, type, kernel, anchor),
CV_CPU_DISPATCH_MODES_ALL);
}
cv::Ptr<cv::FilterEngine> cv::createMorphologyFilter( int op, int type, InputArray _kernel,
Ptr<FilterEngine> createMorphologyFilter(
int op, int type, InputArray _kernel,
Point anchor, int _rowBorderType, int _columnBorderType,
const Scalar& _borderValue)
{
@ -862,7 +132,7 @@ cv::Ptr<cv::FilterEngine> cv::createMorphologyFilter( int op, int type, InputArr
}
cv::Mat cv::getStructuringElement(int shape, Size ksize, Point anchor)
Mat getStructuringElement(int shape, Size ksize, Point anchor)
{
int i, j;
int r = 0, c = 0;
@ -915,9 +185,6 @@ cv::Mat cv::getStructuringElement(int shape, Size ksize, Point anchor)
return elem;
}
namespace cv
{
// ===== 1. replacement implementation
static bool halMorph(int op, int src_type, int dst_type,
@ -1732,9 +999,7 @@ static void morphOp( int op, InputArray _src, OutputArray _dst,
(src.isSubmatrix() && !isolated));
}
}
void cv::erode( InputArray src, OutputArray dst, InputArray kernel,
void erode( InputArray src, OutputArray dst, InputArray kernel,
Point anchor, int iterations,
int borderType, const Scalar& borderValue )
{
@ -1744,7 +1009,7 @@ void cv::erode( InputArray src, OutputArray dst, InputArray kernel,
}
void cv::dilate( InputArray src, OutputArray dst, InputArray kernel,
void dilate( InputArray src, OutputArray dst, InputArray kernel,
Point anchor, int iterations,
int borderType, const Scalar& borderValue )
{
@ -1755,8 +1020,6 @@ void cv::dilate( InputArray src, OutputArray dst, InputArray kernel,
#ifdef HAVE_OPENCL
namespace cv {
static bool ocl_morphologyEx(InputArray _src, OutputArray _dst, int op,
InputArray kernel, Point anchor, int iterations,
int borderType, const Scalar& borderValue)
@ -1813,13 +1076,11 @@ static bool ocl_morphologyEx(InputArray _src, OutputArray _dst, int op,
return true;
}
}
#endif
#define IPP_DISABLE_MORPH_ADV 1
#if 0 //defined HAVE_IPP
#if !IPP_DISABLE_MORPH_ADV
namespace cv {
static bool ipp_morphologyEx(int op, InputArray _src, OutputArray _dst,
InputArray _kernel,
Point anchor, int iterations,
@ -1884,11 +1145,10 @@ static bool ipp_morphologyEx(int op, InputArray _src, OutputArray _dst,
return false;
#endif
}
}
#endif
#endif
void cv::morphologyEx( InputArray _src, OutputArray _dst, int op,
void morphologyEx( InputArray _src, OutputArray _dst, int op,
InputArray _kernel, Point anchor, int iterations,
int borderType, const Scalar& borderValue )
{
@ -1985,6 +1245,8 @@ void cv::morphologyEx( InputArray _src, OutputArray _dst, int op,
}
}
} // namespace cv
CV_IMPL IplConvKernel *
cvCreateStructuringElementEx( int cols, int rows,
int anchorX, int anchorY,

