opencv/modules/dnn/test/test_darknet_importer.cpp

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#include "test_precomp.hpp"
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#include "npy_blob.hpp"
#include <opencv2/dnn/shape_utils.hpp>
namespace opencv_test { namespace {
template<typename TString>
static std::string _tf(TString filename)
{
return (getOpenCVExtraDir() + "/dnn/") + filename;
}
TEST(Test_Darknet, read_tiny_yolo_voc)
{
Net net = readNetFromDarknet(_tf("tiny-yolo-voc.cfg"));
ASSERT_FALSE(net.empty());
}
TEST(Test_Darknet, read_yolo_voc)
{
Net net = readNetFromDarknet(_tf("yolo-voc.cfg"));
ASSERT_FALSE(net.empty());
}
TEST(Test_Darknet, read_yolo_voc_stream)
{
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applyTestTag(CV_TEST_TAG_MEMORY_1GB);
Mat ref;
Mat sample = imread(_tf("dog416.png"));
Mat inp = blobFromImage(sample, 1.0/255, Size(416, 416), Scalar(), true, false);
const std::string cfgFile = findDataFile("dnn/yolo-voc.cfg");
const std::string weightsFile = findDataFile("dnn/yolo-voc.weights", false);
// Import by paths.
{
Net net = readNetFromDarknet(cfgFile, weightsFile);
net.setInput(inp);
net.setPreferableBackend(DNN_BACKEND_OPENCV);
ref = net.forward();
}
// Import from bytes array.
{
std::vector<char> cfg, weights;
readFileContent(cfgFile, cfg);
readFileContent(weightsFile, weights);
Net net = readNetFromDarknet(cfg.data(), cfg.size(), weights.data(), weights.size());
net.setInput(inp);
net.setPreferableBackend(DNN_BACKEND_OPENCV);
Mat out = net.forward();
normAssert(ref, out);
}
}
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class Test_Darknet_layers : public DNNTestLayer
{
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public:
void testDarknetLayer(const std::string& name, bool hasWeights = false, bool testBatchProcessing = true)
{
SCOPED_TRACE(name);
Mat inp = blobFromNPY(findDataFile("dnn/darknet/" + name + "_in.npy"));
Mat ref = blobFromNPY(findDataFile("dnn/darknet/" + name + "_out.npy"));
std::string cfg = findDataFile("dnn/darknet/" + name + ".cfg");
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std::string model = "";
if (hasWeights)
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model = findDataFile("dnn/darknet/" + name + ".weights");
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checkBackend(&inp, &ref);
Net net = readNet(cfg, model);
net.setPreferableBackend(backend);
net.setPreferableTarget(target);
net.setInput(inp);
Mat out = net.forward();
normAssert(out, ref, "", default_l1, default_lInf);
if (inp.size[0] == 1 && testBatchProcessing) // test handling of batch size
{
SCOPED_TRACE("batch size 2");
#if defined(INF_ENGINE_RELEASE)
if (target == DNN_TARGET_MYRIAD && name == "shortcut")
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD);
#endif
std::vector<int> sz2 = shape(inp);
sz2[0] = 2;
Net net2 = readNet(cfg, model);
net2.setPreferableBackend(backend);
net2.setPreferableTarget(target);
Range ranges0[4] = { Range(0, 1), Range::all(), Range::all(), Range::all() };
Range ranges1[4] = { Range(1, 2), Range::all(), Range::all(), Range::all() };
Mat inp2(sz2, inp.type(), Scalar::all(0));
inp.copyTo(inp2(ranges0));
inp.copyTo(inp2(ranges1));
net2.setInput(inp2);
Mat out2 = net2.forward();
EXPECT_EQ(0, cv::norm(out2(ranges0), out2(ranges1), NORM_INF)) << "Batch result is not equal: " << name;
Mat ref2 = ref;
if (ref.dims == 2 && out2.dims == 3)
{
int ref_3d_sizes[3] = {1, ref.rows, ref.cols};
ref2 = Mat(3, ref_3d_sizes, ref.type(), (void*)ref.data);
}
/*else if (ref.dims == 3 && out2.dims == 4)
{
int ref_4d_sizes[4] = {1, ref.size[0], ref.size[1], ref.size[2]};
ref2 = Mat(4, ref_4d_sizes, ref.type(), (void*)ref.data);
}*/
ASSERT_EQ(out2.dims, ref2.dims) << ref.dims;
normAssert(out2(ranges0), ref2, "", default_l1, default_lInf);
normAssert(out2(ranges1), ref2, "", default_l1, default_lInf);
}
}
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};
class Test_Darknet_nets : public DNNTestLayer
{
public:
// Test object detection network from Darknet framework.
