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objdetect: validate feature rectangle on reading
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6158bd2afa
commit
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@ -47,6 +47,10 @@
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#include "opencv2/objdetect/objdetect_c.h"
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#include "opencl_kernels_objdetect.hpp"
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#if defined(_MSC_VER)
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# pragma warning(disable:4458) // declaration of 'origWinSize' hides class member
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#endif
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namespace cv
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{
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@ -537,7 +541,7 @@ bool FeatureEvaluator::setImage( InputArray _image, const std::vector<float>& _s
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//---------------------------------------------- HaarEvaluator ---------------------------------------
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bool HaarEvaluator::Feature :: read( const FileNode& node )
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bool HaarEvaluator::Feature::read(const FileNode& node, const Size& origWinSize)
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{
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FileNode rnode = node[CC_RECTS];
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FileNodeIterator it = rnode.begin(), it_end = rnode.end();
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@ -549,11 +553,23 @@ bool HaarEvaluator::Feature :: read( const FileNode& node )
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rect[ri].weight = 0.f;
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}
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const int W = origWinSize.width;
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const int H = origWinSize.height;
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for(ri = 0; it != it_end; ++it, ri++)
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{
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FileNodeIterator it2 = (*it).begin();
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it2 >> rect[ri].r.x >> rect[ri].r.y >>
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rect[ri].r.width >> rect[ri].r.height >> rect[ri].weight;
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Feature::RectWeigth& rw = rect[ri];
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it2 >> rw.r.x >> rw.r.y >> rw.r.width >> rw.r.height >> rw.weight;
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// input validation
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{
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CV_CheckGE(rw.r.x, 0, "Invalid HAAR feature");
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CV_CheckGE(rw.r.y, 0, "Invalid HAAR feature");
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CV_CheckLT(rw.r.x, W, "Invalid HAAR feature"); // necessary for overflow checks
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CV_CheckLT(rw.r.y, H, "Invalid HAAR feature"); // necessary for overflow checks
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CV_CheckLE(rw.r.x + rw.r.width, W, "Invalid HAAR feature");
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CV_CheckLE(rw.r.y + rw.r.height, H, "Invalid HAAR feature");
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}
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}
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tilted = (int)node[CC_TILTED] != 0;
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@ -598,7 +614,7 @@ bool HaarEvaluator::read(const FileNode& node, Size _origWinSize)
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for(i = 0; i < n; i++, ++it)
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{
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if(!ff[i].read(*it))
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if(!ff[i].read(*it, _origWinSize))
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return false;
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if( ff[i].tilted )
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hasTiltedFeatures = true;
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@ -759,11 +775,24 @@ int HaarEvaluator::getSquaresOffset() const
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}
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//---------------------------------------------- LBPEvaluator -------------------------------------
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bool LBPEvaluator::Feature :: read(const FileNode& node )
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bool LBPEvaluator::Feature::read(const FileNode& node, const Size& origWinSize)
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{
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FileNode rnode = node[CC_RECT];
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FileNodeIterator it = rnode.begin();
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it >> rect.x >> rect.y >> rect.width >> rect.height;
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const int W = origWinSize.width;
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const int H = origWinSize.height;
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// input validation
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{
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CV_CheckGE(rect.x, 0, "Invalid LBP feature");
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CV_CheckGE(rect.y, 0, "Invalid LBP feature");
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CV_CheckLT(rect.x, W, "Invalid LBP feature");
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CV_CheckLT(rect.y, H, "Invalid LBP feature");
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CV_CheckLE(rect.x + rect.width, W, "Invalid LBP feature");
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CV_CheckLE(rect.y + rect.height, H, "Invalid LBP feature");
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}
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return true;
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}
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@ -797,7 +826,7 @@ bool LBPEvaluator::read( const FileNode& node, Size _origWinSize )
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std::vector<Feature>& ff = *features;
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for(int i = 0; it != it_end; ++it, i++)
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{
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if(!ff[i].read(*it))
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if(!ff[i].read(*it, _origWinSize))
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return false;
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}
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nchannels = 1;
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@ -1477,6 +1506,8 @@ bool CascadeClassifierImpl::Data::read(const FileNode &root)
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origWinSize.width = (int)root[CC_WIDTH];
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origWinSize.height = (int)root[CC_HEIGHT];
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CV_Assert( origWinSize.height > 0 && origWinSize.width > 0 );
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CV_CheckLE(origWinSize.width, 1000000, "Invalid window size (too large)");
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CV_CheckLE(origWinSize.height, 1000000, "Invalid window size (too large)");
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// load feature params
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FileNode fn = root[CC_FEATURE_PARAMS];
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@ -317,12 +317,12 @@ public:
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struct Feature
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{
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Feature();
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bool read( const FileNode& node );
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bool read(const FileNode& node, const Size& origWinSize);
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bool tilted;
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enum { RECT_NUM = 3 };
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struct
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struct RectWeigth
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{
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Rect r;
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float weight;
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@ -412,7 +412,7 @@ public:
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Feature( int x, int y, int _block_w, int _block_h ) :
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rect(x, y, _block_w, _block_h) {}
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bool read(const FileNode& node );
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bool read(const FileNode& node, const Size& origWinSize);
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Rect rect; // weight and height for block
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};
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