From 4eb0f3d2ddc3bf9bd4aa52eee09b832ce4facdc8 Mon Sep 17 00:00:00 2001 From: Xiao Li Date: Sun, 12 Aug 2012 23:18:31 -0700 Subject: [PATCH] port matching_to_many_images.cpp as cvmat#match_descriptors, and an example to use it --- examples/matching_to_many_images.rb | 16 ++++ examples/matching_to_many_images/query.png | Bin 0 -> 121403 bytes examples/matching_to_many_images/train/1.png | Bin 0 -> 118730 bytes examples/matching_to_many_images/train/2.png | Bin 0 -> 114372 bytes examples/matching_to_many_images/train/3.png | Bin 0 -> 120917 bytes .../train/trainImages.txt | 3 + ext/opencv/cvmat.cpp | 70 +++++++++++++++++- ext/opencv/cvmat.h | 2 + 8 files changed, 88 insertions(+), 3 deletions(-) create mode 100644 examples/matching_to_many_images.rb create mode 100755 examples/matching_to_many_images/query.png create mode 100755 examples/matching_to_many_images/train/1.png create mode 100755 examples/matching_to_many_images/train/2.png create mode 100755 examples/matching_to_many_images/train/3.png create mode 100755 examples/matching_to_many_images/train/trainImages.txt diff --git a/examples/matching_to_many_images.rb b/examples/matching_to_many_images.rb new file mode 100644 index 0000000..0fef936 --- /dev/null +++ b/examples/matching_to_many_images.rb @@ -0,0 +1,16 @@ +require 'opencv' +require 'benchmark' +include OpenCV + +data = File.join(File.dirname(__FILE__), 'matching_to_many_images') + +query = IplImage.load File.join(data, 'query.png'), CV_LOAD_IMAGE_GRAYSCALE +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} + + +matchs = query.match_descriptors("SURF", "SURF", "FlannBased", images) + +match, count = matchs.max_by {|image, count| count} + +puts "max match: #{image_files[images.index(match)]}" diff --git a/examples/matching_to_many_images/query.png b/examples/matching_to_many_images/query.png new file mode 100755 index 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z)ulp)h>n8Q z*%CoGU=vy=0BBGv9TCYQVX8*BC{b%84pl*lOaV0rL`4EtP(=~6ZB;y_s8Lbe7J+E= zR|Gu+g-oh_fByV<#X6C5ozB}e1Lz?`+DrxPl@o+QP)4Q4ZcACsh@MWd|^!*W-FSfB(k^ zWqtkqpWcCURfSgQ<(Wc}TBkmy89+^b{*RAHcV^T^isnoS5lC{fCOb8>m@vKOR-{x& z-QtYp>}6EAilb`IPL99);ZJ=2c%K|`BDOfH8(MkYOcW5U)oaU-uV!>SXT2Vg4sLj; zibRpJNTBtEWPpe-mC1#p58YEdea zs-|Jl=19OrQ-GFO1ppfT*H|P&X{g-S{qf`Tj-caIy55$i#q&T7i4b+vgmF((WfYMT zYcpzBX))}h{`&imbJSV0-v976OQju-BonhOimE;NmFLG!y3e}RO0BKD?QPE;o0_T` zt4Jt0dp;_Kxn@@Lb)L`XIeq*6pMD#u8Ps&NnR_JBm`X|Cj&yJYA}@|lYrJigvzw7mBS#~2+D|5ksw9It!S+O7DPb>0`z?T{Po=NcIBSS>v37Z z_ROJGbPP`07NZ2HDkUyA7D58R$!Yuf{U0xbJa3Obd>tfV9TiC>C`dIrE&Jy`ayLzj zs{IIA-CF5noi2)`X(X$syz;7+&@AM$*5N*Pzx?@6Z91!0+rLZ>yYB$I-Gq8JT9I#H_% z34mZEQmethod, rho, theta, threshold, param1, param2) -> cvseq(include CvLine or CvTwoPoints) * * Finds lines in binary image using a Hough transform. - * * method – + * * method – + * * The Hough transform variant, one of the following: * * - CV_HOUGH_STANDARD - classical or standard Hough transform. * * - CV_HOUGH_PROBABILISTIC - probabilistic Hough transform (more efficient in case if picture contains a few long linear segments). @@ -5104,12 +5106,14 @@ rb_moments(int argc, VALUE *argv, VALUE self) * * rho - Distance resolution in pixel-related units. * * theta - Angle resolution