void testDarknetModel(const std::string& cfg, const std::string& weights,
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
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const std::vector<std::vector<int> >& refClassIds,
const std::vector<std::vector<float> >& refConfidences,
const std::vector<std::vector<Rect2d> >& refBoxes,
double scoreDiff, double iouDiff, float confThreshold = 0.24, float nmsThreshold = 0.4)
{
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checkBackend();
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
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Mat img1 = imread(_tf("dog416.png"));
Mat img2 = imread(_tf("street.png"));
std::vector<Mat> samples(2);
samples[0] = img1; samples[1] = img2;
// determine test type, whether batch or single img
int batch_size = refClassIds.size();
CV_Assert(batch_size == 1 || batch_size == 2);
samples.resize(batch_size);
Mat inp = blobFromImages(samples, 1.0/255, Size(416, 416), Scalar(), true, false);
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Net net = readNet(findDataFile("dnn/" + cfg),
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findDataFile("dnn/" + weights, false));
net.setPreferableBackend(backend);
net.setPreferableTarget(target);
net.setInput(inp);
std::vector<Mat> outs;
net.forward(outs, net.getUnconnectedOutLayersNames());
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
for (int b = 0; b < batch_size; ++b)
{
std::vector<int> classIds;
std::vector<float> confidences;
std::vector<Rect2d> boxes;
for (int i = 0; i < outs.size(); ++i)
{
Mat out;
if (batch_size > 1){
// get the sample slice from 3D matrix (batch, box, classes+5)
Range ranges[3] = {Range(b, b+1), Range::all(), Range::all()};
out = outs[i](ranges).reshape(1, outs[i].size[1]);
}else{
out = outs[i];
}
for (int j = 0; j < out.rows; ++j)
{
Mat scores = out.row(j).colRange(5, out.cols);
double confidence;
Point maxLoc;
minMaxLoc(scores, 0, &confidence, 0, &maxLoc);
if (confidence > confThreshold) {
float* detection = out.ptr<float>(j);
double centerX = detection[0];
double centerY = detection[1];
double width = detection[2];
double height = detection[3];
boxes.push_back(Rect2d(centerX - 0.5 * width, centerY - 0.5 * height,
width, height));
confidences.push_back(confidence);
classIds.push_back(maxLoc.x);
}
}
}
// here we need NMS of boxes
std::vector<int> indices;
NMSBoxes(boxes, confidences, confThreshold, nmsThreshold, indices);
std::vector<int> nms_classIds;
std::vector<float> nms_confidences;
std::vector<Rect2d> nms_boxes;
for (size_t i = 0; i < indices.size(); ++i)
{
int idx = indices[i];
Rect2d box = boxes[idx];
float conf = confidences[idx];
int class_id = classIds[idx];
nms_boxes.push_back(box);
nms_confidences.push_back(conf);
nms_classIds.push_back(class_id);
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#if 0 // use to update test reference data
std::cout << b << ", " << class_id << ", " << conf << "f, "
<< box.x << "f, " << box.y << "f, "
<< box.x + box.width << "f, " << box.y + box.height << "f,"
<< std::endl;
#endif
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
}
2020-07-04 03:14:05 +08:00
if (cvIsNaN(iouDiff))
{
if (b == 0)
std::cout << "Skip accuracy checks" << std::endl;
continue;
}
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
normAssertDetections(refClassIds[b], refConfidences[b], refBoxes[b], nms_classIds,
nms_confidences, nms_boxes, format("batch size %d, sample %d\n", batch_size, b).c_str(), confThreshold, scoreDiff, iouDiff);
}
}
