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upgrade FaceDetectorYN to v2
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@@ -65,20 +65,16 @@ TEST(Objdetect_face_detection, regression)
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{
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// Pre-set params
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float scoreThreshold = 0.7f;
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float matchThreshold = 0.9f;
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float l2disThreshold = 5.0f;
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float matchThreshold = 0.7f;
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float l2disThreshold = 15.0f;
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int numLM = 5;
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int numCoords = 4 + 2 * numLM;
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// Load ground truth labels
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std::map<std::string, Mat> gt = blobFromTXT(findDataFile("dnn_face/detection/cascades_labels.txt"), numCoords);
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// for (auto item: gt)
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// {
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// std::cout << item.first << " " << item.second.size() << std::endl;
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// }
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// Initialize detector
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std::string model = findDataFile("dnn/onnx/models/yunet-202202.onnx", false);
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std::string model = findDataFile("dnn/onnx/models/yunet-202303.onnx", false);
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Ptr<FaceDetectorYN> faceDetector = FaceDetectorYN::create(model, "", Size(300, 300));
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faceDetector->setScoreThreshold(0.7f);
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@@ -137,6 +133,7 @@ TEST(Objdetect_face_detection, regression)
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lmMatched[lmIdx] = true;
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}
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}
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break;
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}
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EXPECT_TRUE(boxMatched) << "In image " << item.first << ", cannot match resBox " << resBox << " with any ground truth.";
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if (boxMatched)
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@@ -178,7 +175,7 @@ TEST(Objdetect_face_recognition, regression)
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}
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// Initialize detector
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std::string detect_model = findDataFile("dnn/onnx/models/yunet-202202.onnx", false);
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std::string detect_model = findDataFile("dnn/onnx/models/yunet-202303.onnx", false);
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Ptr<FaceDetectorYN> faceDetector = FaceDetectorYN::create(detect_model, "", Size(150, 150), score_thresh, nms_thresh);
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std::string recog_model = findDataFile("dnn/onnx/models/face_recognizer_fast.onnx", false);
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