final refactoring and test for training
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apps/sft/dataset.cpp
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161
apps/sft/dataset.cpp
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// For Open Source Computer Vision Library
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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//M*/
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#include <sft/dataset.hpp>
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#include <opencv2/highgui/highgui.hpp>
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#include <iostream>
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#include <queue>
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inline std::string itoa(long i) { return cv::format("%ld", i); }
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#if !defined (_WIN32) && ! defined(__MINGW32__)
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# include <glob.h>
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namespace {
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using namespace sft;
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void glob(const string& path, svector& ret)
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{
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glob_t glob_result;
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glob(path.c_str(), GLOB_TILDE, 0, &glob_result);
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ret.clear();
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ret.reserve(glob_result.gl_pathc);
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for(unsigned int i = 0; i < glob_result.gl_pathc; ++i)
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{
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ret.push_back(std::string(glob_result.gl_pathv[i]));
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dprintf("%s\n", ret[i].c_str());
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}
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globfree(&glob_result);
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}
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}
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#else
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# include <windows.h>
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namespace {
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using namespace sft;
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void glob(const string& refRoot, const string& refExt, svector &refvecFiles)
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{
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std::string strFilePath; // File path
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std::string strExtension; // Extension
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std::string strPattern = refRoot + "\\*.*";
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WIN32_FIND_DATA FileInformation; // File information
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HANDLE hFile = ::FindFirstFile(strPattern.c_str(), &FileInformation);
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if(hFile == INVALID_HANDLE_VALUE)
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CV_Error(CV_StsBadArg, "Your dataset search path is incorrect");
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do
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{
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if(FileInformation.cFileName[0] != '.')
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{
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strFilePath.erase();
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strFilePath = refRoot + "\\" + FileInformation.cFileName;
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if( !(FileInformation.dwFileAttributes & FILE_ATTRIBUTE_DIRECTORY) )
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{
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// Check extension
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strExtension = FileInformation.cFileName;
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strExtension = strExtension.substr(strExtension.rfind(".") + 1);
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if(strExtension == refExt)
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// Save filename
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refvecFiles.push_back(strFilePath);
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}
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}
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}
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while(::FindNextFile(hFile, &FileInformation) == TRUE);
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// Close handle
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::FindClose(hFile);
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DWORD dwError = ::GetLastError();
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if(dwError != ERROR_NO_MORE_FILES)
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CV_Error(CV_StsBadArg, "Your dataset search path is incorrect");
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}
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}
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#endif
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// in the default case data folders should be aligned as following:
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// 1. positives: <train or test path>/octave_<octave number>/pos/*.png
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// 2. negatives: <train or test path>/octave_<octave number>/neg/*.png
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ScaledDataset::ScaledDataset(const string& path, const int oct)
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{
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dprintf("%s\n", "get dataset file names...");
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dprintf("%s\n", "Positives globing...");
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#if !defined (_WIN32) && ! defined(__MINGW32__)
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glob(path + "/pos/octave_" + itoa(oct) + "/*.png", pos);
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#else
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glob(path + "/pos/octave_" + itoa(oct), "png", pos);
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#endif
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dprintf("%s\n", "Negatives globing...");
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#if !defined (_WIN32) && ! defined(__MINGW32__)
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glob(path + "/neg/octave_" + itoa(oct) + "/*.png", neg);
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#else
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glob(path + "/neg/octave_" + itoa(oct), "png", neg);
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#endif
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// Check: files not empty
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CV_Assert(pos.size() != size_t(0));
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CV_Assert(neg.size() != size_t(0));
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}
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cv::Mat ScaledDataset::get(SampleType type, int idx) const
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{
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const std::string& src = (type == POSITIVE)? pos[idx]: neg[idx];
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return cv::imread(src);
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}
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int ScaledDataset::available(SampleType type) const
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{
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return (int)((type == POSITIVE)? pos.size():neg.size());
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}
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ScaledDataset::~ScaledDataset(){}
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