void testDarknetModel(const std::string& cfg, const std::string& weights,
const std::vector<int>& refClassIds,
const std::vector<float>& refConfidences,
const std::vector<Rect2d>& refBoxes,
double scoreDiff, double iouDiff, float confThreshold = 0.24, float nmsThreshold = 0.4)
{
testDarknetModel(cfg, weights,
std::vector<std::vector<int> >(1, refClassIds),
std::vector<std::vector<float> >(1, refConfidences),
std::vector<std::vector<Rect2d> >(1, refBoxes),
scoreDiff, iouDiff, confThreshold, nmsThreshold);
}
2018-06-27 21:34:36 +08:00
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
void testDarknetModel(const std::string& cfg, const std::string& weights,
const cv::Mat& ref, double scoreDiff, double iouDiff,
float confThreshold = 0.24, float nmsThreshold = 0.4)
{
CV_Assert(ref.cols == 7);
std::vector<std::vector<int> > refClassIds;
std::vector<std::vector<float> > refScores;
std::vector<std::vector<Rect2d> > refBoxes;
for (int i = 0; i < ref.rows; ++i)
2018-04-13 23:53:12 +08:00
{
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
int batchId = static_cast<int>(ref.at<float>(i, 0));
int classId = static_cast<int>(ref.at<float>(i, 1));
float score = ref.at<float>(i, 2);
float left = ref.at<float>(i, 3);
float top = ref.at<float>(i, 4);
float right = ref.at<float>(i, 5);
float bottom = ref.at<float>(i, 6);
Rect2d box(left, top, right - left, bottom - top);
if (batchId >= refClassIds.size())
2018-06-27 21:34:36 +08:00
{
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
refClassIds.resize(batchId + 1);
refScores.resize(batchId + 1);
refBoxes.resize(batchId + 1);
2018-06-27 21:34:36 +08:00
}
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
refClassIds[batchId].push_back(classId);
refScores[batchId].push_back(score);
refBoxes[batchId].push_back(box);
}
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
testDarknetModel(cfg, weights, refClassIds, refScores, refBoxes,
scoreDiff, iouDiff, confThreshold, nmsThreshold);
}
2018-06-27 21:34:36 +08:00
};
2018-04-13 23:53:12 +08:00
TEST_P(Test_Darknet_nets, YoloVoc)
{
applyTestTag(
#if defined(OPENCV_32BIT_CONFIGURATION) && defined(HAVE_OPENCL)
CV_TEST_TAG_MEMORY_2GB,
#else
CV_TEST_TAG_MEMORY_1GB,
#endif
CV_TEST_TAG_LONG
);
2018-10-09 06:38:06 +08:00
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2020040000) // nGraph compilation failure
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
2019-04-01 20:00:25 +08:00
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16);
#endif
#if defined(INF_ENGINE_RELEASE)
if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) &&
target == DNN_TARGET_MYRIAD && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X); // need to update check function
#endif
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
// batchId, classId, confidence, left, top, right, bottom
Mat ref = (Mat_<float>(6, 7) << 0, 6, 0.750469f, 0.577374f, 0.127391f, 0.902949f, 0.300809f, // a car
0, 1, 0.780879f, 0.270762f, 0.264102f, 0.732475f, 0.745412f, // a bicycle
0, 11, 0.901615f, 0.1386f, 0.338509f, 0.421337f, 0.938789f, // a dog
1, 14, 0.623813f, 0.183179f, 0.381921f, 0.247726f, 0.625847f, // a person
1, 6, 0.667770f, 0.446555f, 0.453578f, 0.499986f, 0.519167f, // a car
1, 6, 0.844947f, 0.637058f, 0.460398f, 0.828508f, 0.66427f); // a car
2018-06-27 21:34:36 +08:00
double scoreDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 1e-2 : 8e-5;
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
double iouDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.018 : 3e-4;
double nmsThreshold = (target == DNN_TARGET_MYRIAD) ? 0.397 : 0.4;
