mirror of
https://github.com/ruby-opencv/ruby-opencv
synced 2023-03-27 23:22:12 -04:00
2947 lines
78 KiB
Ruby
Executable file
2947 lines
78 KiB
Ruby
Executable file
#!/usr/bin/env ruby
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# -*- mode: ruby; coding: utf-8 -*-
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require 'test/unit'
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require 'opencv'
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require File.expand_path(File.dirname(__FILE__)) + '/helper'
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include OpenCV
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# Tests for OpenCV::CvMat
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class TestCvMat < OpenCVTestCase
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def test_initialize
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m = CvMat.new(10, 20)
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assert_equal(10, m.rows)
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assert_equal(20, m.cols)
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assert_equal(:cv8u, m.depth)
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assert_equal(3, m.channel)
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depth_table = {
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CV_8U => :cv8u,
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CV_8S => :cv8s,
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CV_16U => :cv16u,
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CV_16S => :cv16s,
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CV_32S => :cv32s,
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CV_32F => :cv32f,
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CV_64F => :cv64f
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}
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[CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F,
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:cv8u, :cv8s, :cv16u, :cv16s, :cv32s, :cv32f, :cv64f].each { |depth|
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[1, 2, 3, 4].each { |ch|
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m = CvMat.new(10, 20, depth, ch)
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assert_equal(10, m.rows)
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assert_equal(20, m.cols)
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depth = depth_table[depth] unless depth.is_a? Symbol
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assert_equal(depth, m.depth)
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assert_equal(ch, m.channel)
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}
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}
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assert_raise(TypeError) {
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m = CvMat.new(DUMMY_OBJ, 20, :cv8u, 1)
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}
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assert_raise(TypeError) {
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m = CvMat.new(10, DUMMY_OBJ, :cv8u, 1)
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}
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assert_raise(TypeError) {
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m = CvMat.new(10, 20, :cv8u, DUMMY_OBJ)
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}
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end
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def test_load
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mat = CvMat.load(FILENAME_CAT)
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assert_equal(CvMat, mat.class)
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assert_equal(375, mat.cols)
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assert_equal(500, mat.rows)
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assert_equal(:cv8u, mat.depth)
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assert_equal(3, mat.channel)
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assert_equal('ebc0b85d3ac44ea60181c997f35d13df', hash_img(mat))
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mat = CvMat.load(FILENAME_CAT, CV_LOAD_IMAGE_GRAYSCALE)
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assert_equal(CvMat, mat.class)
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assert_equal(375, mat.cols)
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assert_equal(500, mat.rows)
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assert_equal(:cv8u, mat.depth)
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assert_equal(1, mat.channel)
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assert_equal('f0ae1d7f2d6b3a64d093e3181361f3a4', hash_img(mat))
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mat = CvMat.load(FILENAME_CAT, CV_LOAD_IMAGE_ANYDEPTH | CV_LOAD_IMAGE_ANYCOLOR)
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assert_equal(CvMat, mat.class)
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assert_equal(375, mat.cols)
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assert_equal(500, mat.rows)
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assert_equal(:cv8u, mat.depth)
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assert_equal(3, mat.channel)
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assert_equal('ebc0b85d3ac44ea60181c997f35d13df', hash_img(mat))
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assert_raise(ArgumentError) {
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CvMat.load
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}
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assert_raise(TypeError) {
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CvMat.load(DUMMY_OBJ)
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}
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assert_raise(TypeError) {
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CvMat.load(FILENAME_CAT, DUMMY_OBJ)
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}
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assert_raise(StandardError) {
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CvMat.load('file/does/not/exist')
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}
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end
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def test_save_image
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filename_jpg = 'save_image_test.jpg'
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filename_png = 'save_image_test.png'
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m = CvMat.new(20, 20, :cv8u, 1)
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File.delete filename_jpg if File.exists? filename_jpg
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m.save_image filename_jpg
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assert(File.exists? filename_jpg)
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File.delete filename_jpg if File.exists? filename_jpg
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m.save_image(filename_jpg, CV_IMWRITE_JPEG_QUALITY => 10)
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assert(File.exists? filename_jpg)
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File.delete filename_png if File.exists? filename_png
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m.save_image(filename_png, CV_IMWRITE_PNG_COMPRESSION => 9)
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assert(File.exists? filename_png)
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# Alias
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File.delete filename_jpg if File.exists? filename_jpg
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m.save filename_jpg
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assert(File.exists? filename_jpg)
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assert_raise(TypeError) {
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m.save_image(DUMMY_OBJ)
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}
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assert_raise(TypeError) {
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m.save_image(filename_jpg, DUMMY_OBJ)
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}
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File.delete filename_jpg if File.exists? filename_jpg
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File.delete filename_png if File.exists? filename_png
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end
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def test_encode
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mat = CvMat.load(FILENAME_CAT);
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jpg = mat.encode('.jpg')
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assert_equal('JFIF', jpg[6, 4].map(&:chr).join) # Is jpeg format?
