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169 lines
6.0 KiB
C++
169 lines
6.0 KiB
C++
/*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) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2008-2012, Willow Garage Inc., 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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// Training application for Soft Cascades.
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#include <sft/common.hpp>
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#include <iostream>
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#include <sft/dataset.hpp>
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#include <sft/config.hpp>
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#include <opencv2/core/core_c.h>
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int main(int argc, char** argv)
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{
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using namespace sft;
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const string keys =
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"{help h usage ? | | print this message }"
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"{config c | | path to configuration xml }"
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;
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cv::CommandLineParser parser(argc, argv, keys);
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parser.about("Soft cascade training application.");
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if (parser.has("help"))
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{
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parser.printMessage();
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return 0;
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}
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if (!parser.check())
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{
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parser.printErrors();
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return 1;
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}
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string configPath = parser.get<string>("config");
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if (configPath.empty())
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{
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std::cout << "Configuration file is missing or empty. Could not start training." << std::endl;
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return 0;
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}
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std::cout << "Read configuration from file " << configPath << std::endl;
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cv::FileStorage fs(configPath, cv::FileStorage::READ);
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if(!fs.isOpened())
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{
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std::cout << "Configuration file " << configPath << " can't be opened." << std::endl;
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return 1;
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}
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// 1. load config
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sft::Config cfg;
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fs["config"] >> cfg;
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std::cout << std::endl << "Training will be executed for configuration:" << std::endl << cfg << std::endl;
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// 2. check and open output file
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cv::FileStorage fso(cfg.outXmlPath, cv::FileStorage::WRITE);
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if(!fso.isOpened())
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{
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std::cout << "Training stopped. Output classifier Xml file " << cfg.outXmlPath << " can't be opened." << std::endl;
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return 1;
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}
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fso << cfg.cascadeName
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<< "{"
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<< "stageType" << "BOOST"
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<< "featureType" << cfg.featureType
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<< "octavesNum" << (int)cfg.octaves.size()
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<< "width" << cfg.modelWinSize.width
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<< "height" << cfg.modelWinSize.height
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<< "shrinkage" << cfg.shrinkage
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<< "octaves" << "[";
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// 3. Train all octaves
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for (ivector::const_iterator it = cfg.octaves.begin(); it != cfg.octaves.end(); ++it)
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{
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// a. create random feature pool
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int nfeatures = cfg.poolSize;
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cv::Size model = cfg.model(it);
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std::cout << "Model " << model << std::endl;
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int nchannels = (cfg.featureType == "HOG6MagLuv") ? 10: 8;
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std::cout << "number of feature channels is " << nchannels << std::endl;
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cv::Ptr<cv::FeaturePool> pool = cv::FeaturePool::create(model, nfeatures, nchannels);
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nfeatures = pool->size();
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int npositives = cfg.positives;
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int nnegatives = cfg.negatives;
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int shrinkage = cfg.shrinkage;
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cv::Rect boundingBox = cfg.bbox(it);
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std::cout << "Object bounding box" << boundingBox << std::endl;
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typedef cv::Octave Octave;
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cv::Ptr<cv::ChannelFeatureBuilder> builder = cv::ChannelFeatureBuilder::create(cfg.featureType);
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std::cout << "Channel builder " << builder->info()->name() << std::endl;
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cv::Ptr<Octave> boost = Octave::create(boundingBox, npositives, nnegatives, *it, shrinkage, builder);
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std::string path = cfg.trainPath;
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sft::ScaledDataset dataset(path, *it);
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if (boost->train(&dataset, pool, cfg.weaks, cfg.treeDepth))
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{
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CvFileStorage* fout = cvOpenFileStorage(cfg.resPath(it).c_str(), 0, CV_STORAGE_WRITE);
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boost->write(fout, cfg.cascadeName);
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cvReleaseFileStorage( &fout);
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cv::Mat thresholds;
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boost->setRejectThresholds(thresholds);
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boost->write(fso, pool, thresholds);
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cv::FileStorage tfs(("thresholds." + cfg.resPath(it)).c_str(), cv::FileStorage::WRITE);
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tfs << "thresholds" << thresholds;
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std::cout << "Octave " << *it << " was successfully trained..." << std::endl;
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}
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}
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fso << "]" << "}";
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fso.release();
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std::cout << "Training complete..." << std::endl;
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return 0;
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}
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