std::string config_file = "yolo-voc.cfg";
std::string weights_file = "yolo-voc.weights";
{
SCOPED_TRACE("batch size 1");
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
testDarknetModel(config_file, weights_file, ref.rowRange(0, 3), scoreDiff, iouDiff);
}
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
{
SCOPED_TRACE("batch size 2");
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
testDarknetModel(config_file, weights_file, ref, scoreDiff, iouDiff, 0.24, nmsThreshold);
}
}
2018-04-13 23:53:12 +08:00
TEST_P(Test_Darknet_nets, TinyYoloVoc)
{
2018-10-09 06:38:06 +08:00
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2020040000) // nGraph compilation failure
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
#if defined(INF_ENGINE_RELEASE)
if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 || backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) &&
target == DNN_TARGET_MYRIAD && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X); // need to update check function
#endif
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
// batchId, classId, confidence, left, top, right, bottom
Mat ref = (Mat_<float>(4, 7) << 0, 6, 0.761967f, 0.579042f, 0.159161f, 0.894482f, 0.31994f, // a car
0, 11, 0.780595f, 0.129696f, 0.386467f, 0.445275f, 0.920994f, // a dog
1, 6, 0.651450f, 0.460526f, 0.458019f, 0.522527f, 0.5341f, // a car
1, 6, 0.928758f, 0.651024f, 0.463539f, 0.823784f, 0.654998f); // a car
2018-06-27 21:34:36 +08:00
double scoreDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 8e-3 : 8e-5;
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
double iouDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.018 : 3e-4;
std::string config_file = "tiny-yolo-voc.cfg";
std::string weights_file = "tiny-yolo-voc.weights";
{
SCOPED_TRACE("batch size 1");
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
testDarknetModel(config_file, weights_file, ref.rowRange(0, 2), scoreDiff, iouDiff);
}
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
{
SCOPED_TRACE("batch size 2");
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
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testDarknetModel(config_file, weights_file, ref, scoreDiff, iouDiff);
}
}
#ifdef HAVE_INF_ENGINE
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static const std::chrono::milliseconds async_timeout(10000);
typedef testing::TestWithParam<tuple<std::string, tuple<Backend, Target> > > Test_Darknet_nets_async;
TEST_P(Test_Darknet_nets_async, Accuracy)
{
Backend backendId = get<0>(get<1>(GetParam()));
Target targetId = get<1>(get<1>(GetParam()));
if (INF_ENGINE_VER_MAJOR_LT(2019020000) && backendId == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);
std::string prefix = get<0>(GetParam());
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if (targetId == DNN_TARGET_MYRIAD && prefix == "yolov4") // NC_OUT_OF_MEMORY
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
if (backendId != DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && backendId != DNN_BACKEND_INFERENCE_ENGINE_NGRAPH)
throw SkipTestException("No support for async forward");
const int numInputs = 2;
std::vector<Mat> inputs(numInputs);
int blobSize[] = {1, 3, 416, 416};
for (int i = 0; i < numInputs; ++i)
{
inputs[i].create(4, &blobSize[0], CV_32F);
randu(inputs[i], 0, 1);
}
Net netSync = readNet(findDataFile("dnn/" + prefix + ".cfg"),
findDataFile("dnn/" + prefix + ".weights", false));
netSync.setPreferableBackend(backendId);
netSync.setPreferableTarget(targetId);
// Run synchronously.
