feat: 切换后端至PaddleOCR-NCNN，切换工程为CMake

1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试 2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程 3.重整权利声明文件，重整代码工程，确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
2022-05-10 09:54:44 +08:00
parent ecdd171c6f
commit 718c41634f
10018 changed files with 3593797 additions and 186748 deletions
--- a/3rdparty/opencv-4.5.4/modules/dnn/perf/perf_caffe.cpp
+++ b/3rdparty/opencv-4.5.4/modules/dnn/perf/perf_caffe.cpp
@ -0,0 +1,111 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+//
+// Copyright (C) 2017, Intel Corporation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+
+// Recommends run this performance test via
+// ./bin/opencv_perf_dnn 2> /dev/null | grep "PERFSTAT" -A 3
+// because whole output includes Caffe's logs.
+//
+// Note: Be sure that interesting version of Caffe was linked.
+// Note: There is an impact on Halide performance. Comment this tests if you
+//       want to run the last one.
+//
+// How to build Intel-Caffe with MKLDNN backend
+// ============================================
+// mkdir build && cd build
+// cmake -DCMAKE_BUILD_TYPE=Release \
+//       -DUSE_MKLDNN_AS_DEFAULT_ENGINE=ON \
+//       -DUSE_MKL2017_AS_DEFAULT_ENGINE=OFF \
+//       -DCPU_ONLY=ON \
+//       -DCMAKE_INSTALL_PREFIX=/usr/local .. && make -j8
+// sudo make install
+//
+// In case of problems with cublas_v2.h at include/caffe/util/device_alternate.hpp: add line
+// #define CPU_ONLY
+// before the first line
+// #ifdef CPU_ONLY  // CPU-only Caffe.
+
+#if defined(HAVE_CAFFE) || defined(HAVE_CLCAFFE)
+
+#include "perf_precomp.hpp"
+#include <iostream>
+#include <caffe/caffe.hpp>
+
+namespace opencv_test {
+
+static caffe::Net<float>* initNet(std::string proto, std::string weights)
+{
+    proto = findDataFile(proto);
+    weights = findDataFile(weights, false);
+
+#ifdef HAVE_CLCAFFE
+    caffe::Caffe::set_mode(caffe::Caffe::GPU);
+    caffe::Caffe::SetDevice(0);
+
+    caffe::Net<float>* net =
+        new caffe::Net<float>(proto, caffe::TEST, caffe::Caffe::GetDefaultDevice());
+#else
+    caffe::Caffe::set_mode(caffe::Caffe::CPU);
+
+    caffe::Net<float>* net = new caffe::Net<float>(proto, caffe::TEST);
+#endif
+
+    net->CopyTrainedLayersFrom(weights);
+
+    caffe::Blob<float>* input = net->input_blobs()[0];
+
+    CV_Assert(input->num() == 1);
+    CV_Assert(input->channels() == 3);
+
+    Mat inputMat(input->height(), input->width(), CV_32FC3, (char*)input->cpu_data());
+    randu(inputMat, 0.0f, 1.0f);
+
+    net->Forward();
+    return net;
+}
+
+PERF_TEST(AlexNet_caffe, CaffePerfTest)
+{
+    caffe::Net<float>* net = initNet("dnn/bvlc_alexnet.prototxt",
+                                     "dnn/bvlc_alexnet.caffemodel");
+    TEST_CYCLE() net->Forward();
+    SANITY_CHECK_NOTHING();
+}
+
+PERF_TEST(GoogLeNet_caffe, CaffePerfTest)
+{
+    caffe::Net<float>* net = initNet("dnn/bvlc_googlenet.prototxt",
+                                     "dnn/bvlc_googlenet.caffemodel");
+    TEST_CYCLE() net->Forward();
+    SANITY_CHECK_NOTHING();
+}
+
+PERF_TEST(ResNet50_caffe, CaffePerfTest)
+{
+    caffe::Net<float>* net = initNet("dnn/ResNet-50-deploy.prototxt",
+                                     "dnn/ResNet-50-model.caffemodel");
+    TEST_CYCLE() net->Forward();
+    SANITY_CHECK_NOTHING();
+}
+
+PERF_TEST(SqueezeNet_v1_1_caffe, CaffePerfTest)
+{
+    caffe::Net<float>* net = initNet("dnn/squeezenet_v1.1.prototxt",
+                                     "dnn/squeezenet_v1.1.caffemodel");
+    TEST_CYCLE() net->Forward();
+    SANITY_CHECK_NOTHING();
+}
+
+PERF_TEST(MobileNet_SSD, CaffePerfTest)
+{
+    caffe::Net<float>* net = initNet("dnn/MobileNetSSD_deploy.prototxt",
+                                     "dnn/MobileNetSSD_deploy.caffemodel");
+    TEST_CYCLE() net->Forward();
+    SANITY_CHECK_NOTHING();
+}
+
+} // namespace
+#endif  // HAVE_CAFFE