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[*] Fixed #974 ("GPU CascadeClassifier fails with some training files"): Moved IsNodeLeaf bit from NodeDescriptor to FeatureDescriptor for both left and right nodes, therefore from now on max number of rects in a feature is 31

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This commit is contained in:
Anton Obukhov
2011-04-04 11:47:21 +00:00
parent 2388fa223e
commit 58476b64a6
3 changed files with 97 additions and 60 deletions
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70
modules/gpu/src/cascadeclassifier.cpp
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@@ -336,24 +336,24 @@ NCVStatus loadFromXML(const std::string &filename,
haar.NumClassifierTotalNodes = 0;
haar.NumFeatures = 0;
haar.ClassifierSize.width = 0;
haar.ClassifierSize.height = 0;
haar.ClassifierSize.height = 0;
haar.bHasStumpsOnly = true;
haar.bNeedsTiltedII = false;
Ncv32u curMaxTreeDepth;
std::vector<char> xmlFileCont;
std::vector<char> xmlFileCont;
std::vector<HaarClassifierNode128> h_TmpClassifierNotRootNodes;
haarStages.resize(0);
haarClassifierNodes.resize(0);
haarFeatures.resize(0);
haarFeatures.resize(0);
Ptr<CvHaarClassifierCascade> oldCascade = (CvHaarClassifierCascade*)cvLoad(filename.c_str(), 0, 0, 0);
if (oldCascade.empty())
return NCV_HAAR_XML_LOADING_EXCEPTION;
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
haar.ClassifierSize.width = oldCascade->orig_window_size.width;
haar.ClassifierSize.height = oldCascade->orig_window_size.height;
@@ -366,53 +366,58 @@ NCVStatus loadFromXML(const std::string &filename,
curStage.setStageThreshold(oldCascade->stage_classifier[s].threshold);
int treesCount = oldCascade->stage_classifier[s].count;
for(int t = 0; t < treesCount; ++t) // bytrees
{
for(int t = 0; t < treesCount; ++t) // by trees
{
Ncv32u nodeId = 0;
CvHaarClassifier* tree = &oldCascade->stage_classifier[s].classifier[t];
int nodesCount = tree->count;
for(int n = 0; n < nodesCount; ++n) //by features
{
for(int n = 0; n < nodesCount; ++n) //by features
{
CvHaarFeature* feature = &tree->haar_feature[n];
HaarClassifierNode128 curNode;
HaarClassifierNode128 curNode;
curNode.setThreshold(tree->threshold[n]);
NcvBool bIsLeftNodeLeaf = false;
NcvBool bIsRightNodeLeaf = false;
HaarClassifierNodeDescriptor32 nodeLeft;
if ( tree->left[n] <= 0 )
{
Ncv32f leftVal = tree->alpha[-tree->left[n]];
ncvStat = nodeLeft.create(leftVal);
ncvAssertReturn(ncvStat == NCV_SUCCESS, ncvStat);
ncvAssertReturn(ncvStat == NCV_SUCCESS, ncvStat);
bIsLeftNodeLeaf = true;
}
else
{
Ncv32u leftNodeOffset = tree->left[n];
Ncv32u leftNodeOffset = tree->left[n];
nodeLeft.create((Ncv32u)(h_TmpClassifierNotRootNodes.size() + leftNodeOffset - 1));
haar.bHasStumpsOnly = false;
}
curNode.setLeftNodeDesc(nodeLeft);
HaarClassifierNodeDescriptor32 nodeRight;
if ( tree->right[n] <= 0 )
{
Ncv32f rightVal = tree->alpha[-tree->right[n]];
{
Ncv32f rightVal = tree->alpha[-tree->right[n]];
ncvStat = nodeRight.create(rightVal);
ncvAssertReturn(ncvStat == NCV_SUCCESS, ncvStat);
