dnn: move module from opencv_contrib

https://github.com/opencv/opencv_contrib/tree/e6f63c7a38ca40c5dc33e38736e3027e3528d6cb/modules/dnn
2026-07-30 15:53:03 +04:00 · 2017-06-26 13:35:51 +03:00
parent ef692350e0
commit 93729784bb
143 changed files with 135205 additions and 0 deletions
@@ -0,0 +1,107 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "test_precomp.hpp"
+#include "npy_blob.hpp"
+#include <opencv2/core/ocl.hpp>
+#include <opencv2/ts/ocl_test.hpp>
+
+namespace cvtest
+{
+
+using namespace cv;
+using namespace cv::dnn;
+
+template<typename TString>
+static std::string _tf(TString filename)
+{
+    return (getOpenCVExtraDir() + "/dnn/") + filename;
+}
+
+static void launchGoogleNetTest()
+{
+    Net net;
+    {
+        const string proto = findDataFile("dnn/bvlc_googlenet.prototxt", false);
+        const string model = findDataFile("dnn/bvlc_googlenet.caffemodel", false);
+        Ptr<Importer> importer = createCaffeImporter(proto, model);
+        ASSERT_TRUE(importer != NULL);
+        importer->populateNet(net);
+    }
+
+    std::vector<Mat> inpMats;
+    inpMats.push_back( imread(_tf("googlenet_0.png")) );
+    inpMats.push_back( imread(_tf("googlenet_1.png")) );
+    ASSERT_TRUE(!inpMats[0].empty() && !inpMats[1].empty());
+
+    net.setInput(blobFromImages(inpMats), "data");
+    Mat out = net.forward("prob");
+
+    Mat ref = blobFromNPY(_tf("googlenet_prob.npy"));
+    normAssert(out, ref);
+
+    std::vector<String> blobsNames;
+    blobsNames.push_back("conv1/7x7_s2");
+    blobsNames.push_back("conv1/relu_7x7");
+    blobsNames.push_back("inception_4c/1x1");
+    blobsNames.push_back("inception_4c/relu_1x1");
+    std::vector<Mat> outs;
+    Mat in = blobFromImage(inpMats[0]);
+    net.setInput(in, "data");
+    net.forward(outs, blobsNames);
+    CV_Assert(outs.size() == blobsNames.size());
+
+    for (int i = 0; i < blobsNames.size(); i++)
+    {
+        std::string filename = blobsNames[i];
+        std::replace( filename.begin(), filename.end(), '/', '#');
+        Mat ref = blobFromNPY(_tf("googlenet_" + filename + ".npy"));
+
+        normAssert(outs[i], ref, "", 1E-4, 1E-2);
+    }
+}
+
+TEST(Reproducibility_GoogLeNet, Accuracy)
+{
+    launchGoogleNetTest();
+}
+
+}