mirror/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2024-11-28 21:20:18 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

Merge pull request #11551 from take1014:filter2d_10683

Browse Source 
* Add arguments to dftFilter2D

* test: add expected test values
This commit is contained in:
yuki takehara 2018-05-24 05:25:11 +09:00 committed by Alexander Alekhin
parent 1923916929
commit 2d5d98ec0f
2 changed files with 85 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

18
modules/imgproc/src/filter.cpp
View File

@ -4643,7 +4643,8 @@ static bool ippFilter2D(int stype, int dtype, int kernel_type,
static bool dftFilter2D(int stype, int dtype, int kernel_type,
uchar * src_data, size_t src_step,
uchar * dst_data, size_t dst_step,
int width, int height,
int full_width, int full_height,
int offset_x, int offset_y,
uchar * kernel_data, size_t kernel_step,
int kernel_width, int kernel_height,
int anchor_x, int anchor_y,
@ -4666,8 +4667,8 @@ static bool dftFilter2D(int stype, int dtype, int kernel_type,
Point anchor = Point(anchor_x, anchor_y);
Mat kernel = Mat(Size(kernel_width, kernel_height), kernel_type, kernel_data, kernel_step);
Mat src(Size(width, height), stype, src_data, src_step);
Mat dst(Size(width, height), dtype, dst_data, dst_step);
Mat src(Size(full_width-offset_x, full_height-offset_y), stype, src_data, src_step);
Mat dst(Size(full_width, full_height), dtype, dst_data, dst_step);
Mat temp;
int src_channels = CV_MAT_CN(stype);
int dst_channels = CV_MAT_CN(dtype);
@ -4680,10 +4681,10 @@ static bool dftFilter2D(int stype, int dtype, int kernel_type,
// we just use that.
int corrDepth = ddepth;
if ((ddepth == CV_32F || ddepth == CV_64F) && src_data != dst_data) {
temp = Mat(Size(width, height), dtype, dst_data, dst_step);
temp = Mat(Size(full_width, full_height), dtype, dst_data, dst_step);
} else {
corrDepth = ddepth == CV_64F ? CV_64F : CV_32F;
temp.create(Size(width, height), CV_MAKETYPE(corrDepth, dst_channels));
temp.create(Size(full_width, full_height), CV_MAKETYPE(corrDepth, dst_channels));
}
crossCorr(src, kernel, temp, src.size(),
CV_MAKETYPE(corrDepth, src_channels),
@ -4694,9 +4695,9 @@ static bool dftFilter2D(int stype, int dtype, int kernel_type,
}
} else {
if (src_data != dst_data)
temp = Mat(Size(width, height), dtype, dst_data, dst_step);
temp = Mat(Size(full_width, full_height), dtype, dst_data, dst_step);
else
temp.create(Size(width, height), dtype);
temp.create(Size(full_width, full_height), dtype);
crossCorr(src, kernel, temp, src.size(),
CV_MAKETYPE(ddepth, src_channels),
anchor, delta, borderType);
@ -4830,7 +4831,8 @@ void filter2D(int stype, int dtype, int kernel_type,
res = dftFilter2D(stype, dtype, kernel_type,
src_data, src_step,
dst_data, dst_step,
width, height,
full_width, full_height,
offset_x, offset_y,
kernel_data, kernel_step,
kernel_width, kernel_height,
anchor_x, anchor_y,