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jpg = mat.encode('.jpg', CV_IMWRITE_JPEG_QUALITY => 10)
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assert_equal('JFIF', jpg[6, 4].map(&:chr).join)
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png = mat.encode('.png')
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assert_equal('PNG', png[1, 3].map(&:chr).join) # Is png format?
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png = mat.encode('.png', CV_IMWRITE_PNG_COMPRESSION => 9)
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assert_equal('PNG', png[1, 3].map(&:chr).join)
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assert_raise(TypeError) {
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mat.encode(DUMMY_OBJ)
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}
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assert_raise(TypeError) {
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mat.encode('.jpg', DUMMY_OBJ)
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}
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# Uncomment the following lines to see the result images
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#
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# open('test-jpeg.jpg', 'wb') { |f|
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# f.write jpg.pack("c*")
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# }
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# open('test-png.png', 'wb') { |f|
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# f.write png.pack("c*")
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# }
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end
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def test_decode
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data = nil
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open(FILENAME_CAT, 'rb') { |f|
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data = f.read
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}
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data_ary = data.unpack("c*")
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data_mat = CvMat.new(1, data_ary.size).set_data(data_ary)
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expected = CvMat.load(FILENAME_CAT)
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mat1 = CvMat.decode(data)
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mat2 = CvMat.decode(data_ary)
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mat3 = CvMat.decode(data_mat)
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mat4 = CvMat.decode(data, CV_LOAD_IMAGE_COLOR)
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mat5 = CvMat.decode(data_ary, CV_LOAD_IMAGE_COLOR)
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mat6 = CvMat.decode(data_mat, CV_LOAD_IMAGE_COLOR)
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expected_hash = hash_img(expected)
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[mat1, mat2, mat3, mat4, mat5, mat6].each { |mat|
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assert_equal(CvMat, mat.class)
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assert_equal(expected.rows, mat.rows)
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assert_equal(expected.cols, mat.cols)
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assert_equal(expected.channel, mat.channel)
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assert_equal(expected_hash, hash_img(mat))
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}
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expected_c1 = CvMat.load(FILENAME_CAT, CV_LOAD_IMAGE_GRAYSCALE)
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mat1c1 = CvMat.decode(data, CV_LOAD_IMAGE_GRAYSCALE)
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mat2c1 = CvMat.decode(data_ary, CV_LOAD_IMAGE_GRAYSCALE)
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mat3c1 = CvMat.decode(data_mat, CV_LOAD_IMAGE_GRAYSCALE)
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expected_hash_c1 = hash_img(expected_c1)
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[mat1c1, mat2c1, mat3c1].each { |mat|
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assert_equal(CvMat, mat.class)
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assert_equal(expected_c1.rows, mat.rows)
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assert_equal(expected_c1.cols, mat.cols)
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assert_equal(expected_c1.channel, mat.channel)
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assert_equal(expected_hash_c1, hash_img(mat))
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}
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assert_raise(TypeError) {
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CvMat.decode(DUMMY_OBJ)
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}
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assert_raise(TypeError) {
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CvMat.decode(data, DUMMY_OBJ)
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}
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# Uncomment the following line to show the result images
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# snap mat1, mat2, mat3
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end
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def test_GOOD_FEATURES_TO_TRACK_OPTION
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assert_equal(0xff, CvMat::GOOD_FEATURES_TO_TRACK_OPTION[:max])