846
modules/imgproc/src/morph.simd.hpp Normal file
View File

@ -0,0 +1,846 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#include <limits.h>
#include "opencv2/core/hal/intrin.hpp"
/****************************************************************************************\
Basic Morphological Operations: Erosion & Dilation
\****************************************************************************************/
namespace cv {
CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
// forward declarations
Ptr<BaseRowFilter> getMorphologyRowFilter(int op, int type, int ksize, int anchor);
Ptr<BaseColumnFilter> getMorphologyColumnFilter(int op, int type, int ksize, int anchor);
Ptr<BaseFilter> getMorphologyFilter(int op, int type, const Mat& kernel, Point anchor);
#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
namespace {
template<typename T> struct MinOp
{
typedef T type1;
typedef T type2;
typedef T rtype;
T operator ()(const T a, const T b) const { return std::min(a, b); }
};
template<typename T> struct MaxOp
{
typedef T type1;
typedef T type2;
typedef T rtype;
T operator ()(const T a, const T b) const { return std::max(a, b); }
};
#if !defined(CV_SIMD) // min/max operation are usually fast enough (without using of control flow 'if' statements)
#undef CV_MIN_8U
#undef CV_MAX_8U
#define CV_MIN_8U(a,b) ((a) - CV_FAST_CAST_8U((a) - (b)))
#define CV_MAX_8U(a,b) ((a) + CV_FAST_CAST_8U((b) - (a)))
template<> inline uchar MinOp<uchar>::operator ()(const uchar a, const uchar b) const { return CV_MIN_8U(a, b); }
template<> inline uchar MaxOp<uchar>::operator ()(const uchar a, const uchar b) const { return CV_MAX_8U(a, b); }
#endif
struct MorphRowNoVec
{
MorphRowNoVec(int, int) {}
int operator()(const uchar*, uchar*, int, int) const { return 0; }
};
struct MorphColumnNoVec
{
MorphColumnNoVec(int, int) {}
int operator()(const uchar**, uchar*, int, int, int) const { return 0; }
};
struct MorphNoVec
{
int operator()(uchar**, int, uchar*, int) const { return 0; }
};
#if CV_SIMD
template<class VecUpdate> struct MorphRowVec
{
typedef typename VecUpdate::vtype vtype;
typedef typename vtype::lane_type stype;
MorphRowVec(int _ksize, int _anchor) : ksize(_ksize), anchor(_anchor) {}
int operator()(const uchar* src, uchar* dst, int width, int cn) const
{
CV_INSTRUMENT_REGION();
int i, k, _ksize = ksize*cn;
width *= cn;
VecUpdate updateOp;
for( i = 0; i <= width - 4*vtype::nlanes; i += 4*vtype::nlanes )
{
vtype s0 = vx_load((const stype*)src + i);
vtype s1 = vx_load((const stype*)src + i + vtype::nlanes);
vtype s2 = vx_load((const stype*)src + i + 2*vtype::nlanes);
vtype s3 = vx_load((const stype*)src + i + 3*vtype::nlanes);
for (k = cn; k < _ksize; k += cn)
{
s0 = updateOp(s0, vx_load((const stype*)src + i + k));
s1 = updateOp(s1, vx_load((const stype*)src + i + k + vtype::nlanes));
s2 = updateOp(s2, vx_load((const stype*)src + i + k + 2*vtype::nlanes));
s3 = updateOp(s3, vx_load((const stype*)src + i + k + 3*vtype::nlanes));
}
v_store((stype*)dst + i, s0);
v_store((stype*)dst + i + vtype::nlanes, s1);
v_store((stype*)dst + i + 2*vtype::nlanes, s2);
v_store((stype*)dst + i + 3*vtype::nlanes, s3);
}
if( i <= width - 2*vtype::nlanes )
{
vtype s0 = vx_load((const stype*)src + i);
vtype s1 = vx_load((const stype*)src + i + vtype::nlanes);
for( k = cn; k < _ksize; k += cn )
{
s0 = updateOp(s0, vx_load((const stype*)src + i + k));
s1 = updateOp(s1, vx_load((const stype*)src + i + k + vtype::nlanes));
}
v_store((stype*)dst + i, s0);
v_store((stype*)dst + i + vtype::nlanes, s1);
i += 2*vtype::nlanes;
}
if( i <= width - vtype::nlanes )
{
vtype s = vx_load((const stype*)src + i);
for( k = cn; k < _ksize; k += cn )
s = updateOp(s, vx_load((const stype*)src + i + k));
v_store((stype*)dst + i, s);
i += vtype::nlanes;
}
if( i <= width - vtype::nlanes/2 )
{
vtype s = vx_load_low((const stype*)src + i);
for( k = cn; k < _ksize; k += cn )
s = updateOp(s, vx_load_low((const stype*)src + i + k));
v_store_low((stype*)dst + i, s);
i += vtype::nlanes/2;
}
return i - i % cn;
}
int ksize, anchor;
};
template<class VecUpdate> struct MorphColumnVec
{
typedef typename VecUpdate::vtype vtype;
typedef typename vtype::lane_type stype;
MorphColumnVec(int _ksize, int _anchor) : ksize(_ksize), anchor(_anchor) {}
int operator()(const uchar** _src, uchar* _dst, int dststep, int count, int width) const
{
CV_INSTRUMENT_REGION();
int i = 0, k, _ksize = ksize;
VecUpdate updateOp;
for( i = 0; i < count + ksize - 1; i++ )
CV_Assert( ((size_t)_src[i] & (CV_SIMD_WIDTH-1)) == 0 );
const stype** src = (const stype**)_src;
stype* dst = (stype*)_dst;
dststep /= sizeof(dst[0]);
for( ; _ksize > 1 && count > 1; count -= 2, dst += dststep*2, src += 2 )
{
for( i = 0; i <= width - 4*vtype::nlanes; i += 4*vtype::nlanes)
{
const stype* sptr = src[1] + i;
vtype s0 = vx_load_aligned(sptr);
vtype s1 = vx_load_aligned(sptr + vtype::nlanes);
vtype s2 = vx_load_aligned(sptr + 2*vtype::nlanes);
vtype s3 = vx_load_aligned(sptr + 3*vtype::nlanes);
for( k = 2; k < _ksize; k++ )
{
sptr = src[k] + i;
s0 = updateOp(s0, vx_load_aligned(sptr));
s1 = updateOp(s1, vx_load_aligned(sptr + vtype::nlanes));
s2 = updateOp(s2, vx_load_aligned(sptr + 2*vtype::nlanes));
s3 = updateOp(s3, vx_load_aligned(sptr + 3*vtype::nlanes));
}
sptr = src[0] + i;
v_store(dst + i, updateOp(s0, vx_load_aligned(sptr)));
v_store(dst + i + vtype::nlanes, updateOp(s1, vx_load_aligned(sptr + vtype::nlanes)));
v_store(dst + i + 2*vtype::nlanes, updateOp(s2, vx_load_aligned(sptr + 2*vtype::nlanes)));
v_store(dst + i + 3*vtype::nlanes, updateOp(s3, vx_load_aligned(sptr + 3*vtype::nlanes)));
sptr = src[k] + i;
v_store(dst + dststep + i, updateOp(s0, vx_load_aligned(sptr)));
v_store(dst + dststep + i + vtype::nlanes, updateOp(s1, vx_load_aligned(sptr + vtype::nlanes)));
v_store(dst + dststep + i + 2*vtype::nlanes, updateOp(s2, vx_load_aligned(sptr + 2*vtype::nlanes)));
v_store(dst + dststep + i + 3*vtype::nlanes, updateOp(s3, vx_load_aligned(sptr + 3*vtype::nlanes)));
}
if( i <= width - 2*vtype::nlanes )
{
const stype* sptr = src[1] + i;
vtype s0 = vx_load_aligned(sptr);
vtype s1 = vx_load_aligned(sptr + vtype::nlanes);
for( k = 2; k < _ksize; k++ )
{
sptr = src[k] + i;
s0 = updateOp(s0, vx_load_aligned(sptr));
s1 = updateOp(s1, vx_load_aligned(sptr + vtype::nlanes));
}
sptr = src[0] + i;
v_store(dst + i, updateOp(s0, vx_load_aligned(sptr)));
v_store(dst + i + vtype::nlanes, updateOp(s1, vx_load_aligned(sptr + vtype::nlanes)));
sptr = src[k] + i;
v_store(dst + dststep + i, updateOp(s0, vx_load_aligned(sptr)));
v_store(dst + dststep + i + vtype::nlanes, updateOp(s1, vx_load_aligned(sptr + vtype::nlanes)));
i += 2*vtype::nlanes;
}
if( i <= width - vtype::nlanes )
{
vtype s0 = vx_load_aligned(src[1] + i);
for( k = 2; k < _ksize; k++ )
s0 = updateOp(s0, vx_load_aligned(src[k] + i));
v_store(dst + i, updateOp(s0, vx_load_aligned(src[0] + i)));
v_store(dst + dststep + i, updateOp(s0, vx_load_aligned(src[k] + i)));
i += vtype::nlanes;
}
if( i <= width - vtype::nlanes/2 )
{
vtype s0 = vx_load_low(src[1] + i);
for( k = 2; k < _ksize; k++ )
s0 = updateOp(s0, vx_load_low(src[k] + i));
v_store_low(dst + i, updateOp(s0, vx_load_low(src[0] + i)));
v_store_low(dst + dststep + i, updateOp(s0, vx_load_low(src[k] + i)));
i += vtype::nlanes/2;
}
}
for( ; count > 0; count--, dst += dststep, src++ )
{
for( i = 0; i <= width - 4*vtype::nlanes; i += 4*vtype::nlanes)
{
const stype* sptr = src[0] + i;
vtype s0 = vx_load_aligned(sptr);
vtype s1 = vx_load_aligned(sptr + vtype::nlanes);
vtype s2 = vx_load_aligned(sptr + 2*vtype::nlanes);
vtype s3 = vx_load_aligned(sptr + 3*vtype::nlanes);
for( k = 1; k < _ksize; k++ )
{
sptr = src[k] + i;
s0 = updateOp(s0, vx_load_aligned(sptr));
s1 = updateOp(s1, vx_load_aligned(sptr + vtype::nlanes));
s2 = updateOp(s2, vx_load_aligned(sptr + 2*vtype::nlanes));
s3 = updateOp(s3, vx_load_aligned(sptr + 3*vtype::nlanes));
}
v_store(dst + i, s0);
v_store(dst + i + vtype::nlanes, s1);
v_store(dst + i + 2*vtype::nlanes, s2);
v_store(dst + i + 3*vtype::nlanes, s3);
}
if( i <= width - 2*vtype::nlanes )
{
const stype* sptr = src[0] + i;
vtype s0 = vx_load_aligned(sptr);
vtype s1 = vx_load_aligned(sptr + vtype::nlanes);
for( k = 1; k < _ksize; k++ )
{
sptr = src[k] + i;
s0 = updateOp(s0, vx_load_aligned(sptr));
s1 = updateOp(s1, vx_load_aligned(sptr + vtype::nlanes));
}
v_store(dst + i, s0);
v_store(dst + i + vtype::nlanes, s1);
i += 2*vtype::nlanes;
}
if( i <= width - vtype::nlanes )
{
vtype s0 = vx_load_aligned(src[0] + i);
for( k = 1; k < _ksize; k++ )
s0 = updateOp(s0, vx_load_aligned(src[k] + i));
v_store(dst + i, s0);
i += vtype::nlanes;
}
if( i <= width - vtype::nlanes/2 )
{
vtype s0 = vx_load_low(src[0] + i);
for( k = 1; k < _ksize; k++ )
s0 = updateOp(s0, vx_load_low(src[k] + i));
v_store_low(dst + i, s0);
i += vtype::nlanes/2;
}
}
return i;
}
int ksize, anchor;
};
template<class VecUpdate> struct MorphVec
{
typedef typename VecUpdate::vtype vtype;
typedef typename vtype::lane_type stype;
int operator()(uchar** _src, int nz, uchar* _dst, int width) const
{
CV_INSTRUMENT_REGION();
const stype** src = (const stype**)_src;
stype* dst = (stype*)_dst;
int i, k;
VecUpdate updateOp;
for( i = 0; i <= width - 4*vtype::nlanes; i += 4*vtype::nlanes )
{
const stype* sptr = src[0] + i;
vtype s0 = vx_load(sptr);
vtype s1 = vx_load(sptr + vtype::nlanes);
vtype s2 = vx_load(sptr + 2*vtype::nlanes);
vtype s3 = vx_load(sptr + 3*vtype::nlanes);
for( k = 1; k < nz; k++ )
{
sptr = src[k] + i;
s0 = updateOp(s0, vx_load(sptr));
s1 = updateOp(s1, vx_load(sptr + vtype::nlanes));
s2 = updateOp(s2, vx_load(sptr + 2*vtype::nlanes));
s3 = updateOp(s3, vx_load(sptr + 3*vtype::nlanes));
}
v_store(dst + i, s0);
v_store(dst + i + vtype::nlanes, s1);
v_store(dst + i + 2*vtype::nlanes, s2);
v_store(dst + i + 3*vtype::nlanes, s3);
}
if( i <= width - 2*vtype::nlanes )
{
const stype* sptr = src[0] + i;
vtype s0 = vx_load(sptr);
vtype s1 = vx_load(sptr + vtype::nlanes);
for( k = 1; k < nz; k++ )
{
sptr = src[k] + i;
s0 = updateOp(s0, vx_load(sptr));
s1 = updateOp(s1, vx_load(sptr + vtype::nlanes));
}
v_store(dst + i, s0);
v_store(dst + i + vtype::nlanes, s1);
i += 2*vtype::nlanes;
}
if( i <= width - vtype::nlanes )
{
vtype s0 = vx_load(src[0] + i);
for( k = 1; k < nz; k++ )
s0 = updateOp(s0, vx_load(src[k] + i));
v_store(dst + i, s0);
i += vtype::nlanes;
}
if( i <= width - vtype::nlanes/2 )
{
vtype s0 = vx_load_low(src[0] + i);
for( k = 1; k < nz; k++ )
s0 = updateOp(s0, vx_load_low(src[k] + i));
v_store_low(dst + i, s0);
i += vtype::nlanes/2;
}
return i;
}
};
template <typename T> struct VMin
{
typedef T vtype;
vtype operator()(const vtype& a, const vtype& b) const { return v_min(a,b); }
};
template <typename T> struct VMax
{
typedef T vtype;
vtype operator()(const vtype& a, const vtype& b) const { return v_max(a,b); }
