removed contrib, legacy and softcsscade modules; removed latentsvm and datamatrix detector from objdetect. removed haartraining and sft apps.
some of the stuff will be moved to opencv_contrib module. in order to make this PR pass buildbot, please, comment off opencv_legacy, opencv_contrib and opencv_softcascade test runs.
This commit is contained in:
Vadim Pisarevsky
@@ -144,125 +144,6 @@ CVAPI(int) cvRunHaarClassifierCascade( const CvHaarClassifierCascade* cascade,
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CvPoint pt, int start_stage CV_DEFAULT(0));
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/****************************************************************************************\
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* Latent SVM Object Detection functions *
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\****************************************************************************************/
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// DataType: STRUCT position
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// Structure describes the position of the filter in the feature pyramid
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// l - level in the feature pyramid
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// (x, y) - coordinate in level l
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typedef struct CvLSVMFilterPosition
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{
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int x;
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int y;
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int l;
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} CvLSVMFilterPosition;
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// DataType: STRUCT filterObject
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// Description of the filter, which corresponds to the part of the object
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// V - ideal (penalty = 0) position of the partial filter
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// from the root filter position (V_i in the paper)
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// penaltyFunction - vector describes penalty function (d_i in the paper)
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// pf[0] * x + pf[1] * y + pf[2] * x^2 + pf[3] * y^2
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// FILTER DESCRIPTION
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// Rectangular map (sizeX x sizeY),
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// every cell stores feature vector (dimension = p)
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// H - matrix of feature vectors
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// to set and get feature vectors (i,j)
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// used formula H[(j * sizeX + i) * p + k], where
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// k - component of feature vector in cell (i, j)
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// END OF FILTER DESCRIPTION
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typedef struct CvLSVMFilterObject{
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CvLSVMFilterPosition V;
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float fineFunction[4];
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int sizeX;
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int sizeY;
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int numFeatures;
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float *H;
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} CvLSVMFilterObject;
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// data type: STRUCT CvLatentSvmDetector
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// structure contains internal representation of trained Latent SVM detector
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// num_filters - total number of filters (root plus part) in model
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// num_components - number of components in model
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// num_part_filters - array containing number of part filters for each component
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// filters - root and part filters for all model components
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// b - biases for all model components
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// score_threshold - confidence level threshold
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typedef struct CvLatentSvmDetector
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{
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int num_filters;
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int num_components;
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int* num_part_filters;
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CvLSVMFilterObject** filters;
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float* b;
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float score_threshold;
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} CvLatentSvmDetector;
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// data type: STRUCT CvObjectDetection
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// structure contains the bounding box and confidence level for detected object
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// rect - bounding box for a detected object
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// score - confidence level
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typedef struct CvObjectDetection
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{
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CvRect rect;
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float score;
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} CvObjectDetection;
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//////////////// Object Detection using Latent SVM //////////////
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/*
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// load trained detector from a file
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//
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// API
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// CvLatentSvmDetector* cvLoadLatentSvmDetector(const char* filename);
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// INPUT
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// filename - path to the file containing the parameters of
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- trained Latent SVM detector
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// OUTPUT
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// trained Latent SVM detector in internal representation
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*/
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CVAPI(CvLatentSvmDetector*) cvLoadLatentSvmDetector(const char* filename);
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/*
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// release memory allocated for CvLatentSvmDetector structure
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//
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// API
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// void cvReleaseLatentSvmDetector(CvLatentSvmDetector** detector);
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// INPUT
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// detector - CvLatentSvmDetector structure to be released
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// OUTPUT
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*/
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CVAPI(void) cvReleaseLatentSvmDetector(CvLatentSvmDetector** detector);
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/*
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// find rectangular regions in the given image that are likely
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// to contain objects and corresponding confidence levels
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//
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// API
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// CvSeq* cvLatentSvmDetectObjects(const IplImage* image,
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// CvLatentSvmDetector* detector,
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// CvMemStorage* storage,
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// float overlap_threshold = 0.5f,
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// int numThreads = -1);
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// INPUT
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// image - image to detect objects in
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// detector - Latent SVM detector in internal representation
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// storage - memory storage to store the resultant sequence
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// of the object candidate rectangles
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// overlap_threshold - threshold for the non-maximum suppression algorithm
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= 0.5f [here will be the reference to original paper]
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// OUTPUT
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// sequence of detected objects (bounding boxes and confidence levels stored in CvObjectDetection structures)
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*/
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CVAPI(CvSeq*) cvLatentSvmDetectObjects(IplImage* image,
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CvLatentSvmDetector* detector,
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CvMemStorage* storage,
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float overlap_threshold CV_DEFAULT(0.5f),
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int numThreads CV_DEFAULT(-1));
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#ifdef __cplusplus
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}
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@@ -274,16 +155,6 @@ CV_EXPORTS CvSeq* cvHaarDetectObjectsForROC( const CvArr* image,
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CvSize min_size = cvSize(0, 0), CvSize max_size = cvSize(0, 0),
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bool outputRejectLevels = false );
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struct CvDataMatrixCode
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{
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char msg[4];
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CvMat* original;
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CvMat* corners;
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};
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CV_EXPORTS std::deque<CvDataMatrixCode> cvFindDataMatrix(CvMat *im);
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#endif
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#endif /* __OPENCV_OBJDETECT_C_H__ */
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