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Open Source Computer Vision Library
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152 lines
5.4 KiB
152 lines
5.4 KiB
/**M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2013, OpenCV Foundation, all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include <opencv2/dnn.hpp> |
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#include <opencv2/imgproc.hpp> |
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#include <opencv2/highgui.hpp> |
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#include <opencv2/core/utils/trace.hpp> |
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using namespace cv; |
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using namespace cv::dnn; |
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#include <fstream> |
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#include <iostream> |
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#include <cstdlib> |
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using namespace std; |
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/* Find best class for the blob (i. e. class with maximal probability) */ |
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static void getMaxClass(const Mat &probBlob, int *classId, double *classProb) |
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{ |
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Mat probMat = probBlob.reshape(1, 1); //reshape the blob to 1x1000 matrix |
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Point classNumber; |
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minMaxLoc(probMat, NULL, classProb, NULL, &classNumber); |
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*classId = classNumber.x; |
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} |
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static std::vector<String> readClassNames(const char *filename = "synset_words.txt") |
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{ |
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std::vector<String> classNames; |
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std::ifstream fp(filename); |
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if (!fp.is_open()) |
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{ |
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std::cerr << "File with classes labels not found: " << filename << std::endl; |
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exit(-1); |
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} |
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std::string name; |
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while (!fp.eof()) |
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{ |
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std::getline(fp, name); |
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if (name.length()) |
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classNames.push_back( name.substr(name.find(' ')+1) ); |
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} |
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fp.close(); |
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return classNames; |
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} |
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int main(int argc, char **argv) |
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{ |
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CV_TRACE_FUNCTION(); |
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String modelTxt = "bvlc_googlenet.prototxt"; |
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String modelBin = "bvlc_googlenet.caffemodel"; |
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String imageFile = (argc > 1) ? argv[1] : "space_shuttle.jpg"; |
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//! [Read and initialize network] |
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Net net = dnn::readNetFromCaffe(modelTxt, modelBin); |
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//! [Read and initialize network] |
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//! [Check that network was read successfully] |
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if (net.empty()) |
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{ |
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std::cerr << "Can't load network by using the following files: " << std::endl; |
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std::cerr << "prototxt: " << modelTxt << std::endl; |
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std::cerr << "caffemodel: " << modelBin << std::endl; |
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std::cerr << "bvlc_googlenet.caffemodel can be downloaded here:" << std::endl; |
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std::cerr << "http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel" << std::endl; |
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exit(-1); |
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} |
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//! [Check that network was read successfully] |
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//! [Prepare blob] |
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Mat img = imread(imageFile); |
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if (img.empty()) |
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{ |
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std::cerr << "Can't read image from the file: " << imageFile << std::endl; |
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exit(-1); |
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} |
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//GoogLeNet accepts only 224x224 RGB-images |
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Mat inputBlob = blobFromImage(img, 1, Size(224, 224), |
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Scalar(104, 117, 123)); //Convert Mat to batch of images |
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//! [Prepare blob] |
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Mat prob; |
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cv::TickMeter t; |
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for (int i = 0; i < 10; i++) |
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{ |
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CV_TRACE_REGION("forward"); |
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//! [Set input blob] |
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net.setInput(inputBlob, "data"); //set the network input |
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//! [Set input blob] |
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t.start(); |
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//! [Make forward pass] |
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prob = net.forward("prob"); //compute output |
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//! [Make forward pass] |
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t.stop(); |
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} |
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//! [Gather output] |
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int classId; |
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double classProb; |
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getMaxClass(prob, &classId, &classProb);//find the best class |
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//! [Gather output] |
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//! [Print results] |
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std::vector<String> classNames = readClassNames(); |
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std::cout << "Best class: #" << classId << " '" << classNames.at(classId) << "'" << std::endl; |
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std::cout << "Probability: " << classProb * 100 << "%" << std::endl; |
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//! [Print results] |
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std::cout << "Time: " << (double)t.getTimeMilli() / t.getCounter() << " ms (average from " << t.getCounter() << " iterations)" << std::endl; |
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return 0; |
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} //main
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