};
typedef MorphRowVec<VMin<v_uint8> > ErodeRowVec8u;
typedef MorphRowVec<VMax<v_uint8> > DilateRowVec8u;
typedef MorphRowVec<VMin<v_uint16> > ErodeRowVec16u;
typedef MorphRowVec<VMax<v_uint16> > DilateRowVec16u;
typedef MorphRowVec<VMin<v_int16> > ErodeRowVec16s;
typedef MorphRowVec<VMax<v_int16> > DilateRowVec16s;
typedef MorphRowVec<VMin<v_float32> > ErodeRowVec32f;
typedef MorphRowVec<VMax<v_float32> > DilateRowVec32f;
typedef MorphColumnVec<VMin<v_uint8> > ErodeColumnVec8u;
typedef MorphColumnVec<VMax<v_uint8> > DilateColumnVec8u;
typedef MorphColumnVec<VMin<v_uint16> > ErodeColumnVec16u;
typedef MorphColumnVec<VMax<v_uint16> > DilateColumnVec16u;
typedef MorphColumnVec<VMin<v_int16> > ErodeColumnVec16s;
typedef MorphColumnVec<VMax<v_int16> > DilateColumnVec16s;
typedef MorphColumnVec<VMin<v_float32> > ErodeColumnVec32f;
typedef MorphColumnVec<VMax<v_float32> > DilateColumnVec32f;
typedef MorphVec<VMin<v_uint8> > ErodeVec8u;
typedef MorphVec<VMax<v_uint8> > DilateVec8u;
typedef MorphVec<VMin<v_uint16> > ErodeVec16u;
typedef MorphVec<VMax<v_uint16> > DilateVec16u;
typedef MorphVec<VMin<v_int16> > ErodeVec16s;
typedef MorphVec<VMax<v_int16> > DilateVec16s;
typedef MorphVec<VMin<v_float32> > ErodeVec32f;
typedef MorphVec<VMax<v_float32> > DilateVec32f;
#else
typedef MorphRowNoVec ErodeRowVec8u;
typedef MorphRowNoVec DilateRowVec8u;
typedef MorphColumnNoVec ErodeColumnVec8u;
typedef MorphColumnNoVec DilateColumnVec8u;
typedef MorphRowNoVec ErodeRowVec16u;
typedef MorphRowNoVec DilateRowVec16u;
typedef MorphRowNoVec ErodeRowVec16s;
typedef MorphRowNoVec DilateRowVec16s;
typedef MorphRowNoVec ErodeRowVec32f;
typedef MorphRowNoVec DilateRowVec32f;
typedef MorphColumnNoVec ErodeColumnVec16u;
typedef MorphColumnNoVec DilateColumnVec16u;
typedef MorphColumnNoVec ErodeColumnVec16s;
typedef MorphColumnNoVec DilateColumnVec16s;
typedef MorphColumnNoVec ErodeColumnVec32f;
typedef MorphColumnNoVec DilateColumnVec32f;
typedef MorphNoVec ErodeVec8u;
typedef MorphNoVec DilateVec8u;
typedef MorphNoVec ErodeVec16u;
typedef MorphNoVec DilateVec16u;
typedef MorphNoVec ErodeVec16s;
typedef MorphNoVec DilateVec16s;
typedef MorphNoVec ErodeVec32f;
typedef MorphNoVec DilateVec32f;
#endif
typedef MorphRowNoVec ErodeRowVec64f;
typedef MorphRowNoVec DilateRowVec64f;
typedef MorphColumnNoVec ErodeColumnVec64f;
typedef MorphColumnNoVec DilateColumnVec64f;
typedef MorphNoVec ErodeVec64f;
typedef MorphNoVec DilateVec64f;
template<class Op, class VecOp> struct MorphRowFilter : public BaseRowFilter
{
typedef typename Op::rtype T;
MorphRowFilter( int _ksize, int _anchor ) : vecOp(_ksize, _anchor)
{
ksize = _ksize;
anchor = _anchor;
}
void operator()(const uchar* src, uchar* dst, int width, int cn) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int i, j, k, _ksize = ksize*cn;
const T* S = (const T*)src;
Op op;
T* D = (T*)dst;
if( _ksize == cn )
{
for( i = 0; i < width*cn; i++ )
D[i] = S[i];
return;
}
int i0 = vecOp(src, dst, width, cn);
width *= cn;
for( k = 0; k < cn; k++, S++, D++ )
{
for( i = i0; i <= width - cn*2; i += cn*2 )
{
const T* s = S + i;
T m = s[cn];
for( j = cn*2; j < _ksize; j += cn )
m = op(m, s[j]);
D[i] = op(m, s[0]);
D[i+cn] = op(m, s[j]);
}
for( ; i < width; i += cn )
{
const T* s = S + i;
T m = s[0];
for( j = cn; j < _ksize; j += cn )
m = op(m, s[j]);
D[i] = m;
}
}
}
VecOp vecOp;
};
template<class Op, class VecOp> struct MorphColumnFilter : public BaseColumnFilter
{
typedef typename Op::rtype T;
MorphColumnFilter( int _ksize, int _anchor ) : vecOp(_ksize, _anchor)
{
ksize = _ksize;
anchor = _anchor;
}
void operator()(const uchar** _src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int i, k, _ksize = ksize;
const T** src = (const T**)_src;
T* D = (T*)dst;
Op op;
int i0 = vecOp(_src, dst, dststep, count, width);
dststep /= sizeof(D[0]);
for( ; _ksize > 1 && count > 1; count -= 2, D += dststep*2, src += 2 )
{
i = i0;
#if CV_ENABLE_UNROLLED
for( ; i <= width - 4; i += 4 )
{
const T* sptr = src[1] + i;
T s0 = sptr[0], s1 = sptr[1], s2 = sptr[2], s3 = sptr[3];
for( k = 2; k < _ksize; k++ )
{
sptr = src[k] + i;
s0 = op(s0, sptr[0]); s1 = op(s1, sptr[1]);
s2 = op(s2, sptr[2]); s3 = op(s3, sptr[3]);
}
sptr = src[0] + i;
D[i] = op(s0, sptr[0]);
D[i+1] = op(s1, sptr[1]);
D[i+2] = op(s2, sptr[2]);
D[i+3] = op(s3, sptr[3]);
sptr = src[k] + i;
D[i+dststep] = op(s0, sptr[0]);
D[i+dststep+1] = op(s1, sptr[1]);
D[i+dststep+2] = op(s2, sptr[2]);
D[i+dststep+3] = op(s3, sptr[3]);
}
#endif
for( ; i < width; i++ )
{
T s0 = src[1][i];
for( k = 2; k < _ksize; k++ )
s0 = op(s0, src[k][i]);
D[i] = op(s0, src[0][i]);
D[i+dststep] = op(s0, src[k][i]);
}
}
for( ; count > 0; count--, D += dststep, src++ )
{
i = i0;
#if CV_ENABLE_UNROLLED
for( ; i <= width - 4; i += 4 )
{
const T* sptr = src[0] + i;
T s0 = sptr[0], s1 = sptr[1], s2 = sptr[2], s3 = sptr[3];
for( k = 1; k < _ksize; k++ )
{
sptr = src[k] + i;
s0 = op(s0, sptr[0]); s1 = op(s1, sptr[1]);
s2 = op(s2, sptr[2]); s3 = op(s3, sptr[3]);
}
D[i] = s0; D[i+1] = s1;
D[i+2] = s2; D[i+3] = s3;
}
#endif
for( ; i < width; i++ )
{
T s0 = src[0][i];
for( k = 1; k < _ksize; k++ )
s0 = op(s0, src[k][i]);
D[i] = s0;
}
}
}
VecOp vecOp;
};
template<class Op, class VecOp> struct MorphFilter : BaseFilter
{
typedef typename Op::rtype T;
MorphFilter( const Mat& _kernel, Point _anchor )
{
anchor = _anchor;
ksize = _kernel.size();
CV_Assert( _kernel.type() == CV_8U );
std::vector<uchar> coeffs; // we do not really the values of non-zero
// kernel elements, just their locations
preprocess2DKernel( _kernel, coords, coeffs );
ptrs.resize( coords.size() );
}
void operator()(const uchar** src, uchar* dst, int dststep, int count, int width, int cn) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
const Point* pt = &coords[0];
const T** kp = (const T**)&ptrs[0];
int i, k, nz = (int)coords.size();
Op op;
width *= cn;
for( ; count > 0; count--, dst += dststep, src++ )
{
T* D = (T*)dst;
for( k = 0; k < nz; k++ )
kp[k] = (const T*)src[pt[k].y] + pt[k].x*cn;
i = vecOp(&ptrs[0], nz, dst, width);
#if CV_ENABLE_UNROLLED
for( ; i <= width - 4; i += 4 )
{
const T* sptr = kp[0] + i;
T s0 = sptr[0], s1 = sptr[1], s2 = sptr[2], s3 = sptr[3];
for( k = 1; k < nz; k++ )
{
sptr = kp[k] + i;
s0 = op(s0, sptr[0]); s1 = op(s1, sptr[1]);
s2 = op(s2, sptr[2]); s3 = op(s3, sptr[3]);
}
D[i] = s0; D[i+1] = s1;
D[i+2] = s2; D[i+3] = s3;
}
#endif
for( ; i < width; i++ )
{
T s0 = kp[0][i];
for( k = 1; k < nz; k++ )
s0 = op(s0, kp[k][i]);
D[i] = s0;
}
}
}
std::vector<Point> coords;
std::vector<uchar*> ptrs;
VecOp vecOp;
};
} // namespace anon
/////////////////////////////////// External Interface /////////////////////////////////////
Ptr<BaseRowFilter> getMorphologyRowFilter(int op, int type, int ksize, int anchor)
{
CV_INSTRUMENT_REGION();
int depth = CV_MAT_DEPTH(type);
if( anchor < 0 )
anchor = ksize/2;
CV_Assert( op == MORPH_ERODE || op == MORPH_DILATE );
if( op == MORPH_ERODE )
{
if( depth == CV_8U )
return makePtr<MorphRowFilter<MinOp<uchar>,
ErodeRowVec8u> >(ksize, anchor);
if( depth == CV_16U )
return makePtr<MorphRowFilter<MinOp<ushort>,
ErodeRowVec16u> >(ksize, anchor);
if( depth == CV_16S )
return makePtr<MorphRowFilter<MinOp<short>,
ErodeRowVec16s> >(ksize, anchor);
if( depth == CV_32F )
return makePtr<MorphRowFilter<MinOp<float>,
ErodeRowVec32f> >(ksize, anchor);
if( depth == CV_64F )
return makePtr<MorphRowFilter<MinOp<double>,
ErodeRowVec64f> >(ksize, anchor);
}
else
{
if( depth == CV_8U )
return makePtr<MorphRowFilter<MaxOp<uchar>,
DilateRowVec8u> >(ksize, anchor);
if( depth == CV_16U )
return makePtr<MorphRowFilter<MaxOp<ushort>,
DilateRowVec16u> >(ksize, anchor);
if( depth == CV_16S )
return makePtr<MorphRowFilter<MaxOp<short>,
DilateRowVec16s> >(ksize, anchor);
if( depth == CV_32F )
return makePtr<MorphRowFilter<MaxOp<float>,
DilateRowVec32f> >(ksize, anchor);
if( depth == CV_64F )
return makePtr<MorphRowFilter<MaxOp<double>,
DilateRowVec64f> >(ksize, anchor);
}
CV_Error_( CV_StsNotImplemented, ("Unsupported data type (=%d)", type));
}
Ptr<BaseColumnFilter> getMorphologyColumnFilter(int op, int type, int ksize, int anchor)
{
CV_INSTRUMENT_REGION();
int depth = CV_MAT_DEPTH(type);
if( anchor < 0 )
anchor = ksize/2;
CV_Assert( op == MORPH_ERODE || op == MORPH_DILATE );
if( op == MORPH_ERODE )
{
if( depth == CV_8U )
return makePtr<MorphColumnFilter<MinOp<uchar>,
ErodeColumnVec8u> >(ksize, anchor);
if( depth == CV_16U )
return makePtr<MorphColumnFilter<MinOp<ushort>,
ErodeColumnVec16u> >(ksize, anchor);
if( depth == CV_16S )
return makePtr<MorphColumnFilter<MinOp<short>,
ErodeColumnVec16s> >(ksize, anchor);
if( depth == CV_32F )
return makePtr<MorphColumnFilter<MinOp<float>,
ErodeColumnVec32f> >(ksize, anchor);
if( depth == CV_64F )
return makePtr<MorphColumnFilter<MinOp<double>,
ErodeColumnVec64f> >(ksize, anchor);
}
else
{
if( depth == CV_8U )
return makePtr<MorphColumnFilter<MaxOp<uchar>,
DilateColumnVec8u> >(ksize, anchor);
if( depth == CV_16U )
return makePtr<MorphColumnFilter<MaxOp<ushort>,
DilateColumnVec16u> >(ksize, anchor);
if( depth == CV_16S )
return makePtr<MorphColumnFilter<MaxOp<short>,
DilateColumnVec16s> >(ksize, anchor);
if( depth == CV_32F )
return makePtr<MorphColumnFilter<MaxOp<float>,
DilateColumnVec32f> >(ksize, anchor);
if( depth == CV_64F )
return makePtr<MorphColumnFilter<MaxOp<double>,
DilateColumnVec64f> >(ksize, anchor);
}
CV_Error_( CV_StsNotImplemented, ("Unsupported data type (=%d)", type));
}
Ptr<BaseFilter> getMorphologyFilter(int op, int type, const Mat& kernel, Point anchor)
{
CV_INSTRUMENT_REGION();
int depth = CV_MAT_DEPTH(type);
anchor = normalizeAnchor(anchor, kernel.size());
CV_Assert( op == MORPH_ERODE || op == MORPH_DILATE );
if( op == MORPH_ERODE )
{
if( depth == CV_8U )
return makePtr<MorphFilter<MinOp<uchar>, ErodeVec8u> >(kernel, anchor);
if( depth == CV_16U )
return makePtr<MorphFilter<MinOp<ushort>, ErodeVec16u> >(kernel, anchor);
if( depth == CV_16S )
return makePtr<MorphFilter<MinOp<short>, ErodeVec16s> >(kernel, anchor);
if( depth == CV_32F )
return makePtr<MorphFilter<MinOp<float>, ErodeVec32f> >(kernel, anchor);
if( depth == CV_64F )
return makePtr<MorphFilter<MinOp<double>, ErodeVec64f> >(kernel, anchor);
}
else
{
if( depth == CV_8U )
return makePtr<MorphFilter<MaxOp<uchar>, DilateVec8u> >(kernel, anchor);
if( depth == CV_16U )
return makePtr<MorphFilter<MaxOp<ushort>, DilateVec16u> >(kernel, anchor);
if( depth == CV_16S )
return makePtr<MorphFilter<MaxOp<short>, DilateVec16s> >(kernel, anchor);
if( depth == CV_32F )
return makePtr<MorphFilter<MaxOp<float>, DilateVec32f> >(kernel, anchor);
if( depth == CV_64F )
return makePtr<MorphFilter<MaxOp<double>, DilateVec64f> >(kernel, anchor);
}
CV_Error_( CV_StsNotImplemented, ("Unsupported data type (=%d)", type));
}
#endif
CV_CPU_OPTIMIZATION_NAMESPACE_END
} // namespace