std::vector<Mat> refs(numInputs);
for (int i = 0; i < numInputs; ++i)
{
netSync.setInput(inputs[i]);
refs[i] = netSync.forward().clone();
}
Net netAsync = readNet(findDataFile("dnn/" + prefix + ".cfg"),
findDataFile("dnn/" + prefix + ".weights", false));
netAsync.setPreferableBackend(backendId);
netAsync.setPreferableTarget(targetId);
// Run asynchronously. To make test more robust, process inputs in the reversed order.
for (int i = numInputs - 1; i >= 0; --i)
{
netAsync.setInput(inputs[i]);
AsyncArray out = netAsync.forwardAsync();
ASSERT_TRUE(out.valid());
Mat result;
EXPECT_TRUE(out.get(result, async_timeout));
normAssert(refs[i], result, format("Index: %d", i).c_str(), 0, 0);
}
}
INSTANTIATE_TEST_CASE_P(/**/, Test_Darknet_nets_async, Combine(
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Values("yolo-voc", "tiny-yolo-voc", "yolov3", "yolov4", "yolov4-tiny"),
dnnBackendsAndTargets()
));
#endif
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TEST_P(Test_Darknet_nets, YOLOv3)
{
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applyTestTag(CV_TEST_TAG_LONG, (target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_1GB : CV_TEST_TAG_MEMORY_2GB));
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2020040000) // nGraph compilation failure
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
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if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
// batchId, classId, confidence, left, top, right, bottom
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const int N0 = 3;
const int N1 = 6;
static const float ref_[/* (N0 + N1) * 7 */] = {
0, 16, 0.998836f, 0.160024f, 0.389964f, 0.417885f, 0.943716f,
0, 1, 0.987908f, 0.150913f, 0.221933f, 0.742255f, 0.746261f,
0, 7, 0.952983f, 0.614621f, 0.150257f, 0.901368f, 0.289251f,
1, 2, 0.997412f, 0.647584f, 0.459939f, 0.821037f, 0.663947f,
1, 2, 0.989633f, 0.450719f, 0.463353f, 0.496306f, 0.522258f,
1, 0, 0.980053f, 0.195856f, 0.378454f, 0.258626f, 0.629257f,
1, 9, 0.785341f, 0.665503f, 0.373543f, 0.688893f, 0.439244f,
1, 9, 0.733275f, 0.376029f, 0.315694f, 0.401776f, 0.395165f,
1, 9, 0.384815f, 0.659824f, 0.372389f, 0.673927f, 0.429412f,
};
Mat ref(N0 + N1, 7, CV_32FC1, (void*)ref_);
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
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double scoreDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.006 : 8e-5;
double iouDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.042 : 3e-4;
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
std::string config_file = "yolov3.cfg";
std::string weights_file = "yolov3.weights";
#if defined(INF_ENGINE_RELEASE)
if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 ||
backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_MYRIAD &&
getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
{
scoreDiff = 0.04;
iouDiff = 0.2;
}
#endif
{
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SCOPED_TRACE("batch size 1");
testDarknetModel(config_file, weights_file, ref.rowRange(0, N0), scoreDiff, iouDiff);
}
#if defined(INF_ENGINE_RELEASE)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
{
if (target == DNN_TARGET_OPENCL)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
else if (target == DNN_TARGET_OPENCL_FP16 && INF_ENGINE_VER_MAJOR_LE(202010000))
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
else if (target == DNN_TARGET_MYRIAD &&
getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X);
}
#endif
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
2018-09-12 18:29:43 +08:00
{
SCOPED_TRACE("batch size 2");