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assert_nil(CvMat::GOOD_FEATURES_TO_TRACK_OPTION[:mask])
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assert_equal(3, CvMat::GOOD_FEATURES_TO_TRACK_OPTION[:block_size])
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assert((not CvMat::GOOD_FEATURES_TO_TRACK_OPTION[:use_harris]))
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assert_in_delta(0.04, CvMat::GOOD_FEATURES_TO_TRACK_OPTION[:k], 0.01)
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end
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def test_FIND_CONTOURS_OPTION
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assert_equal(1, CvMat::FIND_CONTOURS_OPTION[:mode])
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assert_equal(2, CvMat::FIND_CONTOURS_OPTION[:method])
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assert_equal(0, CvMat::FIND_CONTOURS_OPTION[:offset].x)
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assert_equal(0, CvMat::FIND_CONTOURS_OPTION[:offset].y)
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end
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def test_OPTICAL_FLOW_HS_OPTION
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assert_in_delta(0.0005, CvMat::OPTICAL_FLOW_HS_OPTION[:lambda], 0.000001)
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assert_equal(1, CvMat::OPTICAL_FLOW_HS_OPTION[:criteria].max)
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assert_in_delta(0.001, CvMat::OPTICAL_FLOW_HS_OPTION[:criteria].eps, 0.00001)
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end
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def test_OPTICAL_FLOW_BM_OPTION
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assert_equal(4, CvMat::OPTICAL_FLOW_BM_OPTION[:block_size].width)
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assert_equal(4, CvMat::OPTICAL_FLOW_BM_OPTION[:block_size].height)
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assert_equal(1, CvMat::OPTICAL_FLOW_BM_OPTION[:shift_size].width)
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assert_equal(1, CvMat::OPTICAL_FLOW_BM_OPTION[:shift_size].height)
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assert_equal(4, CvMat::OPTICAL_FLOW_BM_OPTION[:max_range].width)
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assert_equal(4, CvMat::OPTICAL_FLOW_BM_OPTION[:max_range].height)
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end
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def test_FIND_FUNDAMENTAL_MAT_OPTION
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assert((not CvMat::FIND_FUNDAMENTAL_MAT_OPTION[:with_status]))
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assert_in_delta(1.0, CvMat::FIND_FUNDAMENTAL_MAT_OPTION[:maximum_distance], 0.01)
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assert_in_delta(0.99, CvMat::FIND_FUNDAMENTAL_MAT_OPTION[:desirable_level], 0.01)
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end
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def test_to_s
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m = CvMat.new(10, 20)
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assert_equal('<OpenCV::CvMat:20x10,depth=cv8u,channel=3>', m.to_s)
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m = CvMat.new(10, 20, :cv16s)
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assert_equal('<OpenCV::CvMat:20x10,depth=cv16s,channel=3>', m.to_s)
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m = CvMat.new(10, 20, :cv32f, 1)
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assert_equal('<OpenCV::CvMat:20x10,depth=cv32f,channel=1>', m.to_s)
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end
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def test_inside
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m = CvMat.new(20, 10)
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assert(m.inside? CvPoint.new(0, 0))
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assert(m.inside? CvPoint.new(9, 19))
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assert((not m.inside? CvPoint.new(10, 0)))
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assert((not m.inside? CvPoint.new(0, 20)))
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assert((not m.inside? CvPoint.new(10, 20)))
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end
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def test_to_IplConvKernel
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kernel = CvMat.new(10, 20).to_IplConvKernel(CvPoint.new(2, 3))
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assert_equal(10, kernel.rows)
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assert_equal(20, kernel.cols)
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assert_equal(2, kernel.anchor.x)
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assert_equal(3, kernel.anchor.y)
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assert_equal(2, kernel.anchor_x)
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assert_equal(3, kernel.anchor_y)
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end
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def test_create_mask
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mask = CvMat.new(10, 20).create_mask
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assert_equal(20, mask.width)
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assert_equal(10, mask.height)
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assert_equal(:cv8u, mask.depth)