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2014-2015, Itseez Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#include <vector>
#include "opencv2/core/hal/intrin.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "opencv2/core/openvx/ovx_defs.hpp"
#include "filter.hpp"
#include "opencv2/core/softfloat.hpp"
namespace cv {
#include "fixedpoint.inl.hpp"
}
#include "smooth.simd.hpp"
#include "smooth.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
namespace cv {
/****************************************************************************************\
Gaussian Blur
\****************************************************************************************/
Mat getGaussianKernel(int n, double sigma, int ktype)
{
CV_Assert(n > 0);
const int SMALL_GAUSSIAN_SIZE = 7;
static const float small_gaussian_tab[][SMALL_GAUSSIAN_SIZE] =
{
{1.f},
{0.25f, 0.5f, 0.25f},
{0.0625f, 0.25f, 0.375f, 0.25f, 0.0625f},
{0.03125f, 0.109375f, 0.21875f, 0.28125f, 0.21875f, 0.109375f, 0.03125f}
};
const float* fixed_kernel = n % 2 == 1 && n <= SMALL_GAUSSIAN_SIZE && sigma <= 0 ?
small_gaussian_tab[n>>1] : 0;
CV_Assert( ktype == CV_32F || ktype == CV_64F );
Mat kernel(n, 1, ktype);
float* cf = kernel.ptr<float>();
double* cd = kernel.ptr<double>();
double sigmaX = sigma > 0 ? sigma : ((n-1)*0.5 - 1)*0.3 + 0.8;
double scale2X = -0.5/(sigmaX*sigmaX);
double sum = 0;
int i;
for( i = 0; i < n; i++ )
{
double x = i - (n-1)*0.5;
double t = fixed_kernel ? (double)fixed_kernel[i] : std::exp(scale2X*x*x);
if( ktype == CV_32F )
{
cf[i] = (float)t;
sum += cf[i];
}
else
{
cd[i] = t;
sum += cd[i];
}
}
CV_DbgAssert(fabs(sum) > 0);
sum = 1./sum;
for( i = 0; i < n; i++ )
{
if( ktype == CV_32F )
cf[i] = (float)(cf[i]*sum);
else
cd[i] *= sum;
}
return kernel;
}
template <typename T>
static std::vector<T> getFixedpointGaussianKernel( int n, double sigma )
{
if (sigma <= 0)
{
if(n == 1)
return std::vector<T>(1, softdouble(1.0));
else if(n == 3)
{
T v3[] = { softdouble(0.25), softdouble(0.5), softdouble(0.25) };
return std::vector<T>(v3, v3 + 3);
}
else if(n == 5)
{
T v5[] = { softdouble(0.0625), softdouble(0.25), softdouble(0.375), softdouble(0.25), softdouble(0.0625) };
return std::vector<T>(v5, v5 + 5);
}
else if(n == 7)
{
T v7[] = { softdouble(0.03125), softdouble(0.109375), softdouble(0.21875), softdouble(0.28125), softdouble(0.21875), softdouble(0.109375), softdouble(0.03125) };
return std::vector<T>(v7, v7 + 7);
}
}
softdouble sigmaX = sigma > 0 ? softdouble(sigma) : mulAdd(softdouble(n),softdouble(0.15),softdouble(0.35));// softdouble(((n-1)*0.5 - 1)*0.3 + 0.8)
softdouble scale2X = softdouble(-0.5*0.25)/(sigmaX*sigmaX);
std::vector<softdouble> values(n);
softdouble sum(0.);
for(int i = 0, x = 1 - n; i < n; i++, x+=2 )
{
// x = i - (n - 1)*0.5
// t = std::exp(scale2X*x*x)
values[i] = exp(softdouble(x*x)*scale2X);
sum += values[i];
}
sum = softdouble::one()/sum;
std::vector<T> kernel(n);
for(int i = 0; i < n; i++ )
{
kernel[i] = values[i] * sum;
}
return kernel;
};
static void getGaussianKernel(int n, double sigma, int ktype, Mat& res) { res = getGaussianKernel(n, sigma, ktype); }
template <typename T> static void getGaussianKernel(int n, double sigma, int, std::vector<T>& res) { res = getFixedpointGaussianKernel<T>(n, sigma); }
template <typename T>
static void createGaussianKernels( T & kx, T & ky, int type, Size &ksize,
double sigma1, double sigma2 )
{
int depth = CV_MAT_DEPTH(type);
if( sigma2 <= 0 )
sigma2 = sigma1;
// automatic detection of kernel size from sigma
if( ksize.width <= 0 && sigma1 > 0 )
ksize.width = cvRound(sigma1*(depth == CV_8U ? 3 : 4)*2 + 1)|1;
if( ksize.height <= 0 && sigma2 > 0 )
ksize.height = cvRound(sigma2*(depth == CV_8U ? 3 : 4)*2 + 1)|1;
CV_Assert( ksize.width > 0 && ksize.width % 2 == 1 &&
ksize.height > 0 && ksize.height % 2 == 1 );
sigma1 = std::max( sigma1, 0. );
sigma2 = std::max( sigma2, 0. );
getGaussianKernel( ksize.width, sigma1, std::max(depth, CV_32F), kx );
if( ksize.height == ksize.width && std::abs(sigma1 - sigma2) < DBL_EPSILON )
ky = kx;
else
getGaussianKernel( ksize.height, sigma2, std::max(depth, CV_32F), ky );
}
Ptr<FilterEngine> createGaussianFilter( int type, Size ksize,
double sigma1, double sigma2,
int borderType )
{
Mat kx, ky;
createGaussianKernels(kx, ky, type, ksize, sigma1, sigma2);
return createSeparableLinearFilter( type, type, kx, ky, Point(-1,-1), 0, borderType );
}
#ifdef HAVE_OPENCL
static bool ocl_GaussianBlur_8UC1(InputArray _src, OutputArray _dst, Size ksize, int ddepth,
InputArray _kernelX, InputArray _kernelY, int borderType)
{
const ocl::Device & dev = ocl::Device::getDefault();
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if ( !(dev.isIntel() && (type == CV_8UC1) &&
(_src.offset() == 0) && (_src.step() % 4 == 0) &&
((ksize.width == 5 && (_src.cols() % 4 == 0)) ||
(ksize.width == 3 && (_src.cols() % 16 == 0) && (_src.rows() % 2 == 0)))) )
return false;
Mat kernelX = _kernelX.getMat().reshape(1, 1);
if (kernelX.cols % 2 != 1)
return false;
Mat kernelY = _kernelY.getMat().reshape(1, 1);
if (kernelY.cols % 2 != 1)
return false;
if (ddepth < 0)
ddepth = sdepth;
Size size = _src.size();
size_t globalsize[2] = { 0, 0 };
size_t localsize[2] = { 0, 0 };
if (ksize.width == 3)
{
globalsize[0] = size.width / 16;
globalsize[1] = size.height / 2;
}
else if (ksize.width == 5)
{
globalsize[0] = size.width / 4;
globalsize[1] = size.height / 1;
}
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
char build_opts[1024];
sprintf(build_opts, "-D %s %s%s", borderMap[borderType & ~BORDER_ISOLATED],
ocl::kernelToStr(kernelX, CV_32F, "KERNEL_MATRIX_X").c_str(),
ocl::kernelToStr(kernelY, CV_32F, "KERNEL_MATRIX_Y").c_str());
ocl::Kernel kernel;
if (ksize.width == 3)
kernel.create("gaussianBlur3x3_8UC1_cols16_rows2", cv::ocl::imgproc::gaussianBlur3x3_oclsrc, build_opts);
else if (ksize.width == 5)
kernel.create("gaussianBlur5x5_8UC1_cols4", cv::ocl::imgproc::gaussianBlur5x5_oclsrc, build_opts);
if (kernel.empty())
return false;
UMat src = _src.getUMat();
_dst.create(size, CV_MAKETYPE(ddepth, cn));
if (!(_dst.offset() == 0 && _dst.step() % 4 == 0))
return false;
UMat dst = _dst.getUMat();
int idxArg = kernel.set(0, ocl::KernelArg::PtrReadOnly(src));
idxArg = kernel.set(idxArg, (int)src.step);
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst));
idxArg = kernel.set(idxArg, (int)dst.step);
idxArg = kernel.set(idxArg, (int)dst.rows);
idxArg = kernel.set(idxArg, (int)dst.cols);
return kernel.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false);
}
#endif
#ifdef HAVE_OPENVX
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_GAUSSIAN_3x3>(int w, int h) { return w*h < 320 * 240; }
}
static bool openvx_gaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
double sigma1, double sigma2, int borderType)
{
if (sigma2 <= 0)
sigma2 = sigma1;
// automatic detection of kernel size from sigma
if (ksize.width <= 0 && sigma1 > 0)
ksize.width = cvRound(sigma1*6 + 1) | 1;
if (ksize.height <= 0 && sigma2 > 0)
ksize.height = cvRound(sigma2*6 + 1) | 1;
if (_src.type() != CV_8UC1 ||
_src.cols() < 3 || _src.rows() < 3 ||
ksize.width != 3 || ksize.height != 3)
return false;
sigma1 = std::max(sigma1, 0.);
sigma2 = std::max(sigma2, 0.);
if (!(sigma1 == 0.0 || (sigma1 - 0.8) < DBL_EPSILON) || !(sigma2 == 0.0 || (sigma2 - 0.8) < DBL_EPSILON) ||
ovx::skipSmallImages<VX_KERNEL_GAUSSIAN_3x3>(_src.cols(), _src.rows()))
return false;
Mat src = _src.getMat();
Mat dst = _dst.getMat();
if ((borderType & BORDER_ISOLATED) == 0 && src.isSubmatrix())
return false; //Process isolated borders only
vx_enum border;
switch (borderType & ~BORDER_ISOLATED)
{
case BORDER_CONSTANT:
border = VX_BORDER_CONSTANT;
break;
case BORDER_REPLICATE:
border = VX_BORDER_REPLICATE;
break;
default:
return false;
}
try
{
ivx::Context ctx = ovx::getOpenVXContext();
Mat a;
if (dst.data != src.data)
a = src;
else
src.copyTo(a);
ivx::Image
ia = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(a.cols, a.rows, 1, (vx_int32)(a.step)), a.data),
ib = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(dst.cols, dst.rows, 1, (vx_int32)(dst.step)), dst.data);
//ATTENTION: VX_CONTEXT_IMMEDIATE_BORDER attribute change could lead to strange issues in multi-threaded environments
//since OpenVX standard says nothing about thread-safety for now
ivx::border_t prevBorder = ctx.immediateBorder();
ctx.setImmediateBorder(border, (vx_uint8)(0));
ivx::IVX_CHECK_STATUS(vxuGaussian3x3(ctx, ia, ib));
ctx.setImmediateBorder(prevBorder);
}
catch (const ivx::RuntimeError & e)
{
VX_DbgThrow(e.what());
}
catch (const ivx::WrapperError & e)
{
VX_DbgThrow(e.what());
}
return true;
}
#endif
#ifdef HAVE_IPP
// IW 2017u2 has bug which doesn't allow use of partial inMem with tiling
#if IPP_DISABLE_GAUSSIANBLUR_PARALLEL
#define IPP_GAUSSIANBLUR_PARALLEL 0
#else
#define IPP_GAUSSIANBLUR_PARALLEL 1
#endif
#ifdef HAVE_IPP_IW
class ipp_gaussianBlurParallel: public ParallelLoopBody
{
public:
ipp_gaussianBlurParallel(::ipp::IwiImage &src, ::ipp::IwiImage &dst, int kernelSize, float sigma, ::ipp::IwiBorderType &border, bool *pOk):
m_src(src), m_dst(dst), m_kernelSize(kernelSize), m_sigma(sigma), m_border(border), m_pOk(pOk) {
*m_pOk = true;
}
~ipp_gaussianBlurParallel()
{
}
virtual void operator() (const Range& range) const CV_OVERRIDE
{
CV_INSTRUMENT_REGION_IPP();
if(!*m_pOk)
return;
try
{
::ipp::IwiTile tile = ::ipp::IwiRoi(0, range.start, m_dst.m_size.width, range.end - range.start);
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterGaussian, m_src, m_dst, m_kernelSize, m_sigma, ::ipp::IwDefault(), m_border, tile);
}
catch(const ::ipp::IwException &)
{
*m_pOk = false;
return;
}
}
private:
::ipp::IwiImage &m_src;
::ipp::IwiImage &m_dst;
int m_kernelSize;
float m_sigma;
::ipp::IwiBorderType &m_border;
volatile bool *m_pOk;
const ipp_gaussianBlurParallel& operator= (const ipp_gaussianBlurParallel&);
};
#endif
static bool ipp_GaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
double sigma1, double sigma2, int borderType )
{
#ifdef HAVE_IPP_IW
CV_INSTRUMENT_REGION_IPP();
#if IPP_VERSION_X100 < 201800 && ((defined _MSC_VER && defined _M_IX86) || (defined __GNUC__ && defined __i386__))
CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(ksize); CV_UNUSED(sigma1); CV_UNUSED(sigma2); CV_UNUSED(borderType);
return false; // bug on ia32
#else
if(sigma1 != sigma2)
return false;
if(sigma1 < FLT_EPSILON)
return false;
if(ksize.width != ksize.height)
return false;
// Acquire data and begin processing
try
{
Mat src = _src.getMat();
Mat dst = _dst.getMat();
::ipp::IwiImage iwSrc = ippiGetImage(src);
::ipp::IwiImage iwDst = ippiGetImage(dst);
::ipp::IwiBorderSize borderSize = ::ipp::iwiSizeToBorderSize(ippiGetSize(ksize));
::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize));
if(!ippBorder)
return false;
const int threads = ippiSuggestThreadsNum(iwDst, 2);
if(IPP_GAUSSIANBLUR_PARALLEL && threads > 1) {
bool ok;
ipp_gaussianBlurParallel invoker(iwSrc, iwDst, ksize.width, (float) sigma1, ippBorder, &ok);
if(!ok)
return false;
const Range range(0, (int) iwDst.m_size.height);
parallel_for_(range, invoker, threads*4);
if(!ok)
return false;
} else {
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterGaussian, iwSrc, iwDst, ksize.width, sigma1, ::ipp::IwDefault(), ippBorder);
}
}
catch (const ::ipp::IwException &)
{
return false;
}
return true;
#endif
#else
CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(ksize); CV_UNUSED(sigma1); CV_UNUSED(sigma2); CV_UNUSED(borderType);
return false;
#endif
}
#endif
void GaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
double sigma1, double sigma2,
int borderType)
{
CV_INSTRUMENT_REGION();
int type = _src.type();
Size size = _src.size();
_dst.create( size, type );
if( (borderType & ~BORDER_ISOLATED) != BORDER_CONSTANT &&
((borderType & BORDER_ISOLATED) != 0 || !_src.getMat().isSubmatrix()) )
{
if( size.height == 1 )
ksize.height = 1;
if( size.width == 1 )
ksize.width = 1;
}
if( ksize.width == 1 && ksize.height == 1 )
{
_src.copyTo(_dst);
return;
}
bool useOpenCL = (ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 &&
((ksize.width == 3 && ksize.height == 3) ||
(ksize.width == 5 && ksize.height == 5)) &&
_src.rows() > ksize.height && _src.cols() > ksize.width);
CV_UNUSED(useOpenCL);
int sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
Mat kx, ky;
createGaussianKernels(kx, ky, type, ksize, sigma1, sigma2);
CV_OCL_RUN(useOpenCL, ocl_GaussianBlur_8UC1(_src, _dst, ksize, CV_MAT_DEPTH(type), kx, ky, borderType));
CV_OCL_RUN(_dst.isUMat() && _src.dims() <= 2 && (size_t)_src.rows() > kx.total() && (size_t)_src.cols() > kx.total(),
ocl_sepFilter2D(_src, _dst, sdepth, kx, ky, Point(-1, -1), 0, borderType))
Mat src = _src.getMat();
Mat dst = _dst.getMat();
Point ofs;
Size wsz(src.cols, src.rows);
if(!(borderType & BORDER_ISOLATED))
src.locateROI( wsz, ofs );
CALL_HAL(gaussianBlur, cv_hal_gaussianBlur, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, cn,
ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, ksize.width, ksize.height,
sigma1, sigma2, borderType&~BORDER_ISOLATED);
CV_OVX_RUN(true,
openvx_gaussianBlur(src, dst, ksize, sigma1, sigma2, borderType))
CV_IPP_RUN_FAST(ipp_GaussianBlur(src, dst, ksize, sigma1, sigma2, borderType));
if(sdepth == CV_8U && ((borderType & BORDER_ISOLATED) || !_src.getMat().isSubmatrix()))
{
std::vector<ufixedpoint16> fkx, fky;
createGaussianKernels(fkx, fky, type, ksize, sigma1, sigma2);
if (src.data == dst.data)
src = src.clone();
CV_CPU_DISPATCH(GaussianBlurFixedPoint, (src, dst, (const uint16_t*)&fkx[0], (int)fkx.size(), (const uint16_t*)&fky[0], (int)fky.size(), borderType),
CV_CPU_DISPATCH_MODES_ALL);
return;
}
sepFilter2D(src, dst, sdepth, kx, ky, Point(-1, -1), 0, borderType);
}
} // namespace
//////////////////////////////////////////////////////////////////////////////////////////
CV_IMPL void
cvSmooth( const void* srcarr, void* dstarr, int smooth_type,
int param1, int param2, double param3, double param4 )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst0 = cv::cvarrToMat(dstarr), dst = dst0;
CV_Assert( dst.size() == src.size() &&
(smooth_type == CV_BLUR_NO_SCALE || dst.type() == src.type()) );
if( param2 <= 0 )
param2 = param1;
if( smooth_type == CV_BLUR || smooth_type == CV_BLUR_NO_SCALE )
cv::boxFilter( src, dst, dst.depth(), cv::Size(param1, param2), cv::Point(-1,-1),
smooth_type == CV_BLUR, cv::BORDER_REPLICATE );
else if( smooth_type == CV_GAUSSIAN )
cv::GaussianBlur( src, dst, cv::Size(param1, param2), param3, param4, cv::BORDER_REPLICATE );
else if( smooth_type == CV_MEDIAN )
cv::medianBlur( src, dst, param1 );
else
cv::bilateralFilter( src, dst, param1, param3, param4, cv::BORDER_REPLICATE );
if( dst.data != dst0.data )
CV_Error( CV_StsUnmatchedFormats, "The destination image does not have the proper type" );
}
/* End of file. */