bIsRightNodeLeaf = true;
}
else
{
Ncv32u rightNodeOffset = tree->right[n];
{
Ncv32u rightNodeOffset = tree->right[n];
nodeRight.create((Ncv32u)(h_TmpClassifierNotRootNodes.size() + rightNodeOffset - 1));
haar.bHasStumpsOnly = false;
}
curNode.setRightNodeDesc(nodeRight);
curNode.setRightNodeDesc(nodeRight);
Ncv32u tiltedVal = feature->tilted;
haar.bNeedsTiltedII = (tiltedVal != 0);
haar.bNeedsTiltedII = (tiltedVal != 0);
Ncv32u featureId = 0;
Ncv32u featureId = 0;
for(int l = 0; l < CV_HAAR_FEATURE_MAX; ++l) //by rects
{
Ncv32u rectX = feature->rect[l].r.x;
@@ -435,7 +440,8 @@ NCVStatus loadFromXML(const std::string &filename,
}
HaarFeatureDescriptor32 tmpFeatureDesc;
ncvStat = tmpFeatureDesc.create(haar.bNeedsTiltedII, featureId, haarFeatures.size() - featureId);
ncvStat = tmpFeatureDesc.create(haar.bNeedsTiltedII, bIsLeftNodeLeaf, bIsRightNodeLeaf,
featureId, haarFeatures.size() - featureId);
ncvAssertReturn(NCV_SUCCESS == ncvStat, ncvStat);
curNode.setFeatureDesc(tmpFeatureDesc);
@@ -453,14 +459,14 @@ NCVStatus loadFromXML(const std::string &filename,
}
nodeId++;
}
}
}
curStage.setNumClassifierRootNodes(treesCount);
haarStages.push_back(curStage);
haarStages.push_back(curStage);
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
//fill in cascade stats
haar.NumStages = haarStages.size();
@@ -472,8 +478,10 @@ NCVStatus loadFromXML(const std::string &filename,
Ncv32u offsetRoot = haarClassifierNodes.size();
for (Ncv32u i=0; i<haarClassifierNodes.size(); i++)
{
HaarFeatureDescriptor32 featureDesc = haarClassifierNodes[i].getFeatureDesc();
HaarClassifierNodeDescriptor32 nodeLeft = haarClassifierNodes[i].getLeftNodeDesc();
if (!nodeLeft.isLeaf())
if (!featureDesc.isLeftNodeLeaf())
{
Ncv32u newOffset = nodeLeft.getNextNodeOffset() + offsetRoot;
nodeLeft.create(newOffset);
@@ -481,7 +489,7 @@ NCVStatus loadFromXML(const std::string &filename,
haarClassifierNodes[i].setLeftNodeDesc(nodeLeft);
HaarClassifierNodeDescriptor32 nodeRight = haarClassifierNodes[i].getRightNodeDesc();
if (!nodeRight.isLeaf())
if (!featureDesc.isRightNodeLeaf())
{
Ncv32u newOffset = nodeRight.getNextNodeOffset() + offsetRoot;
nodeRight.create(newOffset);
@@ -490,8 +498,10 @@ NCVStatus loadFromXML(const std::string &filename,
}
for (Ncv32u i=0; i<h_TmpClassifierNotRootNodes.size(); i++)
{
HaarFeatureDescriptor32 featureDesc = h_TmpClassifierNotRootNodes[i].getFeatureDesc();
HaarClassifierNodeDescriptor32 nodeLeft = h_TmpClassifierNotRootNodes[i].getLeftNodeDesc();
if (!nodeLeft.isLeaf())
if (!featureDesc.isLeftNodeLeaf())
{
Ncv32u newOffset = nodeLeft.getNextNodeOffset() + offsetRoot;
nodeLeft.create(newOffset);
@@ -499,7 +509,7 @@ NCVStatus loadFromXML(const std::string &filename,
h_TmpClassifierNotRootNodes[i].setLeftNodeDesc(nodeLeft);
HaarClassifierNodeDescriptor32 nodeRight = h_TmpClassifierNotRootNodes[i].getRightNodeDesc();
if (!nodeRight.isLeaf())
if (!featureDesc.isRightNodeLeaf())
{
Ncv32u newOffset = nodeRight.getNextNodeOffset() + offsetRoot;
nodeRight.create(newOffset);