Merge pull request #12249 from kopytjuk:feature/region-layer-batch-mode Feature/region layer batch mode (#12249) * Add batch mode for Darknet networks. Swap variables in test_darknet. Adapt reorg layer to batch mode. Adapt region layer. Add OpenCL implementation. Remove trailing whitespace. Bugifx reorg opencl implementation. Fix bug in OpenCL reorg. Fix modulo bug. Fix bug. Reorg openCL. Restore reorg layer opencl code. OpenCl fix. Work on openCL reorg. Remove whitespace. Fix openCL region layer implementation. Fix bug. Fix softmax region opencl bug. Fix opencl bug. Fix openCL bug. Update aff_trans.cpp When the fullAffine parameter is set to false, the estimateRigidTransform function maybe return empty, then the _localAffineEstimate function will be called, but the bug in it will result in incorrect results. core(libva): support YV12 too Added to CPU path only. OpenCL code path still expects NV12 only (according to Intel OpenCL extension) cmake: allow to specify own libva paths via CMake: - `-DVA_LIBRARIES=/opt/intel/mediasdk/lib64/libva.so.2\;/opt/intel/mediasdk/lib64/libva-drm.so.2` android: NDK17 support tested with NDK 17b (17.1.4828580) Enable more deep learning tests using Intel's Inference Engine backend ts: don't pass NULL for std::string() constructor openvino: use 2018R3 defines experimental version++ OpenCV version++ OpenCV 3.4.3 OpenCV version '-openvino' openvino: use 2018R3 defines Fixed windows build with InferenceEngine dnn: fix variance setting bug for PriorBoxLayer - The size of second channel should be size[2] of output tensor, - The Scalar should be {variance[0], variance[0], variance[0], variance[0]} for _variance.size() == 1 case. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Fix lifetime of networks which are loaded from Model Optimizer IRs Adds a small note describing BUILD_opencv_world (#12332) * Added a mall note describing BUILD_opencv_world cmake option to the Installation in Windows tutorial. * Made slight changes in BUILD_opencv_world documentation. * Update windows_install.markdown improved grammar Update opengl_interop.cpp resolves #12307 java: fix LIST_GET macro fix typo Added option to fail on missing testdata Fixed that object_detection.py does not work in python3. cleanup: IPP Async (IPP_A) except header file with conversion routines (will be removed in OpenCV 4.0) imgcodecs: add null pointer check Include preprocessing nodes to object detection TensorFlow networks (#12211) * Include preprocessing nodes to object detection TensorFlow networks * Enable more fusion * faster_rcnn_resnet50_coco_2018_01_28 test countNonZero function reworked to use wide universal intrinsics instead of SSE2 intrinsics resolve #5788 imgcodecs(webp): multiple fixes - don't reallocate passed 'img' (test fixed - must use IMREAD_UNCHANGED / IMREAD_ANYCOLOR) - avoid memory DDOS - avoid reading of whole file during header processing - avoid data access after allocated buffer during header processing (missing checks) - use WebPFree() to free allocated buffers (libwebp >= 0.5.0) - drop unused & undefined `.close()` method - added checks for channels >= 5 in encoder ml: fix adjusting K in KNearest (#12358) dnn(perf): fix and merge Convolution tests - OpenCL tests didn't run any OpenCL kernels - use real configuration from existed models (the first 100 cases) - batch size = 1 dnn(test): use dnnBackendsAndTargets() param generator Bit-exact resize reworked to use wide intrinsics (#12038) * Bit-exact resize reworked to use wide intrinsics * Reworked bit-exact resize row data loading * Added bit-exact resize row data loaders for SIMD256 and SIMD512 * Fixed type punned pointer dereferencing warning * Reworked loading of source data for SIMD256 and SIMD512 bit-exact resize Bit-exact GaussianBlur reworked to use wide intrinsics (#12073) * Bit-exact GaussianBlur reworked to use wide intrinsics * Added v_mul_hi universal intrinsic * Removed custom SSE2 branch from bit-exact GaussianBlur * Removed loop unrolling for gaussianBlur horizontal smoothing doc: fix English gramma in tutorial out-of-focus-deblur filter (#12214) * doc: fix English gramma in tutorial out-of-focus-deblur filter * Update out_of_focus_deblur_filter.markdown slightly modified one sentence doc: add new tutorial motion deblur filter (#12215) * doc: add new tutorial motion deblur filter * Update motion_deblur_filter.markdown a few minor changes Replace Slice layer to Crop in Faster-RCNN networks from Caffe js: use generated list of OpenCV headers - replaces hand-written list imgcodecs(webp): use safe cast to size_t on Win32 * Put Version status back to -dev. follow the common codestyle Exclude some target engines. Refactor formulas. Refactor code. * Remove unused variable. * Remove inference engine check for yolov2. * Alter darknet batch tests to test with two different images. * Add yolov3 second image GT. * Fix bug. * Fix bug. * Add second test. * Remove comment. * Add NMS on network level. * Add helper files to dev. * syntax fix. * Fix OD sample. Fix sample dnn object detection. Fix NMS boxes bug. remove trailing whitespace. Remove debug function. Change thresholds for opencl tests. * Adapt score diff and iou diff. * Alter iouDiffs. * Add debug messages. * Adapt iouDiff. * Fix tests
