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Commit e0841f3d authored by Alexander Alekhin's avatar Alexander Alekhin
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dnn(test-tags): add time / memory tags

parent b38de57f
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Showing with 65 additions and 12 deletions
modules/dnn/test/test_backends.cpp
View file @ e0841f3d
......@@ -98,6 +98,7 @@ public:
TEST_P(DNNTestNetwork, AlexNet)
{
applyTestTag(CV_TEST_TAG_MEMORY_1GB);
processNet("dnn/bvlc_alexnet.caffemodel", "dnn/bvlc_alexnet.prototxt",
Size(227, 227), "prob",
target == DNN_TARGET_OPENCL ? "dnn/halide_scheduler_opencl_alexnet.yml" :
......@@ -106,6 +107,7 @@ TEST_P(DNNTestNetwork, AlexNet)
TEST_P(DNNTestNetwork, ResNet_50)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
processNet("dnn/ResNet-50-model.caffemodel", "dnn/ResNet-50-deploy.prototxt",
Size(224, 224), "prob",
target == DNN_TARGET_OPENCL ? "dnn/halide_scheduler_opencl_resnet_50.yml" :
......@@ -122,12 +124,14 @@ TEST_P(DNNTestNetwork, SqueezeNet_v1_1)
TEST_P(DNNTestNetwork, GoogLeNet)
{
applyTestTag(target == DNN_TARGET_CPU ? "" : CV_TEST_TAG_MEMORY_512MB);
processNet("dnn/bvlc_googlenet.caffemodel", "dnn/bvlc_googlenet.prototxt",
Size(224, 224), "prob");
}
TEST_P(DNNTestNetwork, Inception_5h)
{
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
double l1 = default_l1, lInf = default_lInf;
if (backend == DNN_BACKEND_INFERENCE_ENGINE && (target == DNN_TARGET_CPU || target == DNN_TARGET_OPENCL))
{
......@@ -142,6 +146,7 @@ TEST_P(DNNTestNetwork, Inception_5h)
TEST_P(DNNTestNetwork, ENet)
{
applyTestTag(target == DNN_TARGET_CPU ? "" : CV_TEST_TAG_MEMORY_512MB);
if ((backend == DNN_BACKEND_INFERENCE_ENGINE) ||
(backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16))
throw SkipTestException("");
......@@ -153,6 +158,7 @@ TEST_P(DNNTestNetwork, ENet)
TEST_P(DNNTestNetwork, MobileNet_SSD_Caffe)
{
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
Mat sample = imread(findDataFile("dnn/street.png", false));
......@@ -184,6 +190,7 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_Caffe_Different_Width_Height)
TEST_P(DNNTestNetwork, MobileNet_SSD_v1_TensorFlow)
{
applyTestTag(target == DNN_TARGET_CPU ? "" : CV_TEST_TAG_MEMORY_512MB);
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
Mat sample = imread(findDataFile("dnn/street.png", false));
......@@ -214,6 +221,7 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_v1_TensorFlow_Different_Width_Height)
TEST_P(DNNTestNetwork, MobileNet_SSD_v2_TensorFlow)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
Mat sample = imread(findDataFile("dnn/street.png", false));
......@@ -226,6 +234,8 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_v2_TensorFlow)
TEST_P(DNNTestNetwork, SSD_VGG16)
{
applyTestTag(CV_TEST_TAG_LONG, (target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_1GB : CV_TEST_TAG_MEMORY_2GB),
CV_TEST_TAG_DEBUG_VERYLONG);
if (backend == DNN_BACKEND_HALIDE && target == DNN_TARGET_CPU)
throw SkipTestException("");
double scoreThreshold = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.0325 : 0.0;
......@@ -238,6 +248,8 @@ TEST_P(DNNTestNetwork, SSD_VGG16)
TEST_P(DNNTestNetwork, OpenPose_pose_coco)
{
applyTestTag(CV_TEST_TAG_LONG, (target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_1GB : CV_TEST_TAG_MEMORY_2GB),
CV_TEST_TAG_DEBUG_VERYLONG);
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LE(2018050000)
......@@ -254,6 +266,8 @@ TEST_P(DNNTestNetwork, OpenPose_pose_coco)
TEST_P(DNNTestNetwork, OpenPose_pose_mpi)
{
applyTestTag(CV_TEST_TAG_LONG, (target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_1GB : CV_TEST_TAG_MEMORY_2GB),
CV_TEST_TAG_DEBUG_VERYLONG);
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LE(2018050000)
......@@ -270,6 +284,7 @@ TEST_P(DNNTestNetwork, OpenPose_pose_mpi)
TEST_P(DNNTestNetwork, OpenPose_pose_mpi_faster_4_stages)
{
applyTestTag(CV_TEST_TAG_LONG, CV_TEST_TAG_MEMORY_1GB);
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LE(2018050000)
......@@ -318,6 +333,7 @@ TEST_P(DNNTestNetwork, opencv_face_detector)
TEST_P(DNNTestNetwork, Inception_v2_SSD_TensorFlow)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
#if defined(INF_ENGINE_RELEASE)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
......@@ -335,6 +351,7 @@ TEST_P(DNNTestNetwork, Inception_v2_SSD_TensorFlow)
TEST_P(DNNTestNetwork, DenseNet_121)
{
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
// Reference output values are in range [-3.807, 4.605]
......