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assert_equal(1, mask.channel)
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end
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def test_fields
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m = CvMat.new(20, 10)
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assert_equal(10, m.width)
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assert_equal(10, m.columns)
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assert_equal(10, m.cols)
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assert_equal(20, m.height)
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assert_equal(20, m.rows)
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assert_equal(:cv8u, m.depth)
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assert_equal(3, m.channel)
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m = CvMat.new(20, 10, :cv16s, 1)
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assert_equal(10, m.width)
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assert_equal(10, m.columns)
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assert_equal(10, m.cols)
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assert_equal(20, m.height)
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assert_equal(20, m.rows)
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assert_equal(:cv16s, m.depth)
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assert_equal(1, m.channel)
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end
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def test_clone
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m1 = create_cvmat(10, 20)
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m2 = m1.clone
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assert_equal(m1.data, m2.data)
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end
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def test_copy
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m1 = create_cvmat(10, 20, CV_32F, 1) { |j, i, c| CvScalar.new(c) }
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m2 = m1.copy
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assert_equal(m1.data, m2.data)
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m2 = create_cvmat(10, 20, CV_32F, 1).zero
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m3 = m1.copy(m2)
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assert_equal(m1.data, m2.data)
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assert_equal(m1.data, m3.data)
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rows, cols = m1.rows, m1.cols
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mask = create_cvmat(rows, cols, CV_8U, 1) { |j, i, c|
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val = (i > cols / 2) ? 0 : 255
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CvScalar.new(val)
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}
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m2_orig = m2.copy
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m3 = m1.copy(m2, mask)
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rows.times { |j|
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cols.times { |i|
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expected = (mask[j, i][0] == 0) ? m2_orig[j, i] : m1[j, i]
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assert_cvscalar_equal(expected, m2[j, i])
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assert_cvscalar_equal(expected, m3[j, i])
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}
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}
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assert_raise(TypeError) {
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m1.copy(DUMMY_OBJ)
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}
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end
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def test_convert_depth
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m = CvMat.new(10, 20, :cv32f)
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assert_equal(:cv8u, m.to_8u.depth)
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assert_equal(:cv8s, m.to_8s.depth)
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assert_equal(:cv16u, m.to_16u.depth)
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assert_equal(:cv16s, m.to_16s.depth)
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assert_equal(:cv32s, m.to_32s.depth)
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assert_equal(:cv32f, m.to_32f.depth)
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assert_equal(:cv64f, m.to_64f.depth)
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end
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def test_vector
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m = CvMat.new(1, 2)
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assert(m.vector?)
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m = CvMat.new(2, 2)
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assert((not m.vector?))
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end
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def test_square
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m = CvMat.new(2, 2)
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assert(m.square?)
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m = CvMat.new(1, 2)
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assert((not m.square?))
