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changed detector type, descriptor type and matcher type for matching descriptors to be optional arguments; and updated document for CvMat#match_descriptors

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Xiao Li 2012-08-14 14:45:34 -07:00
parent 4db0c33191
commit bf63bbfb86
2 changed files with 24 additions and 11 deletions
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2
examples/matching_to_many_images.rb
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@ -9,7 +9,7 @@ image_files = ['1.png', '2.png', '3.png'].map{|f| File.join(data, 'train', f)}
images = image_files.map{|f| IplImage.load f, CV_LOAD_IMAGE_GRAYSCALE} images = image_files.map{|f| IplImage.load f, CV_LOAD_IMAGE_GRAYSCALE}
matchs = query.match_descriptors("SURF", "SURF", "FlannBased", images) matchs = query.match_descriptors(images)
match_index, count = matchs.max_by {|image_index, count| count} match_index, count = matchs.max_by {|image_index, count| count}

33
ext/opencv/cvmat.cpp
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@ -5333,21 +5333,34 @@ rb_match_shapes(int argc, VALUE *argv, VALUE self)
/** /**
* Port from OpenCV sample: matching_to_many_images.cpp * Port from OpenCV sample: matching_to_many_images.cpp
* call-seq: * call-seq:
* match_descriptors(<i>detector_type, descriptor_type, matcher_type, images</i>) -> Hash * match_descriptors(<i>images[, detector_type="SURF"][, descriptor_type="SURF"][, matcher_type="FlannBased"]</i>) -> Hash
* *
* Matching descriptors detected on one image to descriptors detected in image set. * Matching descriptors detected on one image to descriptors detected in image array.
* Returns a Hash contains match count of each image index. * Returns a Hash contains match count of each image index.
* For example, a Hash {0 => 5, 2 => 10} means the images[0] has 5 key points matched, images[2] has 10 key points matched,
* and all of other images in the images array have no key point matched.
* Hence images[2] is the best match in general.
* *
* <i>detector_type</i> is a string, options: "SURF"
* <i>descriptor_type</i> is a string, options: "SURF"
* <i>matcher_type</i> is a string, options: "FlannBased"
* <i>images</i> is an array of CvMat objects. * <i>images</i> is an array of CvMat objects.
* <i>detector_type</i> is a string, default is "SURF", options: "SURF", "FAST", "SIFT", "STAR"
* <i>descriptor_type</i> is a string, default is "SURF", options: "SURF", "SIFT", "BRIEF"
* <i>matcher_type</i> is a string, default is "FlannBased", options: "FlannBased", "BruteForce"
*/ */
VALUE VALUE
rb_match_descriptors(int argc, VALUE *argv, VALUE self) rb_match_descriptors(int argc, VALUE *argv, VALUE self)
{ {
VALUE detectorType, descriptorType, matcherType, images; VALUE images, detector_type, descriptor_type, matcher_type;
rb_scan_args(argc, argv, "40", &detectorType, &descriptorType, &matcherType, &images); rb_scan_args(argc, argv, "13", &images, &detector_type, &descriptor_type, &matcher_type);
if (NIL_P(detector_type)) {
detector_type = rb_str_new2("SURF");
}
if (NIL_P(descriptor_type)) {
descriptor_type = rb_str_new2("SURF");
}
if (NIL_P(matcher_type)) {
matcher_type = rb_str_new2("FlannBased");
}
cv::Mat queryImage = CVMAT(self); cv::Mat queryImage = CVMAT(self);
std::vector<cv::Mat> trainImages; std::vector<cv::Mat> trainImages;
@ -5356,9 +5369,9 @@ rb_match_descriptors(int argc, VALUE *argv, VALUE self)
} }
// todo: validation // todo: validation
cv::Ptr<cv::FeatureDetector> featureDetector = cv::FeatureDetector::create(RSTRING_PTR(detectorType)); cv::Ptr<cv::FeatureDetector> featureDetector = cv::FeatureDetector::create(RSTRING_PTR(detector_type));
cv::Ptr<cv::DescriptorExtractor> descriptorExtractor = cv::DescriptorExtractor::create(RSTRING_PTR(descriptorType)); cv::Ptr<cv::DescriptorExtractor> descriptorExtractor = cv::DescriptorExtractor::create(RSTRING_PTR(descriptor_type));
cv::Ptr<cv::DescriptorMatcher> descriptorMatcher = cv::DescriptorMatcher::create(RSTRING_PTR(matcherType)); cv::Ptr<cv::DescriptorMatcher> descriptorMatcher = cv::DescriptorMatcher::create(RSTRING_PTR(matcher_type));
std::vector<cv::KeyPoint> queryKeypoints; std::vector<cv::KeyPoint> queryKeypoints;
std::vector<std::vector<cv::KeyPoint> > trainKeypoints; std::vector<std::vector<cv::KeyPoint> > trainKeypoints;