modules/dnn/test/test_caffe_importer.cpp
View file @ e0841f3d
......@@ -112,6 +112,8 @@ TEST(Test_Caffe, read_googlenet)
typedef testing::TestWithParam<tuple<bool, Target> > Reproducibility_AlexNet;
TEST_P(Reproducibility_AlexNet, Accuracy)
{
Target targetId = get<1>(GetParam());
applyTestTag(targetId == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
bool readFromMemory = get<0>(GetParam());
Net net;
{
......@@ -132,7 +134,6 @@ TEST_P(Reproducibility_AlexNet, Accuracy)
ASSERT_FALSE(net.empty());
}
int targetId = get<1>(GetParam());
const float l1 = 1e-5;
const float lInf = (targetId == DNN_TARGET_OPENCL_FP16) ? 3e-3 : 1e-4;
......@@ -151,9 +152,9 @@ TEST_P(Reproducibility_AlexNet, Accuracy)
INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_AlexNet, Combine(testing::Bool(),
Values(DNN_TARGET_CPU, DNN_TARGET_OPENCL, DNN_TARGET_OPENCL_FP16)));
#if !defined(_WIN32) || defined(_WIN64)
TEST(Reproducibility_FCN, Accuracy)
{
applyTestTag(CV_TEST_TAG_LONG, CV_TEST_TAG_MEMORY_2GB);
Net net;
{
const string proto = findDataFile("dnn/fcn8s-heavy-pascal.prototxt", false);
......@@ -179,10 +180,10 @@ TEST(Reproducibility_FCN, Accuracy)
normAssert(ref, out);
}
#endif
TEST(Reproducibility_SSD, Accuracy)
{
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
Net net;
{
const string proto = findDataFile("dnn/ssd_vgg16.prototxt", false);
......@@ -264,10 +265,11 @@ INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_MobileNet_SSD,
typedef testing::TestWithParam<Target> Reproducibility_ResNet50;
TEST_P(Reproducibility_ResNet50, Accuracy)
{
Target targetId = GetParam();
applyTestTag(targetId == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
Net net = readNetFromCaffe(findDataFile("dnn/ResNet-50-deploy.prototxt", false),
findDataFile("dnn/ResNet-50-model.caffemodel", false));
int targetId = GetParam();
net.setPreferableBackend(DNN_BACKEND_OPENCV);
net.setPreferableTarget(targetId);
......@@ -330,6 +332,7 @@ INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_SqueezeNet_v1_1,
TEST(Reproducibility_AlexNet_fp16, Accuracy)
{
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
const float l1 = 1e-5;
const float lInf = 3e-3;
......@@ -375,6 +378,7 @@ TEST(Reproducibility_GoogLeNet_fp16, Accuracy)
// https://github.com/richzhang/colorization
TEST_P(Test_Caffe_nets, Colorization)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
checkBackend();
Mat inp = blobFromNPY(_tf("colorization_inp.npy"));
......@@ -405,6 +409,7 @@ TEST_P(Test_Caffe_nets, Colorization)
TEST_P(Test_Caffe_nets, DenseNet_121)
{
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
checkBackend();
const string proto = findDataFile("dnn/DenseNet_121.prototxt", false);
const string model = findDataFile("dnn/DenseNet_121.caffemodel", false);
......@@ -520,6 +525,8 @@ INSTANTIATE_TEST_CASE_P(Test_Caffe, opencv_face_detector,
TEST_P(Test_Caffe_nets, FasterRCNN_vgg16)
{
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 (backend == DNN_BACKEND_INFERENCE_ENGINE && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
throw SkipTestException("Test is disabled for DLIE OpenCL targets"); // very slow
......@@ -536,6 +543,7 @@ TEST_P(Test_Caffe_nets, FasterRCNN_vgg16)
TEST_P(Test_Caffe_nets, FasterRCNN_zf)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
if ((backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL_FP16) ||
(backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD))
throw SkipTestException("");
......@@ -547,6 +555,7 @@ TEST_P(Test_Caffe_nets, FasterRCNN_zf)
TEST_P(Test_Caffe_nets, RFCN)
{
applyTestTag(CV_TEST_TAG_LONG, (target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_2GB));
if ((backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL_FP16) ||
(backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD))
throw SkipTestException("");
......
