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https://github.com/opencv/opencv.git
synced 2026-07-30 15:53:03 +04:00
engine classic removed
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@@ -798,13 +798,6 @@ TEST_P(Reproducibility_ViT_ONNX, Accuracy)
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Target targetId = GetParam();
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applyTestTag(targetId == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_1GB : CV_TEST_TAG_MEMORY_2GB);
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ASSERT_TRUE(ocl::useOpenCL() || targetId == DNN_TARGET_CPU || targetId == DNN_TARGET_CPU_FP16);
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auto engine_forced = static_cast<EngineType>(
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cv::utils::getConfigurationParameterSizeT("OPENCV_FORCE_DNN_ENGINE", ENGINE_AUTO));
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if (engine_forced == ENGINE_CLASSIC)
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{
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applyTestTag(CV_TEST_TAG_DNN_SKIP_PARSER);
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return;
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}
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std::string modelname = _tf("vit_base_patch16_224_Opset16.onnx", false);
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Net net = readNetFromONNX(modelname);
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@@ -859,13 +852,6 @@ TEST_P(Reproducibility_BERT_ONNX, Accuracy)
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Target targetId = GetParam();
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ASSERT_TRUE(ocl::useOpenCL() || targetId == DNN_TARGET_CPU || targetId == DNN_TARGET_CPU_FP16);
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auto engine_forced = static_cast<EngineType>(
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cv::utils::getConfigurationParameterSizeT("OPENCV_FORCE_DNN_ENGINE", ENGINE_AUTO));
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if (engine_forced == ENGINE_CLASSIC)
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{
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applyTestTag(CV_TEST_TAG_DNN_SKIP_PARSER);
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return;
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}
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std::string modelname = _tf("onnx/models/bert.onnx", false);
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Net net = readNetFromONNX(modelname);
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@@ -931,14 +917,6 @@ typedef testing::TestWithParam<Target> Reproducibility_MobileNetSSD_ONNX;
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TEST_P(Reproducibility_MobileNetSSD_ONNX, Accuracy)
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{
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Target targetId = GetParam();
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auto engine_forced = static_cast<EngineType>(
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cv::utils::getConfigurationParameterSizeT("OPENCV_FORCE_DNN_ENGINE", ENGINE_AUTO));
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if (engine_forced == ENGINE_CLASSIC)
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{
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applyTestTag(CV_TEST_TAG_DNN_SKIP_PARSER);
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return;
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}
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applyTestTag(targetId == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
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ASSERT_TRUE(ocl::useOpenCL() || targetId == DNN_TARGET_CPU || targetId == DNN_TARGET_CPU_FP16);
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@@ -1265,14 +1243,6 @@ INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_YOLOXS_ONNX,
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typedef testing::TestWithParam<Target> Reproducibility_BlazeFace_ONNX;
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TEST_P(Reproducibility_BlazeFace_ONNX, Accuracy)
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{
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auto engine_forced = static_cast<cv::dnn::EngineType>(
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cv::utils::getConfigurationParameterSizeT("OPENCV_FORCE_DNN_ENGINE", cv::dnn::ENGINE_AUTO));
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if (engine_forced == cv::dnn::ENGINE_CLASSIC)
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{
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applyTestTag(CV_TEST_TAG_DNN_SKIP_PARSER);
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return;
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}
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Target targetId = GetParam();
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applyTestTag(targetId == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
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ASSERT_TRUE(ocl::useOpenCL() || targetId == DNN_TARGET_CPU || targetId == DNN_TARGET_CPU_FP16);
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@@ -1381,14 +1351,6 @@ TEST_P(Reproducibility_SwinIR_ONNX, Accuracy)
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Target targetId = GetParam();
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applyTestTag(CV_TEST_TAG_MEMORY_512MB, CV_TEST_TAG_LONG);
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auto engine_forced = static_cast<EngineType>(
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cv::utils::getConfigurationParameterSizeT("OPENCV_FORCE_DNN_ENGINE", ENGINE_AUTO));
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if (engine_forced == ENGINE_CLASSIC)
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{
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applyTestTag(CV_TEST_TAG_DNN_SKIP_PARSER);
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return;
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}
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std::string modelname = _tf("onnx/models/swinir_x4_gan.onnx", false);
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Net net = readNetFromONNX(modelname, ENGINE_NEW);
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ASSERT_FALSE(net.empty());
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