Chiebot-Mirror
/
opencv
mirror of https://github.com/opencv/opencv.git
8
0
Fork 0
Code Issues Projects Releases Wiki Activity

Merge pull request #17392 from alalek:dnn_test_yolov4

Browse Source
pull/17418/head^2
Alexander Alekhin 5 years ago
parent 319db07b6b 6b89154afd
commit e58e545584
2 changed files with 113 additions and 14 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 18
      modules/dnn/perf/perf_net.cpp
  2. 109
      modules/dnn/test/test_darknet_importer.cpp

18
modules/dnn/perf/perf_net.cpp
Unescape View File

@ -197,9 +197,23 @@ PERF_TEST_P_(DNNTestNetwork, YOLOv3)
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
Mat sample = imread(findDataFile("dnn/dog416.png"));
cvtColor(sample, sample, COLOR_BGR2RGB);
Mat inp;
sample.convertTo(inp, CV_32FC3);
processNet("dnn/yolov3.weights", "dnn/yolov3.cfg", "", inp / 255);
sample.convertTo(inp, CV_32FC3, 1.0f / 255, 0);
processNet("dnn/yolov3.weights", "dnn/yolov3.cfg", "", inp);
}
PERF_TEST_P_(DNNTestNetwork, YOLOv4)
{
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
if (target == DNN_TARGET_MYRIAD)
throw SkipTestException("");
Mat sample = imread(findDataFile("dnn/dog416.png"));
cvtColor(sample, sample, COLOR_BGR2RGB);
Mat inp;
sample.convertTo(inp, CV_32FC3, 1.0f / 255, 0);
processNet("dnn/yolov4.weights", "dnn/yolov4.cfg", "", inp);
}
PERF_TEST_P_(DNNTestNetwork, EAST_text_detection)

109
modules/dnn/test/test_darknet_importer.cpp
Unescape View File

@ -245,6 +245,13 @@ public:
nms_boxes.push_back(box);
nms_confidences.push_back(conf);
nms_classIds.push_back(class_id);
#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
}
normAssertDetections(refClassIds[b], refConfidences[b], refBoxes[b], nms_classIds,
@ -395,6 +402,9 @@ TEST_P(Test_Darknet_nets_async, Accuracy)
std::string prefix = get<0>(GetParam());
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");
@ -439,7 +449,7 @@ TEST_P(Test_Darknet_nets_async, Accuracy)
}
INSTANTIATE_TEST_CASE_P(/**/, Test_Darknet_nets_async, Combine(
Values("yolo-voc", "tiny-yolo-voc", "yolov3"),
Values("yolo-voc", "tiny-yolo-voc", "yolov3", "yolov4"),
dnnBackendsAndTargets()
));
@ -453,15 +463,21 @@ TEST_P(Test_Darknet_nets, YOLOv3)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);
// batchId, classId, confidence, left, top, right, bottom
Mat ref = (Mat_<float>(9, 7) << 0, 7, 0.952983f, 0.614622f, 0.150257f, 0.901369f, 0.289251f, // a truck
0, 1, 0.987908f, 0.150913f, 0.221933f, 0.742255f, 0.74626f, // a bicycle
0, 16, 0.998836f, 0.160024f, 0.389964f, 0.417885f, 0.943716f, // a dog (COCO)
1, 9, 0.384801f, 0.659824f, 0.372389f, 0.673926f, 0.429412f, // a traffic light
1, 9, 0.733283f, 0.376029f, 0.315694f, 0.401776f, 0.395165f, // a traffic light
1, 9, 0.785352f, 0.665503f, 0.373543f, 0.688893f, 0.439245f, // a traffic light
1, 0, 0.980052f, 0.195856f, 0.378454f, 0.258626f, 0.629258f, // a person
1, 2, 0.989633f, 0.450719f, 0.463353f, 0.496305f, 0.522258f, // a car
1, 2, 0.997412f, 0.647584f, 0.459939f, 0.821038f, 0.663947f); // a car
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_);
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;
@ -480,8 +496,8 @@ TEST_P(Test_Darknet_nets, YOLOv3)
#endif
{
SCOPED_TRACE("batch size 1");
testDarknetModel(config_file, weights_file, ref.rowRange(0, 3), scoreDiff, iouDiff);
SCOPED_TRACE("batch size 1");
testDarknetModel(config_file, weights_file, ref.rowRange(0, N0), scoreDiff, iouDiff);
}
#if defined(INF_ENGINE_RELEASE)
@ -503,6 +519,75 @@ TEST_P(Test_Darknet_nets, YOLOv3)
}
}
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)
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);
}
}
INSTANTIATE_TEST_CASE_P(/**/, Test_Darknet_nets, dnnBackendsAndTargets());
TEST_P(Test_Darknet_layers, shortcut)

Write Preview
Loading…
Cancel
Save