modules/dnn/test/test_darknet_importer.cpp
View file @ e0841f3d
......@@ -78,6 +78,7 @@ TEST(Test_Darknet, read_yolo_voc)
TEST(Test_Darknet, read_yolo_voc_stream)
{
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);
......@@ -267,6 +268,8 @@ public:
TEST_P(Test_Darknet_nets, YoloVoc)
{
applyTestTag(CV_TEST_TAG_LONG, CV_TEST_TAG_MEMORY_1GB);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_OPENCL_FP16)
throw SkipTestException("Test is disabled");
......@@ -305,6 +308,8 @@ TEST_P(Test_Darknet_nets, YoloVoc)
TEST_P(Test_Darknet_nets, TinyYoloVoc)
{
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
#if defined(INF_ENGINE_RELEASE)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
......@@ -339,6 +344,8 @@ TEST_P(Test_Darknet_nets, TinyYoloVoc)
TEST_P(Test_Darknet_nets, YOLOv3)
{
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 (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
......
modules/dnn/test/test_onnx_importer.cpp
View file @ e0841f3d
......@@ -217,6 +217,7 @@ INSTANTIATE_TEST_CASE_P(/*nothing*/, Test_ONNX_layers, dnnBackendsAndTargets());
class Test_ONNX_nets : public Test_ONNX_layers {};
TEST_P(Test_ONNX_nets, Alexnet)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
const String model = _tf("models/alexnet.onnx");
Net net = readNetFromONNX(model);
......@@ -270,31 +271,30 @@ TEST_P(Test_ONNX_nets, Googlenet)
TEST_P(Test_ONNX_nets, CaffeNet)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
testONNXModels("caffenet", pb);
}
TEST_P(Test_ONNX_nets, RCNN_ILSVRC13)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
// Reference output values are in range [-4.992, -1.161]
testONNXModels("rcnn_ilsvrc13", pb, 0.0045);
}
#ifdef OPENCV_32BIT_CONFIGURATION
TEST_P(Test_ONNX_nets, DISABLED_VGG16) // memory usage >2Gb
#else
TEST_P(Test_ONNX_nets, VGG16)
#endif
{
applyTestTag(CV_TEST_TAG_MEMORY_6GB); // > 2.3Gb
// output range: [-69; 72], after Softmax [0; 0.96]
testONNXModels("vgg16", pb, default_l1, default_lInf, true);
}
#ifdef OPENCV_32BIT_CONFIGURATION
TEST_P(Test_ONNX_nets, DISABLED_VGG16_bn) // memory usage >2Gb
#else
TEST_P(Test_ONNX_nets, VGG16_bn)
#endif
{
applyTestTag(CV_TEST_TAG_MEMORY_6GB); // > 2.3Gb
// output range: [-16; 27], after Softmax [0; 0.67]
const double lInf = (target == DNN_TARGET_MYRIAD) ? 0.038 : default_lInf;
testONNXModels("vgg16-bn", pb, default_l1, lInf, true);
......@@ -302,23 +302,30 @@ TEST_P(Test_ONNX_nets, VGG16_bn)
TEST_P(Test_ONNX_nets, ZFNet)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
testONNXModels("zfnet512", pb);
}
TEST_P(Test_ONNX_nets, ResNet18v1)
{
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
// output range: [-16; 22], after Softmax [0, 0.51]
testONNXModels("resnet18v1", pb, default_l1, default_lInf, true);
}
TEST_P(Test_ONNX_nets, ResNet50v1)
{
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
// output range: [-67; 75], after Softmax [0, 0.98]
testONNXModels("resnet50v1", pb, default_l1, default_lInf, true);
}
TEST_P(Test_ONNX_nets, ResNet101_DUC_HDC)
{
applyTestTag(CV_TEST_TAG_VERYLONG);
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019010000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("Test is disabled for DLIE targets");