541
modules/imgproc/src/smooth.cpp → modules/imgproc/src/smooth.simd.hpp
View File

@ -46,120 +46,28 @@
#include <vector>
#include "opencv2/core/hal/intrin.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "opencv2/core/openvx/ovx_defs.hpp"
#include "filter.hpp"
#include "fixedpoint.inl.hpp"
/****************************************************************************************\
Gaussian Blur
\****************************************************************************************/
cv::Mat cv::getGaussianKernel( int n, double sigma, int ktype )
{
CV_Assert(n > 0);
const int SMALL_GAUSSIAN_SIZE = 7;
static const float small_gaussian_tab[][SMALL_GAUSSIAN_SIZE] =
{
{1.f},
{0.25f, 0.5f, 0.25f},
{0.0625f, 0.25f, 0.375f, 0.25f, 0.0625f},
{0.03125f, 0.109375f, 0.21875f, 0.28125f, 0.21875f, 0.109375f, 0.03125f}
};
const float* fixed_kernel = n % 2 == 1 && n <= SMALL_GAUSSIAN_SIZE && sigma <= 0 ?
small_gaussian_tab[n>>1] : 0;
CV_Assert( ktype == CV_32F || ktype == CV_64F );
Mat kernel(n, 1, ktype);
float* cf = kernel.ptr<float>();
double* cd = kernel.ptr<double>();
double sigmaX = sigma > 0 ? sigma : ((n-1)*0.5 - 1)*0.3 + 0.8;
double scale2X = -0.5/(sigmaX*sigmaX);
double sum = 0;
int i;
for( i = 0; i < n; i++ )
{
double x = i - (n-1)*0.5;
double t = fixed_kernel ? (double)fixed_kernel[i] : std::exp(scale2X*x*x);
if( ktype == CV_32F )
{
cf[i] = (float)t;
sum += cf[i];
}
else
{
cd[i] = t;
sum += cd[i];
}
}
CV_DbgAssert(fabs(sum) > 0);
sum = 1./sum;
for( i = 0; i < n; i++ )
{
if( ktype == CV_32F )
cf[i] = (float)(cf[i]*sum);
else
cd[i] *= sum;
}
return kernel;
}
#include "opencv2/core/softfloat.hpp"
namespace cv {
CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
// forward declarations
void GaussianBlurFixedPoint(const Mat& src, /*const*/ Mat& dst,
const uint16_t/*ufixedpoint16*/* fkx, int fkx_size,
const uint16_t/*ufixedpoint16*/* fky, int fky_size,
int borderType);
template <typename T>
static std::vector<T> getFixedpointGaussianKernel( int n, double sigma )
{
if (sigma <= 0)
{
if(n == 1)
return std::vector<T>(1, softdouble(1.0));
else if(n == 3)
{
T v3[] = { softdouble(0.25), softdouble(0.5), softdouble(0.25) };
return std::vector<T>(v3, v3 + 3);
}
else if(n == 5)
{
T v5[] = { softdouble(0.0625), softdouble(0.25), softdouble(0.375), softdouble(0.25), softdouble(0.0625) };
return std::vector<T>(v5, v5 + 5);
}
else if(n == 7)
{
T v7[] = { softdouble(0.03125), softdouble(0.109375), softdouble(0.21875), softdouble(0.28125), softdouble(0.21875), softdouble(0.109375), softdouble(0.03125) };
return std::vector<T>(v7, v7 + 7);
}
}
#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
#if defined(CV_CPU_BASELINE_MODE)
// included in dispatch.cpp
#else
#include "fixedpoint.inl.hpp"
#endif
softdouble sigmaX = sigma > 0 ? softdouble(sigma) : mulAdd(softdouble(n),softdouble(0.15),softdouble(0.35));// softdouble(((n-1)*0.5 - 1)*0.3 + 0.8)
softdouble scale2X = softdouble(-0.5*0.25)/(sigmaX*sigmaX);
std::vector<softdouble> values(n);
softdouble sum(0.);
for(int i = 0, x = 1 - n; i < n; i++, x+=2 )
{
// x = i - (n - 1)*0.5
// t = std::exp(scale2X*x*x)
values[i] = exp(softdouble(x*x)*scale2X);
sum += values[i];
}
sum = softdouble::one()/sum;
std::vector<T> kernel(n);
for(int i = 0; i < n; i++ )
{
kernel[i] = values[i] * sum;
}
return kernel;
};
namespace {
template <typename ET, typename FT>
void hlineSmooth1N(const ET* src, int cn, const FT* m, int, FT* dst, int len, int)
@ -2119,418 +2027,27 @@ private:
fixedSmoothInvoker& operator=(const fixedSmoothInvoker&);
};
static void getGaussianKernel(int n, double sigma, int ktype, Mat& res) { res = getGaussianKernel(n, sigma, ktype); }
template <typename T> static void getGaussianKernel(int n, double sigma, int, std::vector<T>& res) { res = getFixedpointGaussianKernel<T>(n, sigma); }
} // namespace anon
template <typename T>
static void createGaussianKernels( T & kx, T & ky, int type, Size &ksize,
double sigma1, double sigma2 )
{
int depth = CV_MAT_DEPTH(type);
if( sigma2 <= 0 )
sigma2 = sigma1;
// automatic detection of kernel size from sigma
if( ksize.width <= 0 && sigma1 > 0 )
ksize.width = cvRound(sigma1*(depth == CV_8U ? 3 : 4)*2 + 1)|1;
if( ksize.height <= 0 && sigma2 > 0 )
ksize.height = cvRound(sigma2*(depth == CV_8U ? 3 : 4)*2 + 1)|1;
CV_Assert( ksize.width > 0 && ksize.width % 2 == 1 &&
ksize.height > 0 && ksize.height % 2 == 1 );
sigma1 = std::max( sigma1, 0. );
sigma2 = std::max( sigma2, 0. );
getGaussianKernel( ksize.width, sigma1, std::max(depth, CV_32F), kx );
if( ksize.height == ksize.width && std::abs(sigma1 - sigma2) < DBL_EPSILON )
ky = kx;
else
getGaussianKernel( ksize.height, sigma2, std::max(depth, CV_32F), ky );
}
}
cv::Ptr<cv::FilterEngine> cv::createGaussianFilter( int type, Size ksize,
double sigma1, double sigma2,
int borderType )
{
Mat kx, ky;
createGaussianKernels(kx, ky, type, ksize, sigma1, sigma2);
return createSeparableLinearFilter( type, type, kx, ky, Point(-1,-1), 0, borderType );
}
namespace cv
{
#ifdef HAVE_OPENCL
static bool ocl_GaussianBlur_8UC1(InputArray _src, OutputArray _dst, Size ksize, int ddepth,
InputArray _kernelX, InputArray _kernelY, int borderType)
{
const ocl::Device & dev = ocl::Device::getDefault();
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if ( !(dev.isIntel() && (type == CV_8UC1) &&
(_src.offset() == 0) && (_src.step() % 4 == 0) &&
((ksize.width == 5 && (_src.cols() % 4 == 0)) ||
(ksize.width == 3 && (_src.cols() % 16 == 0) && (_src.rows() % 2 == 0)))) )
return false;
Mat kernelX = _kernelX.getMat().reshape(1, 1);
if (kernelX.cols % 2 != 1)
return false;
Mat kernelY = _kernelY.getMat().reshape(1, 1);
if (kernelY.cols % 2 != 1)
return false;
if (ddepth < 0)
ddepth = sdepth;
Size size = _src.size();
size_t globalsize[2] = { 0, 0 };
size_t localsize[2] = { 0, 0 };
if (ksize.width == 3)
{
globalsize[0] = size.width / 16;
globalsize[1] = size.height / 2;
}
else if (ksize.width == 5)
{
globalsize[0] = size.width / 4;
globalsize[1] = size.height / 1;
}
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
char build_opts[1024];
sprintf(build_opts, "-D %s %s%s", borderMap[borderType & ~BORDER_ISOLATED],
ocl::kernelToStr(kernelX, CV_32F, "KERNEL_MATRIX_X").c_str(),
ocl::kernelToStr(kernelY, CV_32F, "KERNEL_MATRIX_Y").c_str());
ocl::Kernel kernel;
if (ksize.width == 3)
kernel.create("gaussianBlur3x3_8UC1_cols16_rows2", cv::ocl::imgproc::gaussianBlur3x3_oclsrc, build_opts);
else if (ksize.width == 5)
kernel.create("gaussianBlur5x5_8UC1_cols4", cv::ocl::imgproc::gaussianBlur5x5_oclsrc, build_opts);
if (kernel.empty())
return false;
UMat src = _src.getUMat();
_dst.create(size, CV_MAKETYPE(ddepth, cn));
if (!(_dst.offset() == 0 && _dst.step() % 4 == 0))
return false;
UMat dst = _dst.getUMat();
int idxArg = kernel.set(0, ocl::KernelArg::PtrReadOnly(src));
idxArg = kernel.set(idxArg, (int)src.step);
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst));
idxArg = kernel.set(idxArg, (int)dst.step);
idxArg = kernel.set(idxArg, (int)dst.rows);
idxArg = kernel.set(idxArg, (int)dst.cols);
return kernel.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false);
}
#endif
#ifdef HAVE_OPENVX
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_GAUSSIAN_3x3>(int w, int h) { return w*h < 320 * 240; }
}
static bool openvx_gaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
double sigma1, double sigma2, int borderType)
{
if (sigma2 <= 0)
sigma2 = sigma1;
// automatic detection of kernel size from sigma
if (ksize.width <= 0 && sigma1 > 0)
ksize.width = cvRound(sigma1*6 + 1) | 1;
if (ksize.height <= 0 && sigma2 > 0)
ksize.height = cvRound(sigma2*6 + 1) | 1;
if (_src.type() != CV_8UC1 ||
_src.cols() < 3 || _src.rows() < 3 ||
ksize.width != 3 || ksize.height != 3)
return false;
sigma1 = std::max(sigma1, 0.);
sigma2 = std::max(sigma2, 0.);
if (!(sigma1 == 0.0 || (sigma1 - 0.8) < DBL_EPSILON) || !(sigma2 == 0.0 || (sigma2 - 0.8) < DBL_EPSILON) ||
ovx::skipSmallImages<VX_KERNEL_GAUSSIAN_3x3>(_src.cols(), _src.rows()))
return false;
Mat src = _src.getMat();
Mat dst = _dst.getMat();
if ((borderType & BORDER_ISOLATED) == 0 && src.isSubmatrix())
return false; //Process isolated borders only
vx_enum border;
switch (borderType & ~BORDER_ISOLATED)
{
case BORDER_CONSTANT:
border = VX_BORDER_CONSTANT;
break;
case BORDER_REPLICATE:
border = VX_BORDER_REPLICATE;
break;
default:
return false;
}
try
{
ivx::Context ctx = ovx::getOpenVXContext();
Mat a;
if (dst.data != src.data)
a = src;
else
src.copyTo(a);
ivx::Image
ia = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(a.cols, a.rows, 1, (vx_int32)(a.step)), a.data),
ib = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(dst.cols, dst.rows, 1, (vx_int32)(dst.step)), dst.data);
//ATTENTION: VX_CONTEXT_IMMEDIATE_BORDER attribute change could lead to strange issues in multi-threaded environments
//since OpenVX standard says nothing about thread-safety for now
ivx::border_t prevBorder = ctx.immediateBorder();
ctx.setImmediateBorder(border, (vx_uint8)(0));
ivx::IVX_CHECK_STATUS(vxuGaussian3x3(ctx, ia, ib));
ctx.setImmediateBorder(prevBorder);
}
catch (const ivx::RuntimeError & e)
{
VX_DbgThrow(e.what());
}
catch (const ivx::WrapperError & e)
{
VX_DbgThrow(e.what());
}
return true;
}
#endif
#if 0 //defined HAVE_IPP
// IW 2017u2 has bug which doesn't allow use of partial inMem with tiling
#if IPP_DISABLE_GAUSSIANBLUR_PARALLEL
#define IPP_GAUSSIANBLUR_PARALLEL 0
#else
#define IPP_GAUSSIANBLUR_PARALLEL 1
#endif
#ifdef HAVE_IPP_IW
class ipp_gaussianBlurParallel: public ParallelLoopBody
{
public:
ipp_gaussianBlurParallel(::ipp::IwiImage &src, ::ipp::IwiImage &dst, int kernelSize, float sigma, ::ipp::IwiBorderType &border, bool *pOk):
m_src(src), m_dst(dst), m_kernelSize(kernelSize), m_sigma(sigma), m_border(border), m_pOk(pOk) {
*m_pOk = true;
}
~ipp_gaussianBlurParallel()
{
}
virtual void operator() (const Range& range) const CV_OVERRIDE
{
CV_INSTRUMENT_REGION_IPP();
if(!*m_pOk)
return;
try
{
::ipp::IwiTile tile = ::ipp::IwiRoi(0, range.start, m_dst.m_size.width, range.end - range.start);
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterGaussian, m_src, m_dst, m_kernelSize, m_sigma, ::ipp::IwDefault(), m_border, tile);
}
catch(const ::ipp::IwException &)
{
*m_pOk = false;
return;
}
}
private:
::ipp::IwiImage &m_src;
::ipp::IwiImage &m_dst;
int m_kernelSize;
float m_sigma;
::ipp::IwiBorderType &m_border;
volatile bool *m_pOk;
const ipp_gaussianBlurParallel& operator= (const ipp_gaussianBlurParallel&);
};
#endif
static bool ipp_GaussianBlur(InputArray _src, OutputArray _dst, Size ksize,
double sigma1, double sigma2, int borderType )
{
#ifdef HAVE_IPP_IW
CV_INSTRUMENT_REGION_IPP();
#if IPP_VERSION_X100 < 201800 && ((defined _MSC_VER && defined _M_IX86) || (defined __GNUC__ && defined __i386__))
CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(ksize); CV_UNUSED(sigma1); CV_UNUSED(sigma2); CV_UNUSED(borderType);
return false; // bug on ia32
#else
if(sigma1 != sigma2)
return false;
if(sigma1 < FLT_EPSILON)
return false;
if(ksize.width != ksize.height)
return false;
// Acquire data and begin processing
try
{
Mat src = _src.getMat();
Mat dst = _dst.getMat();
::ipp::IwiImage iwSrc = ippiGetImage(src);
::ipp::IwiImage iwDst = ippiGetImage(dst);
::ipp::IwiBorderSize borderSize = ::ipp::iwiSizeToBorderSize(ippiGetSize(ksize));
::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize));
if(!ippBorder)
return false;
const int threads = ippiSuggestThreadsNum(iwDst, 2);
if(IPP_GAUSSIANBLUR_PARALLEL && threads > 1) {
bool ok;
ipp_gaussianBlurParallel invoker(iwSrc, iwDst, ksize.width, (float) sigma1, ippBorder, &ok);
if(!ok)
return false;
const Range range(0, (int) iwDst.m_size.height);
parallel_for_(range, invoker, threads*4);
if(!ok)
return false;
} else {
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterGaussian, iwSrc, iwDst, ksize.width, sigma1, ::ipp::IwDefault(), ippBorder);
}
}
catch (const ::ipp::IwException &)
{
return false;
}
return true;
#endif
#else
CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(ksize); CV_UNUSED(sigma1); CV_UNUSED(sigma2); CV_UNUSED(borderType);
return false;
#endif
}
#endif
}
void cv::GaussianBlur( InputArray _src, OutputArray _dst, Size ksize,
double sigma1, double sigma2,
void GaussianBlurFixedPoint(const Mat& src, /*const*/ Mat& dst,
const uint16_t/*ufixedpoint16*/* fkx, int fkx_size,
const uint16_t/*ufixedpoint16*/* fky, int fky_size,
int borderType)
{
CV_INSTRUMENT_REGION();
int type = _src.type();
Size size = _src.size();
_dst.create( size, type );
if( (borderType & ~BORDER_ISOLATED) != BORDER_CONSTANT &&
((borderType & BORDER_ISOLATED) != 0 || !_src.getMat().isSubmatrix()) )
CV_Assert(src.depth() == CV_8U && ((borderType & BORDER_ISOLATED) || !src.isSubmatrix()));
fixedSmoothInvoker<uint8_t, ufixedpoint16> invoker(
src.ptr<uint8_t>(), src.step1(),
dst.ptr<uint8_t>(), dst.step1(), dst.cols, dst.rows, dst.channels(),
(const ufixedpoint16*)fkx, fkx_size, (const ufixedpoint16*)fky, fky_size,
borderType & ~BORDER_ISOLATED);
{
if( size.height == 1 )
ksize.height = 1;
if( size.width == 1 )
ksize.width = 1;
}
if( ksize.width == 1 && ksize.height == 1 )
{
_src.copyTo(_dst);
return;
}
bool useOpenCL = (ocl::isOpenCLActivated() && _dst.isUMat() && _src.dims() <= 2 &&
((ksize.width == 3 && ksize.height == 3) ||
(ksize.width == 5 && ksize.height == 5)) &&
_src.rows() > ksize.height && _src.cols() > ksize.width);
CV_UNUSED(useOpenCL);
int sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
Mat kx, ky;
createGaussianKernels(kx, ky, type, ksize, sigma1, sigma2);
CV_OCL_RUN(useOpenCL, ocl_GaussianBlur_8UC1(_src, _dst, ksize, CV_MAT_DEPTH(type), kx, ky, borderType));
CV_OCL_RUN(_dst.isUMat() && _src.dims() <= 2 && (size_t)_src.rows() > kx.total() && (size_t)_src.cols() > kx.total(),
ocl_sepFilter2D(_src, _dst, sdepth, kx, ky, Point(-1, -1), 0, borderType))
Mat src = _src.getMat();
Mat dst = _dst.getMat();
Point ofs;
Size wsz(src.cols, src.rows);
if(!(borderType & BORDER_ISOLATED))
src.locateROI( wsz, ofs );
CALL_HAL(gaussianBlur, cv_hal_gaussianBlur, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, cn,
ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, ksize.width, ksize.height,
sigma1, sigma2, borderType&~BORDER_ISOLATED);
CV_OVX_RUN(true,
openvx_gaussianBlur(src, dst, ksize, sigma1, sigma2, borderType))
//CV_IPP_RUN_FAST(ipp_GaussianBlur(src, dst, ksize, sigma1, sigma2, borderType));
if(sdepth == CV_8U && ((borderType & BORDER_ISOLATED) || !_src.getMat().isSubmatrix()))
{
std::vector<ufixedpoint16> fkx, fky;
createGaussianKernels(fkx, fky, type, ksize, sigma1, sigma2);
if (src.data == dst.data)
src = src.clone();
fixedSmoothInvoker<uint8_t, ufixedpoint16> invoker(src.ptr<uint8_t>(), src.step1(), dst.ptr<uint8_t>(), dst.step1(), dst.cols, dst.rows, dst.channels(), &fkx[0], (int)fkx.size(), &fky[0], (int)fky.size(), borderType & ~BORDER_ISOLATED);
// TODO AVX guard (external call)
parallel_for_(Range(0, dst.rows), invoker, std::max(1, std::min(getNumThreads(), getNumberOfCPUs())));
return;
}
}
sepFilter2D(src, dst, sdepth, kx, ky, Point(-1, -1), 0, borderType);
}
//////////////////////////////////////////////////////////////////////////////////////////
CV_IMPL void
cvSmooth( const void* srcarr, void* dstarr, int smooth_type,
int param1, int param2, double param3, double param4 )
{
cv::Mat src = cv::cvarrToMat(srcarr), dst0 = cv::cvarrToMat(dstarr), dst = dst0;
CV_Assert( dst.size() == src.size() &&
(smooth_type == CV_BLUR_NO_SCALE || dst.type() == src.type()) );
if( param2 <= 0 )
param2 = param1;
if( smooth_type == CV_BLUR || smooth_type == CV_BLUR_NO_SCALE )
cv::boxFilter( src, dst, dst.depth(), cv::Size(param1, param2), cv::Point(-1,-1),
smooth_type == CV_BLUR, cv::BORDER_REPLICATE );
else if( smooth_type == CV_GAUSSIAN )
cv::GaussianBlur( src, dst, cv::Size(param1, param2), param3, param4, cv::BORDER_REPLICATE );
else if( smooth_type == CV_MEDIAN )
cv::medianBlur( src, dst, param1 );
else
cv::bilateralFilter( src, dst, param1, param3, param4, cv::BORDER_REPLICATE );
if( dst.data != dst0.data )
CV_Error( CV_StsUnmatchedFormats, "The destination image does not have the proper type" );
}
/* End of file. */
#endif
CV_CPU_OPTIMIZATION_NAMESPACE_END
} // namespace

