/*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; } TEST(Reproducibility_GoogLeNet, Accuracy) { Net net = readNetFromCaffe(findDataFile("dnn/bvlc_googlenet.prototxt", false), findDataFile("dnn/bvlc_googlenet.caffemodel", false)); 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); } TEST(IntermediateBlobs_GoogLeNet, Accuracy) { Net net = readNetFromCaffe(findDataFile("dnn/bvlc_googlenet.prototxt", false), findDataFile("dnn/bvlc_googlenet.caffemodel", false)); 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(imread(_tf("googlenet_0.png"))); 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(SeveralCalls_GoogLeNet, Accuracy) { Net net = readNetFromCaffe(findDataFile("dnn/bvlc_googlenet.prototxt", false), findDataFile("dnn/bvlc_googlenet.caffemodel", false)); 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(); Mat ref = blobFromNPY(_tf("googlenet_prob.npy")); normAssert(out, ref); std::vector<String> blobsNames; blobsNames.push_back("conv1/7x7_s2"); std::vector<Mat> outs; Mat in = blobFromImage(inpMats[0]); net.setInput(in, "data"); net.forward(outs, blobsNames); CV_Assert(outs.size() == blobsNames.size()); ref = blobFromNPY(_tf("googlenet_conv1#7x7_s2.npy")); normAssert(outs[0], ref, "", 1E-4, 1E-2); } }