......@@ -334,6 +341,8 @@ TEST_P(Test_ONNX_nets, ResNet101_DUC_HDC)
TEST_P(Test_ONNX_nets, TinyYolov2)
{
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
if (cvtest::skipUnstableTests)
throw SkipTestException("Skip unstable test");
#if defined(INF_ENGINE_RELEASE)
......@@ -347,6 +356,7 @@ TEST_P(Test_ONNX_nets, TinyYolov2)
)
throw SkipTestException("Test is disabled for MyriadX");
#endif
// output range: [-11; 8]
double l1 = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.017 : default_l1;
double lInf = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.14 : default_lInf;
......@@ -367,6 +377,7 @@ TEST_P(Test_ONNX_nets, MobileNet_v2)
TEST_P(Test_ONNX_nets, LResNet100E_IR)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
if (backend == DNN_BACKEND_INFERENCE_ENGINE &&
(target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_OPENCL || target == DNN_TARGET_MYRIAD))
throw SkipTestException("");
......@@ -419,6 +430,8 @@ TEST_P(Test_ONNX_nets, Inception_v2)
TEST_P(Test_ONNX_nets, DenseNet121)
{
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
// output range: [-87; 138], after Softmax [0; 1]
testONNXModels("densenet121", pb, default_l1, default_lInf, true);
}
......
modules/dnn/test/test_tf_importer.cpp
View file @ e0841f3d
......@@ -361,6 +361,8 @@ TEST_P(Test_TensorFlow_nets, MobileNet_SSD)
TEST_P(Test_TensorFlow_nets, Inception_v2_SSD)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
#if defined(INF_ENGINE_RELEASE)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
&& getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X
......@@ -426,6 +428,7 @@ TEST_P(Test_TensorFlow_nets, MobileNet_v1_SSD)
TEST_P(Test_TensorFlow_nets, Faster_RCNN)
{
applyTestTag(CV_TEST_TAG_LONG, (target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_1GB : CV_TEST_TAG_MEMORY_2GB)); // FIXIT split test
static std::string names[] = {"faster_rcnn_inception_v2_coco_2018_01_28",
"faster_rcnn_resnet50_coco_2018_01_28"};
......@@ -521,6 +524,8 @@ TEST_P(Test_TensorFlow_nets, opencv_face_detector_uint8)
// np.save('east_text_detection.geometry.npy', geometry)
TEST_P(Test_TensorFlow_nets, EAST_text_detection)
{
applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
#if defined(INF_ENGINE_RELEASE)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is disabled for Myriad targets");
......@@ -695,6 +700,7 @@ TEST(Test_TensorFlow, two_inputs)
TEST(Test_TensorFlow, Mask_RCNN)
{
applyTestTag(CV_TEST_TAG_MEMORY_1GB);
std::string proto = findDataFile("dnn/mask_rcnn_inception_v2_coco_2018_01_28.pbtxt", false);
std::string model = findDataFile("dnn/mask_rcnn_inception_v2_coco_2018_01_28.pb", false);
......
modules/dnn/test/test_torch_importer.cpp
View file @ e0841f3d
......@@ -345,6 +345,7 @@ static void normAssertSegmentation(const Mat& ref, const Mat& test)
TEST_P(Test_Torch_nets, ENet_accuracy)
{
applyTestTag(target == DNN_TARGET_CPU ? "" : CV_TEST_TAG_MEMORY_512MB);
checkBackend();
if (backend == DNN_BACKEND_INFERENCE_ENGINE ||
(backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16))
......
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