2
modules/java/generator/android/java/org/opencv/android/BaseLoaderCallback.java
View File

@ -137,5 +137,5 @@ public abstract class BaseLoaderCallback implements LoaderCallbackInterface {
}
protected Context mAppContext;
private final static String TAG = "OpenCVLoader/BaseLoaderCallback";
private final static String TAG = "OCV/BaseLoaderCallback";
}

566
modules/java/generator/src/cpp/Mat.cpp
View File

@ -32,6 +32,18 @@ static void throwJavaException(JNIEnv *env, const std::exception *e, const char
CV_UNUSED(method); // avoid "unused" warning
}
// jint could be int or int32_t so casting jint* to int* in general wouldn't work
static std::vector<int> convertJintArrayToVector(JNIEnv* env, jintArray in) {
std::vector<int> out;
int len = env->GetArrayLength(in);
jint* inArray = env->GetIntArrayElements(in, 0);
for ( int i = 0; i < len; i++ ) {
out.push_back(inArray[i]);
}
env->ReleaseIntArrayElements(in, inArray, 0);
return out;
}
extern "C" {
@ -100,6 +112,30 @@ JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1Mat__III
return 0;
}
//
// Mat::Mat(int[] sizes, int type)
//
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1Mat__I_3II
(JNIEnv* env, jclass, jint ndims, jintArray sizesArray, jint type);
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1Mat__I_3II
(JNIEnv* env, jclass, jint ndims, jintArray sizesArray, jint type)
{
static const char method_name[] = "Mat::n_1Mat__I_3II()";
try {
LOGD("%s", method_name);
std::vector<int> sizes = convertJintArrayToVector(env, sizesArray);
return (jlong) new Mat( ndims, sizes.data(), type );
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
} catch (...) {
throwJavaException(env, 0, method_name);
}
return 0;
}
//
@ -182,6 +218,33 @@ JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1Mat__DDIDDDD
//
// Mat::Mat(int[] sizes, int type, Scalar s)
//
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1Mat__I_3IIDDDD
(JNIEnv* env, jclass, jint ndims, jintArray sizesArray, jint type, jdouble s_val0, jdouble s_val1, jdouble s_val2, jdouble s_val3);
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1Mat__I_3IIDDDD
(JNIEnv* env, jclass, jint ndims, jintArray sizesArray, jint type, jdouble s_val0, jdouble s_val1, jdouble s_val2, jdouble s_val3)
{
static const char method_name[] = "Mat::n_1Mat__I_3IIDDDD()";
try {
LOGD("%s", method_name);
std::vector<int> sizes = convertJintArrayToVector(env, sizesArray);
Scalar s(s_val0, s_val1, s_val2, s_val3);
return (jlong) new Mat( ndims, sizes.data(), type, s );
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
} catch (...) {
throwJavaException(env, 0, method_name);
}
return 0;
}
//
// Mat::Mat(Mat m, Range rowRange, Range colRange = Range::all())
//
@ -207,6 +270,59 @@ JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1Mat__JIIII
return 0;
}
jint getObjectIntField(JNIEnv* env, jobject obj, const char * fieldName);
jint getObjectIntField(JNIEnv* env, jobject obj, const char * fieldName) {
jfieldID fid; /* store the field ID */
/* Get a reference to obj's class */
jclass cls = env->GetObjectClass(obj);
/* Look for the instance field s in cls */
fid = env->GetFieldID(cls, fieldName, "I");
if (fid == NULL)
{
return 0; /* failed to find the field */
}
/* Read the instance field s */
return env->GetIntField(obj, fid);
}
#define RANGE_START_FIELD "start"
#define RANGE_END_FIELD "end"
//
// Mat::Mat(Mat m, Range[] ranges)
//
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1Mat__J_3Lorg_opencv_core_Range_2
(JNIEnv* env, jclass, jlong m_nativeObj, jobjectArray rangesArray);
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1Mat__J_3Lorg_opencv_core_Range_2
(JNIEnv* env, jclass, jlong m_nativeObj, jobjectArray rangesArray)
{
static const char method_name[] = "Mat::n_1Mat__J_3Lorg_opencv_core_Range_2()";
try {
LOGD("%s", method_name);
std::vector<Range> ranges;
int rangeCount = env->GetArrayLength(rangesArray);
for (int i = 0; i < rangeCount; i++) {
jobject range = env->GetObjectArrayElement(rangesArray, i);
jint start = getObjectIntField(env, range, RANGE_START_FIELD);
jint end = getObjectIntField(env, range, RANGE_END_FIELD);
ranges.push_back(Range(start, end));
}
return (jlong) new Mat( (*(Mat*)m_nativeObj), ranges );
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
} catch (...) {
throwJavaException(env, 0, method_name);
}
return 0;
}
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1Mat__JII
(JNIEnv* env, jclass, jlong m_nativeObj, jint rowRange_start, jint rowRange_end);
@ -718,6 +834,56 @@ JNIEXPORT void JNICALL Java_org_opencv_core_Mat_n_1create__JDDI
//
// void Mat::create(int[] sizes, int type)
//
JNIEXPORT void JNICALL Java_org_opencv_core_Mat_n_1create__JI_3II
(JNIEnv* env, jclass, jlong self, jint ndims, jintArray sizesArray, jint type);
JNIEXPORT void JNICALL Java_org_opencv_core_Mat_n_1create__JI_3II
(JNIEnv* env, jclass, jlong self, jint ndims, jintArray sizesArray, jint type)
{
static const char method_name[] = "Mat::n_1create__JI_3II()";
try {
LOGD("%s", method_name);
Mat* me = (Mat*) self;
std::vector<int> sizes = convertJintArrayToVector(env, sizesArray);
me->create( ndims, sizes.data(), type );
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
} catch (...) {
throwJavaException(env, 0, method_name);
}
}
//
// Mat Mat::copySize(Mat m)
//
JNIEXPORT void JNICALL Java_org_opencv_core_Mat_n_1copySize
(JNIEnv* env, jclass, jlong self, jlong m_nativeObj);
JNIEXPORT void JNICALL Java_org_opencv_core_Mat_n_1copySize
(JNIEnv* env, jclass, jlong self, jlong m_nativeObj)
{
static const char method_name[] = "Mat::n_1copySize()";
try {
LOGD("%s", method_name);
Mat* me = (Mat*) self;
Mat& m = *((Mat*)m_nativeObj);
me->copySize( m );
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
} catch (...) {
throwJavaException(env, 0, method_name);
}
}
//
// Mat Mat::cross(Mat m)
//
@ -1234,6 +1400,33 @@ JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1ones__DDI
//
// static Mat Mat::ones(int[] sizes, int type)
//
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1ones__I_3II
(JNIEnv* env, jclass, jint ndims, jintArray sizesArray, jint type);
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1ones__I_3II
(JNIEnv* env, jclass, jint ndims, jintArray sizesArray, jint type)
{
static const char method_name[] = "Mat::n_1ones__I_3II()";
try {
LOGD("%s", method_name);
std::vector<int> sizes = convertJintArrayToVector(env, sizesArray);
Mat _retval_ = Mat::ones( ndims, sizes.data(), type );
return (jlong) new Mat(_retval_);
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
} catch (...) {
throwJavaException(env, 0, method_name);
}
return 0;
}
//
// void Mat::push_back(Mat m)
//
@ -1344,8 +1537,8 @@ JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1reshape_11
try {
LOGD("%s", method_name);
Mat* me = (Mat*) self; //TODO: check for NULL
int* newsz = (int*)env->GetPrimitiveArrayCritical(newshape, 0);
Mat _retval_ = me->reshape( cn, newndims, newsz );
std::vector<int> newsz = convertJintArrayToVector(env, newshape);
Mat _retval_ = me->reshape( cn, newndims, newsz.data() );
return (jlong) new Mat(_retval_);
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
@ -1649,6 +1842,39 @@ JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1submat_1rr
return 0;
}
//
// Mat Mat::operator()(Range[] ranges)
//
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1submat_1ranges
(JNIEnv* env, jclass, jlong self, jobjectArray rangesArray);
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1submat_1ranges
(JNIEnv* env, jclass, jlong self, jobjectArray rangesArray)
{
static const char method_name[] = "Mat::n_1submat_1ranges()";
try {
LOGD("%s", method_name);
Mat* me = (Mat*) self;
std::vector<Range> ranges;
int rangeCount = env->GetArrayLength(rangesArray);
for (int i = 0; i < rangeCount; i++) {
jobject range = env->GetObjectArrayElement(rangesArray, i);
jint start = getObjectIntField(env, range, RANGE_START_FIELD);
jint end = getObjectIntField(env, range, RANGE_END_FIELD);
ranges.push_back(Range(start, end));
}
Mat _retval_ = me->operator()( ranges );
return (jlong) new Mat(_retval_);
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
} catch (...) {
throwJavaException(env, 0, method_name);
}
return 0;
}
//
@ -1811,6 +2037,33 @@ JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1zeros__DDI
//
// static Mat Mat::zeros(int[] sizes, int type)
//
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1zeros__I_3II
(JNIEnv* env, jclass, jint ndims, jintArray sizesArray, jint type);
JNIEXPORT jlong JNICALL Java_org_opencv_core_Mat_n_1zeros__I_3II
(JNIEnv* env, jclass, jint ndims, jintArray sizesArray, jint type)
{
static const char method_name[] = "Mat::n_1zeros__I_3II()";
try {
LOGD("%s", method_name);
std::vector<int> sizes = convertJintArrayToVector(env, sizesArray);
Mat _retval_ = Mat::zeros( ndims, sizes.data(), type );
return (jlong) new Mat(_retval_);
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
} catch (...) {
throwJavaException(env, 0, method_name);
}
return 0;
}
//
// native support for java finalize()
// static void Mat::n_delete( __int64 self )
@ -1880,6 +2133,50 @@ template<typename T> static int mat_put(cv::Mat* m, int row, int col, int count,
return res;
}
// returns true if final index was reached
static bool updateIdx(cv::Mat* m, std::vector<int>& idx, int inc) {
for (int i=m->dims-1; i>=0; i--) {
if (inc == 0) return false;
idx[i] = (idx[i] + 1) % m->size[i];
inc--;
}
return true;
}
template<typename T> static int mat_put_idx(cv::Mat* m, std::vector<int>& idx, int count, int offset, char* buff)
{
if(! m) return 0;
if(! buff) return 0;
count *= sizeof(T);
int rest = (int)m->elemSize();
for (int i = 0; i < m->dims; i++) {
rest *= (m->size[i] - idx[i]);
}
if(count>rest) count = rest;
int res = count;
if( m->isContinuous() )
{
memcpy(m->ptr(idx.data()), buff + offset, count);
} else {
// dim by dim
int num = (m->size[m->dims-1] - idx[m->dims-1]) * (int)m->elemSize(); // 1st partial row
if(count<num) num = count;
uchar* data = m->ptr(idx.data());
while(count>0){
memcpy(data, buff + offset, num);
updateIdx(m, idx, num / (int)m->elemSize());
count -= num;
buff += num;
num = m->size[m->dims-1] * (int)m->elemSize();
if(count<num) num = count;
data = m->ptr(idx.data());
}
}
return res;
}
template<class ARRAY> static jint java_mat_put(JNIEnv* env, jlong self, jint row, jint col, jint count, jint offset, ARRAY vals)
{
static const char *method_name = JavaOpenCVTrait<ARRAY>::put;
@ -1903,6 +2200,31 @@ template<class ARRAY> static jint java_mat_put(JNIEnv* env, jlong self, jint row
return 0;
}
template<class ARRAY> static jint java_mat_put_idx(JNIEnv* env, jlong self, jintArray idxArray, jint count, jint offset, ARRAY vals)
{
static const char *method_name = JavaOpenCVTrait<ARRAY>::put;
try {
LOGD("%s", method_name);
cv::Mat* me = (cv::Mat*) self;
if(! self) return 0; // no native object behind
if(me->depth() != JavaOpenCVTrait<ARRAY>::cvtype_1 && me->depth() != JavaOpenCVTrait<ARRAY>::cvtype_2) return 0; // incompatible type
std::vector<int> idx = convertJintArrayToVector(env, idxArray);
for (int i = 0; i < me->dims ; i++ ) {
if (me->size[i]<=idx[i]) return 0;
}
char* values = (char*)env->GetPrimitiveArrayCritical(vals, 0);
int res = mat_put_idx<typename JavaOpenCVTrait<ARRAY>::value_type>(me, idx, count, offset, values);
env->ReleasePrimitiveArrayCritical(vals, values, JNI_ABORT);
return res;
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
} catch (...) {
throwJavaException(env, 0, method_name);
}
return 0;
}
extern "C" {
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutB
@ -1914,6 +2236,15 @@ JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutB
return java_mat_put(env, self, row, col, count, 0, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutBIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jbyteArray vals);
