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Fix proto and weights mess in dnn performance tests.

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This commit is contained in:
Alexander Smorkalov 2024-01-12 15:54:50 +03:00
parent 28d22d7b84
commit 77af137285
1 changed files with 17 additions and 16 deletions
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33
modules/dnn/perf/perf_net.cpp
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@ -40,7 +40,7 @@ public:
if (!halide_scheduler.empty())
halide_scheduler = findDataFile(std::string("dnn/halide_scheduler_") + (target == DNN_TARGET_OPENCL ? "opencl_" : "") + halide_scheduler, true);
}
net = readNet(proto, weights);
net = readNet(weights, proto);
// Set multiple inputs
for(auto &inp: inputs){
net.setInput(std::get<0>(inp), std::get<1>(inp));
@ -283,7 +283,7 @@ PERF_TEST_P_(DNNTestNetwork, YOLOv5) {
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
Mat sample = imread(findDataFile("dnn/dog416.png"));
Mat inp = blobFromImage(sample, 1.0 / 255.0, Size(640, 640), Scalar(), true);
processNet("", "dnn/yolov5n.onnx", "", inp);
processNet("dnn/yolov5n.onnx", "", "", inp);
}
PERF_TEST_P_(DNNTestNetwork, YOLOv8)
@ -295,7 +295,7 @@ PERF_TEST_P_(DNNTestNetwork, YOLOv8)
Mat sample = imread(findDataFile("dnn/dog416.png"));
Mat inp = blobFromImage(sample, 1.0 / 255.0, Size(640, 640), Scalar(), true);
processNet("", "dnn/yolov8n.onnx", "", inp);
processNet("dnn/yolov8n.onnx", "", "", inp);
}
PERF_TEST_P_(DNNTestNetwork, YOLOX) {
@ -305,7 +305,7 @@ PERF_TEST_P_(DNNTestNetwork, YOLOX) {
);
Mat sample = imread(findDataFile("dnn/dog416.png"));
Mat inp = blobFromImage(sample, 1.0 / 255.0, Size(640, 640), Scalar(), true);
processNet("", "dnn/yolox_s.onnx", "", inp);
processNet("dnn/yolox_s.onnx", "", "", inp);
}
PERF_TEST_P_(DNNTestNetwork, EAST_text_detection)
@ -365,15 +365,15 @@ PERF_TEST_P_(DNNTestNetwork, EfficientNet)
Mat sample = imread(findDataFile("dnn/dog416.png"));
Mat inp = blobFromImage(sample, 1.0 / 255.0, Size(224, 224), Scalar(), true);
transposeND(inp, {0, 2, 3, 1}, inp);
processNet("", "dnn/efficientnet-lite4.onnx", "", inp);
processNet("dnn/efficientnet-lite4.onnx", "", "", inp);
}
PERF_TEST_P_(DNNTestNetwork, YuNet) {
processNet("", "dnn/onnx/models/yunet-202303.onnx", "", cv::Size(640, 640));
processNet("dnn/onnx/models/yunet-202303.onnx", "", "", cv::Size(640, 640));
}
PERF_TEST_P_(DNNTestNetwork, SFace) {
processNet("", "dnn/face_recognition_sface_2021dec.onnx", "", cv::Size(112, 112));
processNet("dnn/face_recognition_sface_2021dec.onnx", "", "", cv::Size(112, 112));
}
PERF_TEST_P_(DNNTestNetwork, MPPalm) {
@ -381,7 +381,7 @@ PERF_TEST_P_(DNNTestNetwork, MPPalm) {
randu(inp, 0.0f, 1.0f);
inp = blobFromImage(inp, 1.0, Size(), Scalar(), false);
transposeND(inp, {0, 2, 3, 1}, inp);
processNet("", "dnn/palm_detection_mediapipe_2023feb.onnx", "", inp);