75
modules/imgproc/test/test_filter.cpp
View File

@ -2119,4 +2119,79 @@ TEST(Imgproc_MorphEx, hitmiss_zero_kernel)
ASSERT_DOUBLE_EQ(cvtest::norm(dst, src, NORM_INF), 0.);
}
TEST(Imgproc_Filter2D, dftFilter2d_regression_10683)
{
uchar src_[24*24] = {
0, 40, 0, 0, 255, 0, 0, 78, 131, 0, 196, 0, 255, 0, 0, 0, 0, 255, 70, 0, 255, 0, 0, 0,
0, 0, 255, 204, 0, 0, 255, 93, 255, 0, 0, 255, 12, 0, 0, 0, 255, 121, 0, 255, 0, 0, 0, 255,
0, 178, 0, 25, 67, 0, 165, 0, 255, 0, 0, 181, 151, 175, 0, 0, 32, 0, 0, 255, 165, 93, 0, 255,
255, 255, 0, 0, 255, 126, 0, 0, 0, 0, 133, 29, 9, 0, 220, 255, 0, 142, 255, 255, 255, 0, 255, 0,
255, 32, 255, 0, 13, 237, 0, 0, 0, 0, 0, 19, 90, 0, 0, 85, 122, 62, 95, 29, 255, 20, 0, 0,
0, 0, 166, 41, 0, 48, 70, 0, 68, 0, 255, 0, 139, 7, 63, 144, 0, 204, 0, 0, 0, 98, 114, 255,
105, 0, 0, 0, 0, 255, 91, 0, 73, 0, 255, 0, 0, 0, 255, 198, 21, 0, 0, 0, 255, 43, 153, 128,
0, 98, 26, 0, 101, 0, 0, 0, 255, 0, 0, 0, 255, 77, 56, 0, 241, 0, 169, 132, 0, 255, 186, 255,
255, 87, 0, 1, 0, 0, 10, 39, 120, 0, 23, 69, 207, 0, 0, 0, 0, 84, 0, 0, 0, 0, 255, 0,
255, 0, 0, 136, 255, 77, 247, 0, 67, 0, 15, 255, 0, 143, 0, 243, 255, 0, 0, 238, 255, 0, 255, 8,
42, 0, 0, 255, 29, 0, 0, 0, 255, 255, 255, 75, 0, 0, 0, 255, 0, 0, 255, 38, 197, 0, 255, 87,
0, 123, 17, 0, 234, 0, 0, 149, 0, 0, 255, 16, 0, 0, 0, 255, 0, 255, 0, 38, 0, 114, 255, 76,
0, 0, 8, 0, 255, 0, 0, 0, 220, 0, 11, 255, 0, 0, 55, 98, 0, 0, 0, 255, 0, 175, 255, 110,
235, 0, 175, 0, 255, 227, 38, 206, 0, 0, 255, 246, 0, 0, 123, 183, 255, 0, 0, 255, 0, 156, 0, 54,
0, 255, 0, 202, 0, 0, 0, 0, 157, 0, 255, 63, 0, 0, 0, 0, 0, 255, 132, 0, 255, 0, 0, 0,
0, 0, 0, 255, 0, 0, 128, 126, 0, 243, 46, 7, 0, 211, 108, 166, 0, 0, 162, 227, 0, 204, 0, 51,
255, 216, 0, 0, 43, 0, 255, 40, 188, 188, 255, 0, 0, 255, 34, 0, 0, 168, 0, 0, 0, 35, 0, 0,
0, 80, 131, 255, 0, 255, 10, 0, 0, 0, 180, 255, 209, 255, 173, 34, 0, 66, 0, 49, 0, 255, 83, 0,
0, 204, 0, 91, 0, 0, 0, 205, 84, 0, 0, 0, 92, 255, 91, 0, 126, 0, 185, 145, 0, 0, 9, 0,
255, 0, 0, 255, 255, 0, 0, 255, 0, 0, 216, 0, 187, 221, 0, 0, 141, 0, 0, 209, 0, 0, 255, 0,
255, 0, 0, 154, 150, 0, 0, 0, 148, 0, 201, 255, 0, 255, 16, 0, 0, 160, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 255, 0, 255, 0, 255, 0, 255, 198, 255, 147, 131, 0, 255, 202, 0, 0, 0, 0, 255, 0,
0, 0, 0, 164, 181, 0, 0, 0, 69, 255, 31, 0, 255, 195, 0, 0, 255, 164, 109, 0, 0, 202, 0, 206,
0, 0, 61, 235, 33, 255, 77, 0, 0, 0, 0, 85, 0, 228, 0, 0, 0, 0, 255, 0, 0, 5, 255, 255
};
Mat_<uchar> src(24, 24, src_);
Mat dst = Mat::zeros(src.size(), src.type());
int sz = 12, size2 = sz * sz;
Mat kernel = Mat::ones(sz, sz, CV_32F) / size2;
uchar expected_[24*24] = {