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testDarknetModel(config_file, weights_file, ref, scoreDiff, iouDiff);
}
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}
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TEST_P(Test_Darknet_nets, YOLOv4)
{
applyTestTag(CV_TEST_TAG_LONG, (target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_1GB : CV_TEST_TAG_MEMORY_2GB));
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2020040000) // nGraph compilation failure
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
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#if defined(INF_ENGINE_RELEASE)
if (target == DNN_TARGET_MYRIAD) // NC_OUT_OF_MEMORY
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
// batchId, classId, confidence, left, top, right, bottom
const int N0 = 3;
const int N1 = 7;
static const float ref_[/* (N0 + N1) * 7 */] = {
0, 16, 0.992194f, 0.172375f, 0.402458f, 0.403918f, 0.932801f,
0, 1, 0.988326f, 0.166708f, 0.228236f, 0.737208f, 0.735803f,
0, 7, 0.94639f, 0.602523f, 0.130399f, 0.901623f, 0.298452f,
1, 2, 0.99761f, 0.646556f, 0.45985f, 0.816041f, 0.659067f,
1, 0, 0.988913f, 0.201726f, 0.360282f, 0.266181f, 0.631728f,
1, 2, 0.98233f, 0.452007f, 0.462217f, 0.495612f, 0.521687f,
1, 9, 0.919195f, 0.374642f, 0.316524f, 0.398126f, 0.393714f,
1, 9, 0.856303f, 0.666842f, 0.372215f, 0.685539f, 0.44141f,
1, 9, 0.313516f, 0.656791f, 0.374734f, 0.671959f, 0.438371f,
1, 9, 0.256625f, 0.940232f, 0.326931f, 0.967586f, 0.374002f,
};
Mat ref(N0 + N1, 7, CV_32FC1, (void*)ref_);
double scoreDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.006 : 8e-5;
double iouDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.042 : 3e-4;
std::string config_file = "yolov4.cfg";
std::string weights_file = "yolov4.weights";
#if defined(INF_ENGINE_RELEASE)
if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 ||
backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_MYRIAD &&
getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
{
scoreDiff = 0.04;
iouDiff = 0.2;
}
#endif
{
SCOPED_TRACE("batch size 1");
testDarknetModel(config_file, weights_file, ref.rowRange(0, N0), scoreDiff, iouDiff);
}
{
SCOPED_TRACE("batch size 2");
#if defined(INF_ENGINE_RELEASE)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
{
if (target == DNN_TARGET_OPENCL)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
else if (target == DNN_TARGET_OPENCL_FP16 && INF_ENGINE_VER_MAJOR_LE(202010000))
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
else if (target == DNN_TARGET_MYRIAD &&
getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X);
}
#endif
testDarknetModel(config_file, weights_file, ref, scoreDiff, iouDiff);
}
}
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TEST_P(Test_Darknet_nets, YOLOv4_tiny)
{
applyTestTag(
target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB
);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2021010000) // nGraph compilation failure
if (target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
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const double confThreshold = 0.5;
// batchId, classId, confidence, left, top, right, bottom
const int N0 = 2;
const int N1 = 3;
static const float ref_[/* (N0 + N1) * 7 */] = {
0, 7, 0.85935f, 0.593484f, 0.141211f, 0.920356f, 0.291593f,
0, 16, 0.795188f, 0.169207f, 0.386886f, 0.423753f, 0.933004f,
1, 2, 0.996832f, 0.653802f, 0.464573f, 0.815193f, 0.653292f,
1, 2, 0.963325f, 0.451151f, 0.458915f, 0.496255f, 0.52241f,