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutBIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jbyteArray vals)
{
return java_mat_put_idx(env, self, idxArray, count, 0, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutBwOffset
(JNIEnv* env, jclass, jlong self, jint row, jint col, jint count, jint offset, jbyteArray vals);
@ -1923,6 +2254,15 @@ JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutBwOffset
return java_mat_put(env, self, row, col, count, offset, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutBwIdxOffset
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jint offset, jbyteArray vals);
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutBwIdxOffset
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jint offset, jbyteArray vals)
{
return java_mat_put_idx(env, self, idxArray, count, offset, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutS
(JNIEnv* env, jclass, jlong self, jint row, jint col, jint count, jshortArray vals);
@ -1932,6 +2272,15 @@ JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutS
return java_mat_put(env, self, row, col, count, 0, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutSIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jshortArray vals);
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutSIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jshortArray vals)
{
return java_mat_put_idx(env, self, idxArray, count, 0, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutI
(JNIEnv* env, jclass, jlong self, jint row, jint col, jint count, jintArray vals);
@ -1941,6 +2290,15 @@ JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutI
return java_mat_put(env, self, row, col, count, 0, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutIIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jintArray vals);
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutIIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jintArray vals)
{
return java_mat_put_idx(env, self, idxArray, count, 0, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutF
(JNIEnv* env, jclass, jlong self, jint row, jint col, jint count, jfloatArray vals);
@ -1950,6 +2308,15 @@ JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutF
return java_mat_put(env, self, row, col, count, 0, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutFIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jfloatArray vals);
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutFIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jfloatArray vals)
{
return java_mat_put_idx(env, self, idxArray, count, 0, vals);
}
// unlike other nPut()-s this one (with double[]) should convert input values to correct type
#define PUT_ITEM(T, R, C) { T*dst = (T*)me->ptr(R, C); for(int ch=0; ch<me->channels() && count>0; count--,ch++,src++,dst++) *dst = cv::saturate_cast<T>(*src); }
@ -2010,6 +2377,56 @@ JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutD
return 0;
}
// unlike other nPut()-s this one (with double[]) should convert input values to correct type
#define PUT_ITEM_IDX(T, I) { T*dst = (T*)me->ptr(I); for(int ch=0; ch<me->channels() && count>0; count--,ch++,src++,dst++) *dst = cv::saturate_cast<T>(*src); }
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutDIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jdoubleArray vals);
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nPutDIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jdoubleArray vals)
{
static const char* method_name = JavaOpenCVTrait<jdoubleArray>::put;
try {
LOGD("%s", method_name);
cv::Mat* me = (cv::Mat*) self;
if(!me || !me->data) return 0; // no native object behind
std::vector<int> idx = convertJintArrayToVector(env, idxArray);
for (int i=0; i<me->dims; i++) {
if (me->size[i]<=idx[i]) return 0; // indexes out of range
}
int rest = me->channels();
for (int i=0; i<me->dims; i++) {
rest *= (me->size[i] - idx[i]);
}
if(count>rest) count = rest;
int res = count;
double* values = (double*)env->GetPrimitiveArrayCritical(vals, 0);
double* src = values;
bool reachedFinalIndex = false;
for(; !reachedFinalIndex && count>0; reachedFinalIndex = updateIdx(me, idx, 1))
{
switch(me->depth()) {
case CV_8U: PUT_ITEM_IDX(uchar, idx.data()); break;
case CV_8S: PUT_ITEM_IDX(schar, idx.data()); break;
case CV_16U: PUT_ITEM_IDX(ushort, idx.data()); break;
case CV_16S: PUT_ITEM_IDX(short, idx.data()); break;
case CV_32S: PUT_ITEM_IDX(int, idx.data()); break;
case CV_32F: PUT_ITEM_IDX(float, idx.data()); break;
case CV_64F: PUT_ITEM_IDX(double, idx.data()); break;
}
}
env->ReleasePrimitiveArrayCritical(vals, values, 0);
return res;
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
} catch (...) {
throwJavaException(env, 0, method_name);
}
return 0;
}
} // extern "C"
template<typename T> static int mat_get(cv::Mat* m, int row, int col, int count, char* buff)
@ -2042,6 +2459,40 @@ template<typename T> static int mat_get(cv::Mat* m, int row, int col, int count,
return res;
}
template<typename T> static int mat_get_idx(cv::Mat* m, std::vector<int>& idx, int count, char* buff)
{
if(! m) return 0;
if(! buff) return 0;
count *= sizeof(T);
int rest = (int)m->elemSize();
for (int i = 0; i < m->dims; i++) {
rest *= (m->size[i] - idx[i]);
}
if(count>rest) count = rest;
int res = count;
if( m->isContinuous() )
{
memcpy(buff, m->ptr(idx.data()), count);
} else {
// dim by dim
int num = (m->size[m->dims-1] - idx[m->dims-1]) * (int)m->elemSize(); // 1st partial row
if(count<num) num = count;
uchar* data = m->ptr(idx.data());
while(count>0){
memcpy(buff, data, num);
updateIdx(m, idx, num / (int)m->elemSize());
count -= num;
buff += num;
num = m->size[m->dims-1] * (int)m->elemSize();
if(count<num) num = count;
data = m->ptr(idx.data());
}
}
return res;
}
template<class ARRAY> static jint java_mat_get(JNIEnv* env, jlong self, jint row, jint col, jint count, ARRAY vals) {
static const char *method_name = JavaOpenCVTrait<ARRAY>::get;
try {
@ -2064,6 +2515,31 @@ template<class ARRAY> static jint java_mat_get(JNIEnv* env, jlong self, jint row
return 0;
}
template<class ARRAY> static jint java_mat_get_idx(JNIEnv* env, jlong self, jintArray idxArray, jint count, ARRAY vals) {
static const char *method_name = JavaOpenCVTrait<ARRAY>::get;
try {
LOGD("%s", method_name);
cv::Mat* me = (cv::Mat*) self;
if(! self) return 0; // no native object behind
if(me->depth() != JavaOpenCVTrait<ARRAY>::cvtype_1 && me->depth() != JavaOpenCVTrait<ARRAY>::cvtype_2) return 0; // incompatible type
std::vector<int> idx = convertJintArrayToVector(env, idxArray);
for (int i = 0; i < me->dims ; i++ ) {
if (me->size[i]<=idx[i]) return 0;
}
char* values = (char*)env->GetPrimitiveArrayCritical(vals, 0);
int res = mat_get_idx<typename JavaOpenCVTrait<ARRAY>::value_type>(me, idx, count, values);
env->ReleasePrimitiveArrayCritical(vals, values, 0);
return res;
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
} catch (...) {
throwJavaException(env, 0, method_name);
}
return 0;
}
extern "C" {
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetB
@ -2075,6 +2551,15 @@ JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetB
return java_mat_get(env, self, row, col, count, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetBIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jbyteArray vals);
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetBIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jbyteArray vals)
{
return java_mat_get_idx(env, self, idxArray, count, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetS
(JNIEnv* env, jclass, jlong self, jint row, jint col, jint count, jshortArray vals);
@ -2084,6 +2569,15 @@ JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetS
return java_mat_get(env, self, row, col, count, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetSIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jshortArray vals);
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetSIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jshortArray vals)
{
return java_mat_get_idx(env, self, idxArray, count, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetI
(JNIEnv* env, jclass, jlong self, jint row, jint col, jint count, jintArray vals);
@ -2093,6 +2587,15 @@ JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetI
return java_mat_get(env, self, row, col, count, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetIIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jintArray vals);
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetIIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jintArray vals)
{
return java_mat_get_idx(env, self, idxArray, count, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetF
(JNIEnv* env, jclass, jlong self, jint row, jint col, jint count, jfloatArray vals);
@ -2102,6 +2605,15 @@ JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetF
return java_mat_get(env, self, row, col, count, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetFIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jfloatArray vals);
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetFIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jfloatArray vals)
{
return java_mat_get_idx(env, self, idxArray, count, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetD
(JNIEnv* env, jclass, jlong self, jint row, jint col, jint count, jdoubleArray vals);
@ -2111,6 +2623,15 @@ JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetD
return java_mat_get(env, self, row, col, count, vals);
}
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetDIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jdoubleArray vals);
JNIEXPORT jint JNICALL Java_org_opencv_core_Mat_nGetDIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray, jint count, jdoubleArray vals)
{
return java_mat_get_idx(env, self, idxArray, count, vals);
}
JNIEXPORT jdoubleArray JNICALL Java_org_opencv_core_Mat_nGet
(JNIEnv* env, jclass, jlong self, jint row, jint col);
@ -2149,6 +2670,47 @@ JNIEXPORT jdoubleArray JNICALL Java_org_opencv_core_Mat_nGet
return 0;
}
JNIEXPORT jdoubleArray JNICALL Java_org_opencv_core_Mat_nGetIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray);
JNIEXPORT jdoubleArray JNICALL Java_org_opencv_core_Mat_nGetIdx
(JNIEnv* env, jclass, jlong self, jintArray idxArray)
{
static const char method_name[] = "Mat::nGetIdx()";
try {
LOGD("%s", method_name);
cv::Mat* me = (cv::Mat*) self;
if(! self) return 0; // no native object behind
std::vector<int> idx = convertJintArrayToVector(env, idxArray);
for (int i=0; i<me->dims; i++) {
if (me->size[i]<=idx[i]) return 0; // indexes out of range
}
jdoubleArray res = env->NewDoubleArray(me->channels());
if(res){
jdouble buff[CV_CN_MAX];//me->channels()
int i;
switch(me->depth()){
case CV_8U: for(i=0; i<me->channels(); i++) buff[i] = *((unsigned char*) me->ptr(idx.data()) + i); break;
case CV_8S: for(i=0; i<me->channels(); i++) buff[i] = *((signed char*) me->ptr(idx.data()) + i); break;
case CV_16U: for(i=0; i<me->channels(); i++) buff[i] = *((unsigned short*)me->ptr(idx.data()) + i); break;
case CV_16S: for(i=0; i<me->channels(); i++) buff[i] = *((signed short*) me->ptr(idx.data()) + i); break;
case CV_32S: for(i=0; i<me->channels(); i++) buff[i] = *((int*) me->ptr(idx.data()) + i); break;
case CV_32F: for(i=0; i<me->channels(); i++) buff[i] = *((float*) me->ptr(idx.data()) + i); break;
case CV_64F: for(i=0; i<me->channels(); i++) buff[i] = *((double*) me->ptr(idx.data()) + i); break;
}
env->SetDoubleArrayRegion(res, 0, me->channels(), buff);
}
return res;
} catch(const std::exception &e) {
throwJavaException(env, &e, method_name);
} catch (...) {
throwJavaException(env, 0, method_name);
}
return 0;
}
JNIEXPORT jstring JNICALL Java_org_opencv_core_Mat_nDump
(JNIEnv *env, jclass, jlong self);