processNet("dnn/palm_detection_mediapipe_2023feb.onnx", "", "", inp);
}
PERF_TEST_P_(DNNTestNetwork, MPHand) {
@ -389,7 +389,7 @@ PERF_TEST_P_(DNNTestNetwork, MPHand) {
randu(inp, 0.0f, 1.0f);
inp = blobFromImage(inp, 1.0, Size(), Scalar(), false);
transposeND(inp, {0, 2, 3, 1}, inp);
processNet("", "dnn/handpose_estimation_mediapipe_2023feb.onnx", "", inp);
processNet("dnn/handpose_estimation_mediapipe_2023feb.onnx", "", "", inp);
}
PERF_TEST_P_(DNNTestNetwork, MPPose) {
@ -397,23 +397,23 @@ PERF_TEST_P_(DNNTestNetwork, MPPose) {
randu(inp, 0.0f, 1.0f);
inp = blobFromImage(inp, 1.0, Size(), Scalar(), false);
transposeND(inp, {0, 2, 3, 1}, inp);
processNet("", "dnn/pose_estimation_mediapipe_2023mar.onnx", "", inp);
processNet("dnn/pose_estimation_mediapipe_2023mar.onnx", "", "", inp);
}
PERF_TEST_P_(DNNTestNetwork, PPOCRv3) {
applyTestTag(CV_TEST_TAG_MEMORY_512MB);
processNet("", "dnn/onnx/models/PP_OCRv3_DB_text_det.onnx", "", cv::Size(736, 736));
processNet("dnn/onnx/models/PP_OCRv3_DB_text_det.onnx", "", "", cv::Size(736, 736));
}
PERF_TEST_P_(DNNTestNetwork, PPHumanSeg) {
processNet("", "dnn/human_segmentation_pphumanseg_2023mar.onnx", "", cv::Size(192, 192));
processNet("dnn/human_segmentation_pphumanseg_2023mar.onnx", "", "", cv::Size(192, 192));
}
PERF_TEST_P_(DNNTestNetwork, CRNN) {
Mat inp(cv::Size(100, 32), CV_32FC1);
randu(inp, 0.0f, 1.0f);
inp = blobFromImage(inp, 1.0, Size(), Scalar(), false);
processNet("", "dnn/text_recognition_CRNN_EN_2021sep.onnx", "", inp);
processNet("dnn/text_recognition_CRNN_EN_2021sep.onnx", "", "", inp);
}
PERF_TEST_P_(DNNTestNetwork, VitTrack) {
@ -423,7 +423,8 @@ PERF_TEST_P_(DNNTestNetwork, VitTrack) {
randu(inp2, 0.0f, 1.0f);
inp1 = blobFromImage(inp1, 1.0, Size(), Scalar(), false);
inp2 = blobFromImage(inp2, 1.0, Size(), Scalar(), false);
processNet("", "dnn/onnx/models/object_tracking_vittrack_2023sep.onnx", "", {std::make_tuple(inp1, "template"), std::make_tuple(inp2, "search")});
processNet("dnn/onnx/models/object_tracking_vittrack_2023sep.onnx", "", "",
{std::make_tuple(inp1, "template"), std::make_tuple(inp2, "search")});
}
PERF_TEST_P_(DNNTestNetwork, EfficientDet_int8)
@ -434,14 +435,14 @@ PERF_TEST_P_(DNNTestNetwork, EfficientDet_int8)
}
Mat inp = imread(findDataFile("dnn/dog416.png"));
inp = blobFromImage(inp, 1.0 / 255.0, Size(320, 320), Scalar(), true);
processNet("", "dnn/tflite/coco_efficientdet_lite0_v1_1.0_quant_2021_09_06.tflite", "", inp);
processNet("dnn/tflite/coco_efficientdet_lite0_v1_1.0_quant_2021_09_06.tflite", "", "", inp);
}
PERF_TEST_P_(DNNTestNetwork, VIT_B_32)
{
applyTestTag(CV_TEST_TAG_DEBUG_VERYLONG);
processNet("", "dnn/onnx/models/vit_b_32.onnx", "", cv::Size(224, 224));
processNet("dnn/onnx/models/vit_b_32.onnx", "", "", cv::Size(224, 224));
}
INSTANTIATE_TEST_CASE_P(/*nothing*/, DNNTestNetwork, dnnBackendsAndTargets());