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updated 3rd party libs: CLapack 3.1.1.1 => 3.2.1, zlib 1.2.3 => 1.2.5, libpng 1.2.x => 1.4.3, libtiff 3.7.x => 3.9.4. fixed many 64-bit related VS2010 warnings

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Vadim Pisarevsky
2010-07-16 12:54:53 +00:00
parent 0c9eca7922
commit f78a3b4cc1
465 changed files with 51856 additions and 41344 deletions
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35
modules/features2d/src/descriptors.cpp
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@@ -85,7 +85,7 @@ void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1,
for( vector<KeyPoint>::const_iterator it = keypoints2.begin(); it < keypoints2.end(); ++it )
{
Point p = it->pt;
circle( outImg, Point2f(p.x+img1.cols, p.y), 3, isRandSinglePointColor ?
circle( outImg, Point(p.x+img1.cols, p.y), 3, isRandSinglePointColor ?
Scalar(rng.uniform(0, 256), rng.uniform(0, 256), rng.uniform(0, 256)) : singlePointColor );
}
}
@@ -205,7 +205,7 @@ void SurfDescriptorExtractor::compute( const Mat& image,
bool useProvidedKeypoints = true;
surf(image, mask, keypoints, _descriptors, useProvidedKeypoints);
descriptors.create(keypoints.size(), surf.descriptorSize(), CV_32FC1);
descriptors.create((int)keypoints.size(), (int)surf.descriptorSize(), CV_32FC1);
assert( (int)_descriptors.size() == descriptors.rows * descriptors.cols );
std::copy(_descriptors.begin(), _descriptors.end(), descriptors.begin<float>());
}
@@ -273,7 +273,7 @@ Ptr<DescriptorMatcher> createDescriptorMatcher( const string& descriptorMatcherT
template<>
void BruteForceMatcher<L2<float> >::matchImpl( const Mat& descriptors_1, const Mat& descriptors_2,
const Mat& mask, vector<int>& matches ) const
const Mat& /*mask*/, vector<int>& matches ) const
{
matches.clear();
matches.reserve( descriptors_1.rows );
@@ -330,7 +330,7 @@ void KeyPointCollection::add( const Mat& _image, const vector<KeyPoint>& _points
if( startIndices.empty() )
startIndices.push_back(0);
else
startIndices.push_back(*startIndices.rbegin() + points.rbegin()->size());
startIndices.push_back((int)(*startIndices.rbegin() + points.rbegin()->size()));
// add image and keypoints
images.push_back(_image);
@@ -457,11 +457,11 @@ void OneWayDescriptorMatch::add( const Mat& image, vector<KeyPoint>& keypoints )
size_t trainFeatureCount = keypoints.size();
base->Allocate( trainFeatureCount );
base->Allocate( (int)trainFeatureCount );
IplImage _image = image;
for( size_t i = 0; i < keypoints.size(); i++ )
base->InitializeDescriptor( i, &_image, keypoints[i], "" );
base->InitializeDescriptor( (int)i, &_image, keypoints[i], "" );
collection.add( Mat(), keypoints );
@@ -478,7 +478,7 @@ void OneWayDescriptorMatch::add( KeyPointCollection& keypoints )
size_t trainFeatureCount = keypoints.calcKeypointCount();
base->Allocate( trainFeatureCount );
base->Allocate( (int)trainFeatureCount );
int count = 0;
for( size_t i = 0; i < keypoints.points.size(); i++ )
@@ -517,19 +517,17 @@ void OneWayDescriptorMatch::match( const Mat& image, vector<KeyPoint>& points, v
int poseIdx = -1;
DMatch match;
match.indexQuery = i;
match.indexQuery = (int)i;
match.indexTrain = -1;
base->FindDescriptor( &_image, points[i].pt, match.indexTrain, poseIdx, match.distance );
matches[i] = match;
}
}
void OneWayDescriptorMatch::match( const Mat& image, vector<KeyPoint>& points, vector<vector<DMatch> >& matches, float threshold )
void OneWayDescriptorMatch::match( const Mat& image, vector<KeyPoint>& points, vector<vector<DMatch> >& matches, float /*threshold*/ )
{
matches.clear();
matches.resize( points.size() );
IplImage _image = image;
vector<DMatch> dmatches;
match( image, points, dmatches );
@@ -538,7 +536,6 @@ void OneWayDescriptorMatch::match( const Mat& image, vector<KeyPoint>& points, v
matches[i].push_back( dmatches[i] );
}
/*
printf("Start matching %d points\n", points.size());
//std::cout << "Start matching " << points.size() << "points\n";
@@ -686,7 +683,7 @@ void CalonderDescriptorMatch::calcBestProbAndMatchIdx( const Mat& image, const P
bestProb = 0;
bestMatchIdx = -1;
for( size_t ci = 0; ci < (size_t)classifier->classes(); ci++ )
for( int ci = 0; ci < classifier->classes(); ci++ )
{
if( signature[ci] > bestProb )
{
@@ -764,7 +761,7 @@ void CalonderDescriptorMatch::read( const FileNode &fn )
params.patchSize = fn["patchSize"];
params.reducedNumDim = (int) fn["reducedNumDim"];
params.numQuantBits = fn["numQuantBits"];
params.printStatus = (int) fn["printStatus"];
params.printStatus = (int) fn["printStatus"] != 0;
}
void CalonderDescriptorMatch::write( FileStorage& fs ) const
@@ -839,7 +836,7 @@ void FernDescriptorMatch::trainFernClassifier()
{
refimgs.push_back(new Mat (collection.images[imageIdx]));
points.push_back(collection.points[imageIdx][pointIdx].pt);
labels.push_back(pointIdx);
labels.push_back((int)pointIdx);
}
}
@@ -856,7 +853,7 @@ void FernDescriptorMatch::calcBestProbAndMatchIdx( const Mat& image, const Point
bestProb = -FLT_MAX;
bestMatchIdx = -1;
for( size_t ci = 0; ci < (size_t)classifier->getClassCount(); ci++ )
for( int ci = 0; ci < classifier->getClassCount(); ci++ )
{
if( signature[ci] > bestProb )
{
@@ -888,7 +885,7 @@ void FernDescriptorMatch::match( const Mat& image, vector<KeyPoint>& keypoints,
matches.resize( keypoints.size() );
vector<float> signature( (size_t)classifier->getClassCount() );
for( size_t pi = 0; pi < keypoints.size(); pi++ )
for( int pi = 0; pi < (int)keypoints.size(); pi++ )
{
matches[pi].indexQuery = pi;
calcBestProbAndMatchIdx( image, keypoints[pi].pt, matches[pi].distance, matches[pi].indexTrain, signature );
@@ -904,14 +901,14 @@ void FernDescriptorMatch::match( const Mat& image, vector<KeyPoint>& keypoints,
matches.resize( keypoints.size() );
vector<float> signature( (size_t)classifier->getClassCount() );
for( size_t pi = 0; pi < keypoints.size(); pi++ )
for( int pi = 0; pi < (int)keypoints.size(); pi++ )
{
(*classifier)( image, keypoints[pi].pt, signature);
DMatch match;
match.indexQuery = pi;
for( size_t ci = 0; ci < (size_t)classifier->getClassCount(); ci++ )
for( int ci = 0; ci < classifier->getClassCount(); ci++ )
{
if( -signature[ci] < threshold )
{