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