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fixed multiple warnings from VS2010.

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This commit is contained in:
Vadim Pisarevsky
2010-11-25 16:55:46 +00:00
parent 7e5c11a920
commit 1286c1db45
36 changed files with 178 additions and 177 deletions
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39
modules/features2d/src/matchers.cpp
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@@ -56,10 +56,11 @@ Mat windowedMatchingMask( const vector<KeyPoint>& keypoints1, const vector<KeyPo
if( keypoints1.empty() || keypoints2.empty() )
return Mat();
Mat mask( keypoints1.size(), keypoints2.size(), CV_8UC1 );
for( size_t i = 0; i < keypoints1.size(); i++ )
int n1 = (int)keypoints1.size(), n2 = (int)keypoints2.size();
Mat mask( n1, n2, CV_8UC1 );
for( int i = 0; i < n1; i++ )
{
for( size_t j = 0; j < keypoints2.size(); j++ )
for( int j = 0; j < n2; j++ )
{
Point2f diff = keypoints2[j].pt - keypoints1[i].pt;
mask.at<uchar>(i, j) = std::abs(diff.x) < maxDeltaX && std::abs(diff.y) < maxDeltaY;
@@ -166,11 +167,11 @@ void DescriptorMatcher::DescriptorCollection::getLocalIdx( int globalDescIdx, in
{
if( globalDescIdx < startIdxs[i] )
{
imgIdx = i - 1;
imgIdx = (int)(i - 1);
break;
}
}
imgIdx = imgIdx == -1 ? startIdxs.size() -1 : imgIdx;
imgIdx = imgIdx == -1 ? (int)(startIdxs.size() - 1) : imgIdx;
localDescIdx = globalDescIdx - startIdxs[imgIdx];
}
@@ -648,7 +649,7 @@ void GenericDescriptorMatcher::KeyPointCollection::add( const vector<Mat>& _imag
images.insert( images.end(), _images.begin(), _images.end() );
keypoints.insert( keypoints.end(), _points.begin(), _points.end() );
for( size_t i = 0; i < _points.size(); i++ )
pointCount += _points[i].size();
pointCount += (int)_points[i].size();
size_t prevSize = startIndices.size(), addSize = _images.size();
startIndices.resize( prevSize + addSize );
@@ -656,11 +657,11 @@ void GenericDescriptorMatcher::KeyPointCollection::add( const vector<Mat>& _imag
if( prevSize == 0 )
startIndices[prevSize] = 0; //first
else
startIndices[prevSize] = startIndices[prevSize-1] + keypoints[prevSize-1].size();
startIndices[prevSize] = (int)(startIndices[prevSize-1] + keypoints[prevSize-1].size());
for( size_t i = prevSize + 1; i < prevSize + addSize; i++ )
{
startIndices[i] = startIndices[i - 1] + keypoints[i - 1].size();
startIndices[i] = (int)(startIndices[i - 1] + keypoints[i - 1].size());
}
}
@@ -712,11 +713,11 @@ void GenericDescriptorMatcher::KeyPointCollection::getLocalIdx( int globalPointI
{
if( globalPointIdx < startIndices[i] )
{
imgIdx = i - 1;
imgIdx = (int)(i - 1);
break;
}
}
imgIdx = imgIdx == -1 ? startIndices.size() -1 : imgIdx;
imgIdx = imgIdx == -1 ? (int)(startIndices.size() - 1) : imgIdx;
localPointIdx = globalPointIdx - startIndices[imgIdx];
}
@@ -923,14 +924,14 @@ void OneWayDescriptorMatcher::train()
base = new OneWayDescriptorObject( params.patchSize, params.poseCount, params.pcaFilename,
params.trainPath, params.trainImagesList, params.minScale, params.maxScale, params.stepScale );
base->Allocate( trainPointCollection.keypointCount() );
prevTrainCount = trainPointCollection.keypointCount();
base->Allocate( (int)trainPointCollection.keypointCount() );
prevTrainCount = (int)trainPointCollection.keypointCount();
const vector<vector<KeyPoint> >& points = trainPointCollection.getKeypoints();
int count = 0;
for( size_t i = 0; i < points.size(); i++ )
{
IplImage _image = trainPointCollection.getImage(i);
IplImage _image = trainPointCollection.getImage((int)i);
for( size_t j = 0; j < points[i].size(); j++ )
base->InitializeDescriptor( count++, &_image, points[i][j], "" );
}
@@ -961,7 +962,7 @@ void OneWayDescriptorMatcher::knnMatchImpl( const Mat& queryImage, vector<KeyPoi
int descIdx = -1, poseIdx = -1;
float distance;
base->FindDescriptor( &_qimage, queryKeypoints[i].pt, descIdx, poseIdx, distance );
matches[i].push_back( DMatch(i, descIdx, distance) );
matches[i].push_back( DMatch((int)i, descIdx, distance) );
}
}
@@ -979,7 +980,7 @@ void OneWayDescriptorMatcher::radiusMatchImpl( const Mat& queryImage, vector<Key
float distance;
base->FindDescriptor( &_qimage, queryKeypoints[i].pt, descIdx, poseIdx, distance );
if( distance < maxDistance )
matches[i].push_back( DMatch(i, descIdx, distance) );
matches[i].push_back( DMatch((int)i, descIdx, distance) );
}
}
@@ -1060,7 +1061,7 @@ void FernDescriptorMatcher::train()
vector<vector<Point2f> > points( trainPointCollection.imageCount() );
for( size_t imgIdx = 0; imgIdx < trainPointCollection.imageCount(); imgIdx++ )
KeyPoint::convert( trainPointCollection.getKeypoints(imgIdx), points[imgIdx] );
KeyPoint::convert( trainPointCollection.getKeypoints((int)imgIdx), points[imgIdx] );
classifier = new FernClassifier( points, trainPointCollection.getImages(), vector<vector<int> >(), 0, // each points is a class
params.patchSize, params.signatureSize, params.nstructs, params.structSize,
@@ -1112,8 +1113,8 @@ void FernDescriptorMatcher::knnMatchImpl( const Mat& queryImage, vector<KeyPoint
if( -signature[ci] < bestMatch.distance )
{
int imgIdx = -1, trainIdx = -1;
trainPointCollection.getLocalIdx( ci , imgIdx, trainIdx );
bestMatch = DMatch( queryIdx, trainIdx, imgIdx, -signature[ci] );
trainPointCollection.getLocalIdx( (int)ci , imgIdx, trainIdx );
bestMatch = DMatch( (int)queryIdx, trainIdx, imgIdx, -signature[ci] );
}
}
@@ -1143,7 +1144,7 @@ void FernDescriptorMatcher::radiusMatchImpl( const Mat& queryImage, vector<KeyPo
{
int imgIdx = -1, trainIdx = -1;
trainPointCollection.getLocalIdx( ci , imgIdx, trainIdx );
matches[i].push_back( DMatch( i, trainIdx, imgIdx, -signature[ci] ) );
matches[i].push_back( DMatch( (int)i, trainIdx, imgIdx, -signature[ci] ) );
}
}
}