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Merge pull request #11839 from dkurt:dnn_ie_r2

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Vadim Pisarevsky 2018-06-27 09:56:02 +00:00
commit 5dc0e51682
4 changed files with 6 additions and 6 deletions
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6
modules/dnn/test/test_backends.cpp
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@ -182,11 +182,9 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_Caffe)
throw SkipTestException(""); throw SkipTestException("");
Mat sample = imread(findDataFile("dnn/street.png", false)); Mat sample = imread(findDataFile("dnn/street.png", false));
Mat inp = blobFromImage(sample, 1.0f / 127.5, Size(300, 300), Scalar(127.5, 127.5, 127.5), false); Mat inp = blobFromImage(sample, 1.0f / 127.5, Size(300, 300), Scalar(127.5, 127.5, 127.5), false);
float l1 = (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) ? 0.0007 : 0.0; float diffScores = (target == DNN_TARGET_OPENCL_FP16) ? 6e-3 : 0.0;
float lInf = (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16) ? 0.011 : 0.0;
processNet("dnn/MobileNetSSD_deploy.caffemodel", "dnn/MobileNetSSD_deploy.prototxt", processNet("dnn/MobileNetSSD_deploy.caffemodel", "dnn/MobileNetSSD_deploy.prototxt",
inp, "detection_out", "", l1, lInf); inp, "detection_out", "", diffScores);
} }
TEST_P(DNNTestNetwork, MobileNet_SSD_v1_TensorFlow) TEST_P(DNNTestNetwork, MobileNet_SSD_v1_TensorFlow)

3
modules/dnn/test/test_common.hpp
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@ -157,7 +157,8 @@ static inline bool checkMyriadTarget()
net.addLayerToPrev("testLayer", "Identity", lp); net.addLayerToPrev("testLayer", "Identity", lp);
net.setPreferableBackend(cv::dnn::DNN_BACKEND_INFERENCE_ENGINE); net.setPreferableBackend(cv::dnn::DNN_BACKEND_INFERENCE_ENGINE);
net.setPreferableTarget(cv::dnn::DNN_TARGET_MYRIAD); net.setPreferableTarget(cv::dnn::DNN_TARGET_MYRIAD);
net.setInput(cv::Mat::zeros(1, 1, CV_32FC1)); static int inpDims[] = {1, 2, 3, 4};
net.setInput(cv::Mat(4, &inpDims[0], CV_32FC1, cv::Scalar(0)));
try try
{ {
net.forward(); net.forward();

2
modules/dnn/test/test_darknet_importer.cpp
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@ -143,7 +143,7 @@ TEST_P(Test_Darknet_nets, YoloVoc)
classIds[0] = 6; confidences[0] = 0.750469f; boxes[0] = Rect2d(0.577374, 0.127391, 0.325575, 0.173418); // a car classIds[0] = 6; confidences[0] = 0.750469f; boxes[0] = Rect2d(0.577374, 0.127391, 0.325575, 0.173418); // a car
classIds[1] = 1; confidences[1] = 0.780879f; boxes[1] = Rect2d(0.270762, 0.264102, 0.461713, 0.48131); // a bicycle classIds[1] = 1; confidences[1] = 0.780879f; boxes[1] = Rect2d(0.270762, 0.264102, 0.461713, 0.48131); // a bicycle
classIds[2] = 11; confidences[2] = 0.901615f; boxes[2] = Rect2d(0.1386, 0.338509, 0.282737, 0.60028); // a dog classIds[2] = 11; confidences[2] = 0.901615f; boxes[2] = Rect2d(0.1386, 0.338509, 0.282737, 0.60028); // a dog
double scoreDiff = (targetId == DNN_TARGET_OPENCL_FP16 || targetId == DNN_TARGET_MYRIAD) ? 7e-3 : 8e-5; double scoreDiff = (targetId == DNN_TARGET_OPENCL_FP16 || targetId == DNN_TARGET_MYRIAD) ? 1e-2 : 8e-5;
double iouDiff = (targetId == DNN_TARGET_OPENCL_FP16 || targetId == DNN_TARGET_MYRIAD) ? 0.013 : 3e-5; double iouDiff = (targetId == DNN_TARGET_OPENCL_FP16 || targetId == DNN_TARGET_MYRIAD) ? 0.013 : 3e-5;
testDarknetModel("yolo-voc.cfg", "yolo-voc.weights", outNames, testDarknetModel("yolo-voc.cfg", "yolo-voc.weights", outNames,
classIds, confidences, boxes, backendId, targetId, scoreDiff, iouDiff); classIds, confidences, boxes, backendId, targetId, scoreDiff, iouDiff);

1
modules/dnn/test/test_layers.cpp
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@ -1183,6 +1183,7 @@ TEST(Layer_Test_PoolingIndices, Accuracy)
} }
} }
} }
net.setPreferableBackend(DNN_BACKEND_OPENCV);
net.setInput(blobFromImage(inp)); net.setInput(blobFromImage(inp));
std::vector<Mat> outputs; std::vector<Mat> outputs;