25
modules/java/test/android_test/src/org/opencv/test/OpenCVTestCase.java
View File

@ -99,6 +99,8 @@ public class OpenCVTestCase extends TestCase {
protected Mat rgbLena;
protected Mat grayChess;
protected Mat gray255_32f_3d;
protected Mat v1;
protected Mat v2;
@ -149,6 +151,8 @@ public class OpenCVTestCase extends TestCase {
rgbLena = Imgcodecs.imread(OpenCVTestRunner.LENA_PATH);
grayChess = Imgcodecs.imread(OpenCVTestRunner.CHESS_PATH, 0);
gray255_32f_3d = new Mat(new int[]{matSize, matSize, matSize}, CvType.CV_32F, new Scalar(255.0));
v1 = new Mat(1, 3, CvType.CV_32F);
v1.put(0, 0, 1.0, 3.0, 2.0);
v2 = new Mat(1, 3, CvType.CV_32F);
@ -184,6 +188,7 @@ public class OpenCVTestCase extends TestCase {
rgba128.release();
rgbLena.release();
grayChess.release();
gray255_32f_3d.release();
v1.release();
v2.release();
@ -442,8 +447,24 @@ public class OpenCVTestCase extends TestCase {
assertEquals(msg, expected.z, actual.z, eps);
}
static private boolean dimensionsEqual(Mat expected, Mat actual) {
if (expected.dims() != actual.dims()) {
return false;
}
if (expected.dims() > 2) {
for (int i = 0; i < expected.dims(); i++) {
if (expected.size(i) != actual.size(i)) {
return false;
}
}
return true;
} else {
return expected.cols() == actual.cols() && expected.rows() == actual.rows();
}
}
static private void compareMats(Mat expected, Mat actual, boolean isEqualityMeasured) {
if (expected.type() != actual.type() || expected.cols() != actual.cols() || expected.rows() != actual.rows()) {
if (expected.type() != actual.type() || !dimensionsEqual(expected, actual)) {
throw new UnsupportedOperationException("Can not compare " + expected + " and " + actual);
}
@ -471,7 +492,7 @@ public class OpenCVTestCase extends TestCase {
}
static private void compareMats(Mat expected, Mat actual, double eps, boolean isEqualityMeasured) {
if (expected.type() != actual.type() || expected.cols() != actual.cols() || expected.rows() != actual.rows()) {
if (expected.type() != actual.type() || !dimensionsEqual(expected, actual)) {
throw new UnsupportedOperationException("Can not compare " + expected + " and " + actual);
}

25
modules/java/test/pure_test/src/org/opencv/test/OpenCVTestCase.java
View File

@ -97,6 +97,8 @@ public class OpenCVTestCase extends TestCase {
protected Mat rgbLena;
protected Mat grayChess;
protected Mat gray255_32f_3d;
protected Mat v1;
protected Mat v2;
@ -175,6 +177,8 @@ public class OpenCVTestCase extends TestCase {
rgbLena = Imgcodecs.imread(OpenCVTestRunner.LENA_PATH);
grayChess = Imgcodecs.imread(OpenCVTestRunner.CHESS_PATH, 0);
gray255_32f_3d = new Mat(new int[]{matSize, matSize, matSize}, CvType.CV_32F, new Scalar(255.0));
v1 = new Mat(1, 3, CvType.CV_32F);
v1.put(0, 0, 1.0, 3.0, 2.0);
v2 = new Mat(1, 3, CvType.CV_32F);
@ -210,6 +214,7 @@ public class OpenCVTestCase extends TestCase {
rgba128.release();
rgbLena.release();
grayChess.release();
gray255_32f_3d.release();
v1.release();
v2.release();
@ -468,8 +473,24 @@ public class OpenCVTestCase extends TestCase {
assertEquals(msg, expected.z, actual.z, eps);
}
static private boolean dimensionsEqual(Mat expected, Mat actual) {
if (expected.dims() != actual.dims()) {
return false;
}
if (expected.dims() > 2) {
for (int i = 0; i < expected.dims(); i++) {
if (expected.size(i) != actual.size(i)) {
return false;
}
}
return true;
} else {
return expected.cols() == actual.cols() && expected.rows() == actual.rows();
}
}
static private void compareMats(Mat expected, Mat actual, boolean isEqualityMeasured) {
if (expected.type() != actual.type() || expected.cols() != actual.cols() || expected.rows() != actual.rows()) {
if (expected.type() != actual.type() || !dimensionsEqual(expected, actual)) {
throw new UnsupportedOperationException("Can not compare " + expected + " and " + actual);
}
@ -497,7 +518,7 @@ public class OpenCVTestCase extends TestCase {
}
static private void compareMats(Mat expected, Mat actual, double eps, boolean isEqualityMeasured) {
if (expected.type() != actual.type() || expected.cols() != actual.cols() || expected.rows() != actual.rows()) {
if (expected.type() != actual.type() || !dimensionsEqual(expected, actual)) {
throw new UnsupportedOperationException("Can not compare " + expected + " and " + actual);
}

2
modules/video/perf/perf_optflowpyrlk.cpp
View File

@ -95,7 +95,7 @@ PERF_TEST_P(Path_Idx_Cn_NPoints_WSize, OpticalFlowPyrLK_full, testing::Combine(
typedef tuple<std::string, int, tuple<int, int>, int> Path_Idx_NPoints_WSize_t;
typedef TestBaseWithParam<Path_Idx_NPoints_WSize_t> Path_Idx_NPoints_WSize;
PERF_TEST_P(Path_Idx_NPoints_WSize, OpticalFlowPyrLK_ovx, testing::Combine(
PERF_TEST_P(Path_Idx_NPoints_WSize, DISABLED_OpticalFlowPyrLK_ovx, testing::Combine(
testing::Values<std::string>("cv/optflow/frames/VGA_%02d.png", "cv/optflow/frames/720p_%02d.png"),
testing::Range(1, 3),
testing::Values(make_tuple(9, 9), make_tuple(15, 15)),

4
modules/videoio/src/cap_gstreamer.cpp
View File

@ -1590,6 +1590,10 @@ void handleMessage(GstElement * pipeline)
while(gst_bus_have_pending(bus)) {
msg = gst_bus_pop(bus);
if (!msg || !GST_IS_MESSAGE(msg))
{
continue;
}
if(gst_is_missing_plugin_message(msg))
{