149 lines
4.4 KiB
C++
149 lines
4.4 KiB
C++
/************************************************************
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cvhaarclassifercascade.cpp -
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$Author: lsxi $
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Copyright (C) 2005-2007 Masakazu Yonekura
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************************************************************/
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#include "cvhaarclassifiercascade.h"
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/*
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* Document-class: OpenCV::CvHaarClassifierCascade
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*
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* Haar Feature-based Cascade Classifier for Object Detection
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*/
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__NAMESPACE_BEGIN_OPENCV
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__NAMESPACE_BEGIN_CVHAARCLASSIFERCASCADE
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VALUE rb_klass;
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VALUE
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rb_class()
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{
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return rb_klass;
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}
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VALUE
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rb_allocate(VALUE klass)
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{
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return OPENCV_OBJECT(klass, 0);
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}
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void
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cvhaarclassifiercascade_free(void* ptr)
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{
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if (ptr) {
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CvHaarClassifierCascade* cascade = (CvHaarClassifierCascade*)ptr;
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cvReleaseHaarClassifierCascade(&cascade);
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}
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}
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/*
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* Load trained cascade of haar classifers from file.
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*
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* @overload load(filename)
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* @param filename [String] Haar classifer file name
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* @return [CvHaarClassifierCascade] Object detector
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* @scope class
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* @opencv_func cvLoad
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*/
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VALUE
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rb_load(VALUE klass, VALUE path)
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{
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CvHaarClassifierCascade *cascade = NULL;
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try {
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cascade = (CvHaarClassifierCascade*)cvLoad(StringValueCStr(path), 0, 0, 0);
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}
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catch (cv::Exception& e) {
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raise_cverror(e);
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}
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if (!CV_IS_HAAR_CLASSIFIER(cascade))
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rb_raise(rb_eArgError, "invalid format haar classifier cascade file.");
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return Data_Wrap_Struct(klass, 0, cvhaarclassifiercascade_free, cascade);
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}
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/*
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* Detects objects of different sizes in the input image.
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*
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* @overload detect_objects(image, options = nil)
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* @param image [CvMat,IplImage] Matrix of the type CV_8U containing an image where objects are detected.
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* @param options [Hash] Options
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* @option options [Number] :scale_factor
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* Parameter specifying how much the image size is reduced at each image scale.
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* @option options [Number] :storage
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* Memory storage to store the resultant sequence of the object candidate rectangles
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* @option options [Number] :min_neighbors
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* Parameter specifying how many neighbors each candidate rectangle should have to retain it.
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* @option options [CvSize] :min_size
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* Minimum possible object size. Objects smaller than that are ignored.
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* @option options [CvSize] :max_size
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* Maximum possible object size. Objects larger than that are ignored.
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* @return [CvSeq<CvAvgComp>] Detected objects as a list of rectangles
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* @opencv_func cvHaarDetectObjects
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*/
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VALUE
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rb_detect_objects(int argc, VALUE *argv, VALUE self)
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{
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VALUE image, options;
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rb_scan_args(argc, argv, "11", &image, &options);
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double scale_factor;
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int flags, min_neighbors;
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CvSize min_size, max_size;
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VALUE storage_val;
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if (NIL_P(options)) {
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scale_factor = 1.1;
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flags = 0;
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min_neighbors = 3;
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min_size = max_size = cvSize(0, 0);
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storage_val = cCvMemStorage::new_object();
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}
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else {
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scale_factor = IF_DBL(LOOKUP_CVMETHOD(options, "scale_factor"), 1.1);
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flags = IF_INT(LOOKUP_CVMETHOD(options, "flags"), 0);
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min_neighbors = IF_INT(LOOKUP_CVMETHOD(options, "min_neighbors"), 3);
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VALUE min_size_val = LOOKUP_CVMETHOD(options, "min_size");
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min_size = NIL_P(min_size_val) ? cvSize(0, 0) : VALUE_TO_CVSIZE(min_size_val);
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VALUE max_size_val = LOOKUP_CVMETHOD(options, "max_size");
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max_size = NIL_P(max_size_val) ? cvSize(0, 0) : VALUE_TO_CVSIZE(max_size_val);
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storage_val = CHECK_CVMEMSTORAGE(LOOKUP_CVMETHOD(options, "storage"));
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}
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VALUE result = Qnil;
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try {
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CvSeq *seq = cvHaarDetectObjects(CVARR_WITH_CHECK(image), CVHAARCLASSIFIERCASCADE(self), CVMEMSTORAGE(storage_val),
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scale_factor, min_neighbors, flags, min_size, max_size);
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result = cCvSeq::new_sequence(cCvSeq::rb_class(), seq, cCvAvgComp::rb_class(), storage_val);
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if (rb_block_given_p()) {
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for(int i = 0; i < seq->total; ++i)
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rb_yield(REFER_OBJECT(cCvAvgComp::rb_class(), cvGetSeqElem(seq, i), storage_val));
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}
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}
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catch (cv::Exception& e) {
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raise_cverror(e);
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}
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return result;
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}
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void
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init_ruby_class()
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{
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#if 0
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// For documentation using YARD
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VALUE opencv = rb_define_module("OpenCV");
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#endif
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if (rb_klass)
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return;
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VALUE opencv = rb_module_opencv();
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rb_klass = rb_define_class_under(opencv, "CvHaarClassifierCascade", rb_cObject);
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rb_define_alloc_func(rb_klass, rb_allocate);
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rb_define_singleton_method(rb_klass, "load", RUBY_METHOD_FUNC(rb_load), 1);
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rb_define_method(rb_klass, "detect_objects", RUBY_METHOD_FUNC(rb_detect_objects), -1);
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}
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__NAMESPACE_END_CVHAARCLASSIFERCASCADE
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__NAMESPACE_END_OPENCV
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