1, 0, 0.926244f, 0.194851f, 0.361743f, 0.260277f, 0.632364f,
};
Mat ref(N0 + N1, 7, CV_32FC1, (void*)ref_);
double scoreDiff = 0.01f;
double iouDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.15 : 0.01f;
std::string config_file = "yolov4-tiny.cfg";
std::string weights_file = "yolov4-tiny.weights";
#if defined(INF_ENGINE_RELEASE)
if (target == DNN_TARGET_MYRIAD) // bad accuracy
iouDiff = std::numeric_limits<double>::quiet_NaN();
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_OPENCL)
iouDiff = std::numeric_limits<double>::quiet_NaN();
if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 ||
backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_OPENCL_FP16)
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iouDiff = std::numeric_limits<double>::quiet_NaN();
#endif
{
SCOPED_TRACE("batch size 1");
testDarknetModel(config_file, weights_file, ref.rowRange(0, N0), scoreDiff, iouDiff, confThreshold);
}
{
SCOPED_TRACE("batch size 2");
testDarknetModel(config_file, weights_file, ref, scoreDiff, iouDiff, confThreshold);
}
#if defined(INF_ENGINE_RELEASE)
if (target == DNN_TARGET_MYRIAD) // bad accuracy
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_OPENCL)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 ||
backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_OPENCL_FP16)
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applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
}
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INSTANTIATE_TEST_CASE_P(/**/, Test_Darknet_nets, dnnBackendsAndTargets());
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TEST_P(Test_Darknet_layers, shortcut)
{
testDarknetLayer("shortcut");
testDarknetLayer("shortcut_leaky");
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testDarknetLayer("shortcut_unequal");
testDarknetLayer("shortcut_unequal_2");
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}
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TEST_P(Test_Darknet_layers, upsample)
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{
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testDarknetLayer("upsample");
}
TEST_P(Test_Darknet_layers, mish)
{
testDarknetLayer("mish", true);
}
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TEST_P(Test_Darknet_layers, avgpool_softmax)
{
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testDarknetLayer("avgpool_softmax");
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}
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TEST_P(Test_Darknet_layers, region)
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{
#if defined(INF_ENGINE_RELEASE)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && INF_ENGINE_VER_MAJOR_GE(2020020000))
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
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testDarknetLayer("region");
}
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TEST_P(Test_Darknet_layers, reorg)
{
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testDarknetLayer("reorg");
}
TEST_P(Test_Darknet_layers, route)
{
testDarknetLayer("route");
testDarknetLayer("route_multi");
}
TEST_P(Test_Darknet_layers, maxpool)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2020020000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
#endif
testDarknetLayer("maxpool");
}
TEST_P(Test_Darknet_layers, convolutional)
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{
if (target == DNN_TARGET_MYRIAD)
{
default_l1 = 0.01f;
}
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testDarknetLayer("convolutional", true);
}
TEST_P(Test_Darknet_layers, scale_channels)
{
// TODO: test fails for batches due to a bug/missing feature in ScaleLayer
testDarknetLayer("scale_channels", false, false);
}
TEST_P(Test_Darknet_layers, connected)
{
if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16);
testDarknetLayer("connected", true);
}
TEST_P(Test_Darknet_layers, relu)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD);
testDarknetLayer("relu");
}
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INSTANTIATE_TEST_CASE_P(/**/, Test_Darknet_layers, dnnBackendsAndTargets());
}} // namespace