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169 lines
6.0 KiB
169 lines
6.0 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) 2014, Itseez 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 Itseez Inc 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/datasets/gr_chalearn.hpp" |
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#include "opencv2/datasets/util.hpp" |
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namespace cv |
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{ |
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namespace datasets |
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{ |
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using namespace std; |
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class GR_chalearnImp : public GR_chalearn |
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{ |
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public: |
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GR_chalearnImp() {} |
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//GR_chalearnImp(const string &path); |
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virtual ~GR_chalearnImp() {} |
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virtual void load(const string &path); |
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private: |
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void loadDataset(const string &path); |
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void loadDatasetPart(const string &path, vector< Ptr<Object> > &dataset_, bool loadLabels); |
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}; |
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/*GR_chalearnImp::GR_chalearnImp(const string &path) |
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{ |
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loadDataset(path); |
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}*/ |
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void GR_chalearnImp::load(const string &path) |
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{ |
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loadDataset(path); |
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} |
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void GR_chalearnImp::loadDatasetPart(const string &path, vector< Ptr<Object> > &dataset_, bool loadLabels) |
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{ |
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vector<string> fileNames; |
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getDirList(path, fileNames); |
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for (vector<string>::iterator it=fileNames.begin(); it!=fileNames.end(); ++it) |
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{ |
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Ptr<GR_chalearnObj> curr(new GR_chalearnObj); |
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curr->name = *it; |
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curr->nameColor = curr->name + "/" + curr->name + "_color.mp4"; |
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curr->nameDepth = curr->name + "/" + curr->name + "_depth.mp4"; |
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curr->nameUser = curr->name + "/" + curr->name + "_user.mp4"; |
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// loading video info |
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string fileVideoInfo(path + curr->name + "/" + curr->name + "_data.csv"); |
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ifstream infile(fileVideoInfo.c_str()); |
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string line; |
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getline(infile, line); |
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vector<string> elems; |
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split(line, elems, ','); |
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curr->numFrames = atoi(elems[0].c_str()); |
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curr->fps = atoi(elems[1].c_str()); |
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curr->depth = atoi(elems[2].c_str()); |
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// loading ground truth |
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if (loadLabels) |
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{ |
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string fileGroundTruth(path + curr->name + "/" + curr->name + "_labels.csv"); |
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ifstream infileGroundTruth(fileGroundTruth.c_str()); |
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while (getline(infileGroundTruth, line)) |
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{ |
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vector<string> elems2; |
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split(line, elems2, ','); |
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groundTruth currGroundTruth; |
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currGroundTruth.gestureID = atoi(elems2[0].c_str()); |
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currGroundTruth.initialFrame = atoi(elems2[1].c_str()); |
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currGroundTruth.lastFrame = atoi(elems2[2].c_str()); |
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curr->groundTruths.push_back(currGroundTruth); |
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} |
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} |
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// loading skeleton |
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string fileSkeleton(path + curr->name + "/" + curr->name + "_skeleton.csv"); |
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ifstream infileSkeleton(fileSkeleton.c_str()); |
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while (getline(infileSkeleton, line)) |
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{ |
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skeleton currSkeleton; |
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vector<string> elems2; |
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split(line, elems2, ','); |
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for (unsigned int i=0, numJoin=0; i<elems2.size(); i+=9, ++numJoin) |
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{ |
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currSkeleton.s[numJoin].Wx = atof(elems2[i+0].c_str()); |
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currSkeleton.s[numJoin].Wy = atof(elems2[i+1].c_str()); |
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currSkeleton.s[numJoin].Wz = atof(elems2[i+2].c_str()); |
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currSkeleton.s[numJoin].Rx = atof(elems2[i+3].c_str()); |
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currSkeleton.s[numJoin].Ry = atof(elems2[i+4].c_str()); |
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currSkeleton.s[numJoin].Rz = atof(elems2[i+5].c_str()); |
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currSkeleton.s[numJoin].Rw = atof(elems2[i+6].c_str()); |
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currSkeleton.s[numJoin].Px = atof(elems2[i+7].c_str()); |
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currSkeleton.s[numJoin].Py = atof(elems2[i+8].c_str()); |
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} |
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curr->skeletons.push_back(currSkeleton); |
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} |
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dataset_.push_back(curr); |
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} |
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} |
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void GR_chalearnImp::loadDataset(const string &path) |
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{ |
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train.push_back(vector< Ptr<Object> >()); |
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test.push_back(vector< Ptr<Object> >()); |
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validation.push_back(vector< Ptr<Object> >()); |
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string pathTrain(path + "Train/"); |
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loadDatasetPart(pathTrain, train.back(), true); |
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// freely available validation set doesn't have labels |
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string pathValidation(path + "Validation/"); |
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loadDatasetPart(pathValidation, validation.back(), false); |
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} |
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Ptr<GR_chalearn> GR_chalearn::create() |
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{ |
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return Ptr<GR_chalearnImp>(new GR_chalearnImp); |
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} |
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} |
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}
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