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Merge pull request #28678 from omrope79:caffe-importer-cleanup

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Caffe importer cleanup #28678

Merge with: https://github.com/opencv/opencv_extra/pull/1324

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
- [x] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
omrope79
2026-06-02 19:58:10 +05:30
committed by GitHub
parent 42fc6939f8
commit b67ad9a422
34 changed files with 327 additions and 5674 deletions
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modules/dnn/perf/perf_net.cpp
+27 -18
View File
@@ -9,6 +9,7 @@
#include "opencv2/core/ocl.hpp"
#include "opencv2/dnn/shape_utils.hpp"
#include <opencv2/core/utils/configuration.private.hpp>
#include "../test/test_common.hpp"
@@ -96,17 +97,17 @@ public:
PERF_TEST_P_(DNNTestNetwork, AlexNet)
{
processNet("dnn/bvlc_alexnet.caffemodel", "dnn/bvlc_alexnet.prototxt", cv::Size(227, 227));
processNet("dnn/onnx/models/alexnet.onnx", "", cv::Size(227, 227));
}
PERF_TEST_P_(DNNTestNetwork, GoogLeNet)
{
processNet("dnn/bvlc_googlenet.caffemodel", "dnn/bvlc_googlenet.prototxt", cv::Size(224, 224));
processNet("dnn/onnx/models/googlenet.onnx", "", cv::Size(224, 224));
}
PERF_TEST_P_(DNNTestNetwork, ResNet_50)
{
processNet("dnn/ResNet-50-model.caffemodel", "dnn/ResNet-50-deploy.prototxt", cv::Size(224, 224));
processNet("dnn/onnx/models/resnet50v1.onnx", "", cv::Size(224, 224));
}
PERF_TEST_P_(DNNTestNetwork, ResNet_18_v1_ONNX)
@@ -131,7 +132,7 @@ PERF_TEST_P_(DNNTestNetwork, ResNet50_QDQ_ONNX)
PERF_TEST_P_(DNNTestNetwork, SqueezeNet_v1_1)
{
processNet("dnn/squeezenet_v1.1.caffemodel", "dnn/squeezenet_v1.1.prototxt", cv::Size(227, 227));
processNet("dnn/onnx/models/squeezenet.onnx", "", cv::Size(227, 227));
}
PERF_TEST_P_(DNNTestNetwork, Inception_5h)
@@ -144,12 +145,28 @@ PERF_TEST_P_(DNNTestNetwork, SSD)
{
applyTestTag(CV_TEST_TAG_DEBUG_VERYLONG);
processNet("dnn/VGG_ILSVRC2016_SSD_300x300_iter_440000.caffemodel", "dnn/ssd_vgg16.prototxt", cv::Size(300, 300));
// The Caffe-SSD specific handling lives in the new engine importer only;
// the classic importer can no longer load this model.
auto engine_forced = static_cast<dnn::EngineType>(
utils::getConfigurationParameterSizeT("OPENCV_FORCE_DNN_ENGINE", dnn::ENGINE_AUTO));
if (engine_forced == dnn::ENGINE_CLASSIC)
throw SkipTestException("SSD_VGG16 is supported on the new DNN engine only");
processNet("dnn/onnx/models/ssd_vgg16.onnx", "", cv::Size(300, 300));
}
PERF_TEST_P_(DNNTestNetwork, MobileNet_SSD_Caffe)
PERF_TEST_P_(DNNTestNetwork, MobileNet_SSD_v1_ONNX)
{
processNet("dnn/MobileNetSSD_deploy_19e3ec3.caffemodel", "dnn/MobileNetSSD_deploy_19e3ec3.prototxt", cv::Size(300, 300));
// Dynamic-shape preprocessing in this model needs the new engine; OpenVINO uses the classic one.
if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);
// This model expects a uint8 NHWC image as input.
Mat image(cv::Size(300, 300), CV_8UC3);
randu(image, 0, 255);
int imsize[] = {1, image.rows, image.cols, 3};
Mat input(4, imsize, CV_8U, image.data);
processNet("dnn/onnx/models/ssd_mobilenet_v1_12.onnx", "", input);
}
PERF_TEST_P_(DNNTestNetwork, MobileNet_SSD_v1_TensorFlow)
@@ -162,18 +179,9 @@ PERF_TEST_P_(DNNTestNetwork, MobileNet_SSD_v2_TensorFlow)
processNet("dnn/ssd_mobilenet_v2_coco_2018_03_29.pb", "ssd_mobilenet_v2_coco_2018_03_29.pbtxt", cv::Size(300, 300));
}
PERF_TEST_P_(DNNTestNetwork, MobileNet_SSD_v1_ONNX)
{
Mat image(cv::Size(300, 300), CV_8UC3);
randu(image, 0, 255);
int imsize[] = {1, image.rows, image.cols, 3};
Mat input(4, imsize, CV_8U, image.data);
processNet("dnn/onnx/models/ssd_mobilenet_v1_12.onnx", "", input);
}
PERF_TEST_P_(DNNTestNetwork, DenseNet_121)
{
processNet("dnn/DenseNet_121.caffemodel", "dnn/DenseNet_121.prototxt", cv::Size(224, 224));
processNet("dnn/onnx/models/densenet121.onnx", "", cv::Size(224, 224));
}
PERF_TEST_P_(DNNTestNetwork, OpenPose_pose_mpi_faster_4_stages)
@@ -184,7 +192,8 @@ PERF_TEST_P_(DNNTestNetwork, OpenPose_pose_mpi_faster_4_stages)
throw SkipTestException("");
// The same .caffemodel but modified .prototxt
// See https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/src/openpose/pose/poseParameters.cpp
processNet("dnn/openpose_pose_mpi.caffemodel", "dnn/openpose_pose_mpi_faster_4_stages.prototxt", cv::Size(368, 368));
// processNet("dnn/openpose_pose_mpi.caffemodel", "dnn/openpose_pose_mpi_faster_4_stages.prototxt", cv::Size(368, 368));
processNet("dnn/onnx/models/openpose_pose_mpi.onnx", "", cv::Size(368, 368));
}
PERF_TEST_P_(DNNTestNetwork, Inception_v2_SSD_TensorFlow)