objdetect: validate feature rectangle on reading

pull/15150/head
Alexander Alekhin 5 years ago
parent 6158bd2afa
commit 321c74ccd6
  1. 43
      modules/objdetect/src/cascadedetect.cpp
  2. 6
      modules/objdetect/src/cascadedetect.hpp

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

@ -317,12 +317,12 @@ public:
struct Feature
{
Feature();
bool read( const FileNode& node );
bool read(const FileNode& node, const Size& origWinSize);
bool tilted;
enum { RECT_NUM = 3 };
struct
struct RectWeigth
{
Rect r;
float weight;
@ -412,7 +412,7 @@ public:
Feature( int x, int y, int _block_w, int _block_h ) :
rect(x, y, _block_w, _block_h) {}
bool read(const FileNode& node );
bool read(const FileNode& node, const Size& origWinSize);
Rect rect; // weight and height for block
};

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