measured in radians. * * threshold - Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. - * * param1 – + * * param1 – + * * The first method-dependent parameter: * * For the classical Hough transform it is not used (0). * * For the probabilistic Hough transform it is the minimum line length. * * For the multi-scale Hough transform it is the divisor for the distance resolution . (The coarse distance resolution will be rho and the accurate resolution will be (rho / param1)). - * * param2 – + * * param2 – + * * The second method-dependent parameter: * * For the classical Hough transform it is not used (0). * * For the probabilistic Hough transform it is the maximum gap between line segments lying on the same line to treat them as a single line segment (i.e. to join them). @@ -5325,6 +5329,66 @@ rb_match_shapes(int argc, VALUE *argv, VALUE self) return rb_float_new(result); } + +/** + * Port from OpenCV sample: matching_to_many_images.cpp + * call-seq: + * match_descriptors(detector_type, descriptor_type, matcher_type, images) -> Hash + * + * Matching descriptors detected on one image to descriptors detected in image set. + * Returns a Hash contains match count of each image. + * + * detector_type is a string, options: "SURF" + * descriptor_type is a string, options: "SURF" + * matcher_type is a string, options: "FlannBased" + * images is an array of CvMat objects. + */ +VALUE +rb_match_descriptors(int argc, VALUE *argv, VALUE self) +{ + VALUE detectorType, descriptorType, matcherType, images; + rb_scan_args(argc, argv, "40", &detectorType, &descriptorType, &matcherType, &images); + + cv::Mat queryImage = CVMAT(self); + std::vector trainImages; + for(int i=0; i < RARRAY_LEN(images); i++) { + trainImages.push_back(CVMAT(RARRAY_PTR(images)[i])); + } + + // todo: validation + cv::Ptr featureDetector = cv::FeatureDetector::create(RSTRING_PTR(detectorType)); + cv::Ptr descriptorExtractor = cv::DescriptorExtractor::create(RSTRING_PTR(descriptorType)); + cv::Ptr descriptorMatcher = cv::DescriptorMatcher::create(RSTRING_PTR(matcherType)); + + std::vector queryKeypoints; + std::vector > trainKeypoints; + featureDetector->detect(queryImage, queryKeypoints); + featureDetector->detect(trainImages, trainKeypoints); + + cv::Mat queryDescriptors; + std::vector trainDescriptors; + descriptorExtractor->compute(queryImage, queryKeypoints, queryDescriptors); + descriptorExtractor->compute(trainImages, trainKeypoints, trainDescriptors); + + std::vector matches; + descriptorMatcher->add(trainDescriptors); + descriptorMatcher->train(); + descriptorMatcher->match(queryDescriptors, matches); + + VALUE _matches = rb_hash_new(); + for (size_t i=0; i comp diff --git a/ext/opencv/cvmat.h b/ext/opencv/cvmat.h index e16e03e..dca850e 100644 --- a/ext/opencv/cvmat.h +++ b/ext/opencv/cvmat.h @@ -220,6 +220,8 @@ VALUE rb_equalize_hist(VALUE self); /* Matching*/ VALUE rb_match_template(int argc, VALUE *argv, VALUE self); VALUE rb_match_shapes(int argc, VALUE *argv, VALUE self); +VALUE rb_match_descriptors(int argc, VALUE *argv, VALUE self); + /* Object Tracking */ VALUE rb_mean_shift(VALUE self, VALUE window, VALUE criteria); VALUE rb_cam_shift(VALUE self, VALUE window, VALUE criteria);