83, 83, 77, 80, 76, 76, 76, 75, 71, 67, 72, 71, 73, 70, 80, 83, 86, 84, 89, 88, 88, 96, 99, 98,
83, 83, 77, 80, 76, 76, 76, 75, 71, 67, 72, 71, 73, 70, 80, 83, 86, 84, 89, 88, 88, 96, 99, 98,
82, 82, 77, 80, 77, 75, 74, 75, 70, 68, 71, 72, 72, 72, 82, 84, 88, 88, 93, 92, 93, 100, 105, 104,
76, 76, 72, 77, 73, 74, 73, 74, 69, 68, 71, 71, 73, 72, 82, 81, 86, 87, 92, 91, 92, 98, 103, 102,
75, 75, 72, 77, 73, 72, 75, 76, 74, 71, 73, 75, 76, 72, 81, 80, 85, 87, 90, 89, 90, 97, 102, 97,
74, 74, 71, 77, 72, 74, 77, 76, 74, 72, 74, 76, 77, 76, 84, 83, 85, 87, 90, 92, 93, 100, 102, 99,
72, 72, 69, 71, 68, 73, 73, 73, 70, 69, 74, 72, 75, 75, 81, 82, 85, 87, 90, 94, 96, 103, 102, 101,
71, 71, 68, 70, 68, 71, 73, 71, 69, 68, 74, 72, 73, 73, 81, 80, 84, 89, 91, 99, 102, 107, 106, 105,
74, 74, 70, 69, 67, 73, 76, 72, 69, 70, 79, 75, 74, 75, 82, 83, 88, 91, 92, 100, 104, 108, 106, 105,
75, 75, 71, 70, 67, 75, 76, 71, 67, 68, 75, 72, 72, 75, 81, 83, 87, 89, 89, 97, 102, 107, 103, 103,
69, 69, 67, 67, 65, 72, 74, 71, 70, 70, 75, 74, 74, 75, 80, 80, 84, 85, 85, 92, 96, 100, 97, 97,
67, 67, 67, 68, 67, 77, 79, 75, 74, 76, 81, 78, 81, 80, 84, 81, 84, 83, 83, 91, 94, 95, 93, 93,
73, 73, 71, 73, 70, 80, 82, 79, 80, 83, 85, 82, 82, 82, 87, 84, 88, 87, 84, 91, 93, 94, 93, 92,
72, 72, 74, 75, 71, 80, 81, 79, 80, 82, 82, 80, 82, 84, 88, 83, 87, 87, 83, 88, 88, 89, 90, 90,
78, 78, 81, 80, 74, 84, 86, 82, 85, 86, 85, 81, 83, 83, 86, 84, 85, 84, 78, 85, 82, 83, 85, 84,
81, 81, 84, 81, 75, 86, 90, 85, 89, 91, 89, 84, 86, 87, 90, 87, 89, 85, 78, 84, 79, 80, 81, 81,
76, 76, 80, 79, 73, 86, 90, 87, 92, 95, 92, 87, 91, 92, 93, 87, 89, 84, 77, 81, 76, 74, 76, 76,
77, 77, 80, 77, 72, 83, 86, 86, 93, 95, 91, 87, 92, 92, 93, 87, 90, 84, 79, 79, 75, 72, 75, 72,
80, 80, 81, 79, 72, 82, 86, 86, 95, 97, 89, 87, 89, 89, 91, 85, 88, 84, 79, 80, 73, 69, 74, 73,
82, 82, 82, 80, 74, 83, 86, 87, 98, 100, 90, 90, 93, 94, 94, 89, 90, 84, 82, 79, 71, 68, 72, 69,
76, 76, 77, 76, 70, 81, 83, 88, 99, 102, 92, 91, 97, 97, 97, 90, 90, 86, 83, 81, 70, 67, 70, 68,
75, 75, 76, 74, 69, 79, 84, 88, 102, 106, 95, 94, 99, 98, 98, 90, 89, 86, 82, 79, 67, 62, 65, 62,
80, 80, 82, 78, 71, 82, 87, 90, 105, 108, 96, 94, 99, 98, 97, 88, 88, 85, 81, 79, 65, 61, 65, 60,
77, 77, 80, 75, 66, 76, 81, 87, 102, 105, 92, 91, 95, 97, 96, 88, 89, 88, 84, 81, 67, 63, 68, 63
};
Mat_<uchar> expected(24, 24, expected_);
for(int r = 0; r < src.rows / 3; ++r)
{
for(int c = 0; c < src.cols / 3; ++c)
{
cv::Rect region(c * 3, r * 3, 3, 3);
Mat roi_i(src, region);
Mat roi_o(dst, region);
cv::filter2D(roi_i, roi_o, -1, kernel);
}
}
EXPECT_LE(cvtest::norm(dst, expected, NORM_INF), 2);
}
}} // namespace