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end
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def test_to_CvMat
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m1 = CvMat.new(2, 3, :cv32f, 4)
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m2 = m1.to_CvMat
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assert_equal(CvMat, m2.class)
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assert_equal(m1.rows, m2.rows)
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assert_equal(m1.cols, m2.cols)
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assert_equal(m1.depth, m2.depth)
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assert_equal(m1.channel, m2.channel)
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assert_equal(m1.data, m2.data)
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end
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def test_sub_rect
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m1 = create_cvmat(10, 10)
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assert_raise(ArgumentError) {
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m1.sub_rect
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}
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m2 = m1.sub_rect(CvRect.new(0, 0, 2, 3))
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assert_equal(2, m2.width)
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assert_equal(3, m2.height)
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m2.height.times { |j|
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m2.width.times { |i|
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assert_cvscalar_equal(m1[j, i], m2[j, i])
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}
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}
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topleft = CvPoint.new(2, 3)
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m2 = m1.sub_rect(topleft, CvSize.new(4, 5))
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assert_equal(4, m2.width)
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assert_equal(5, m2.height)
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m2.height.times { |j|
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m2.width.times { |i|
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assert_cvscalar_equal(m1[topleft.y + j, topleft.x + i], m2[j, i])
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}
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}
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topleft = CvPoint.new(1, 2)
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m2 = m1.sub_rect(topleft.x, topleft.y, 3, 4)
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assert_equal(3, m2.width)
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assert_equal(4, m2.height)
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m2.height.times { |j|
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m2.width.times { |i|
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assert_cvscalar_equal(m1[topleft.y + j, topleft.x + i], m2[j, i])
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}
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}
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# Alias
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m2 = m1.subrect(CvRect.new(0, 0, 2, 3))
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assert_equal(2, m2.width)
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assert_equal(3, m2.height)
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m2.height.times { |j|
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m2.width.times { |i|
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assert_cvscalar_equal(m1[j, i], m2[j, i])
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}
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}
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assert_raise(TypeError) {
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m1.sub_rect(DUMMY_OBJ)
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}
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assert_raise(TypeError) {
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m1.sub_rect(DUMMY_OBJ, CvSize.new(1, 2))
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}
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assert_raise(TypeError) {
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m1.sub_rect(CvPoint.new(1, 2), DUMMY_OBJ)
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}
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assert_raise(TypeError) {
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m1.sub_rect(DUMMY_OBJ, 2, 3, 4)
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}
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assert_raise(TypeError) {
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m1.sub_rect(1, DUMMY_OBJ, 3, 4)
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}
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assert_raise(TypeError) {
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m1.sub_rect(1, 2, DUMMY_OBJ, 4)
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}
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assert_raise(TypeError) {
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m1.sub_rect(1, 2, 3, DUMMY_OBJ)
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}
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end
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def test_get_rows
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m1 = create_cvmat(10, 20) { |j, i, c| CvScalar.new(c) }
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row = 2
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m2 = m1.get_rows(row)
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assert_equal(1, m2.rows)
|
|
assert_equal(m1.cols, m2.cols)
|
|
m1.cols.times { |i|
|
|
assert_cvscalar_equal(m1[row, i], m2[i])
|
|
}
|
|
|
|
row1 = 3..7
|
|
row2 = 2...8
|
|
[row1, row2].each { |row|
|
|
m3 = m1.get_rows(row)
|
|
w = (row.exclude_end?) ? row.last - row.begin : row.last - row.begin + 1
|
|
assert_equal(w, m3.rows)
|
|
assert_equal(m1.cols, m3.cols)
|
|
|
|
m3.rows.times { |j|
|
|
m3.cols.times { |i|
|
|
assert_cvscalar_equal(m1[row.begin + j, i], m3[j, i])
|
|
}
|
|
}
|
|
}
|
|
|
|
[row1, row2].each { |row|
|
|
delta = 2
|
|
m3 = m1.get_rows(row, 2)
|
|
w = (((row.exclude_end?) ? row.last - row.begin : row.last - row.begin + 1).to_f / delta).ceil
|
|
assert_equal(w, m3.rows)
|
|
assert_equal(m1.cols, m3.cols)
|
|
|
|
m3.rows.times { |j|
|
|
m3.cols.times { |i|
|
|
assert_cvscalar_equal(m1[row.begin + j * delta, i], m3[j, i])
|
|
}
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.get_rows(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m1.get_rows(1, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_get_cols
|
|
m1 = create_cvmat(10, 20) { |j, i, c| CvScalar.new(c) }
|
|
|
|
col = 2
|
|
m2 = m1.get_cols(col)
|
|
assert_equal(m1.rows, m2.rows)
|
|
assert_equal(1, m2.cols)
|
|
m1.height.times { |j|
|
|
assert_cvscalar_equal(m1[j, col], m2[j])
|
|
}
|
|
|
|
col1 = 3..7
|
|
col2 = 2...8
|
|
[col1, col2].each { |col|
|
|
m3 = m1.get_cols(col)
|
|
w = (col.exclude_end?) ? col.last - col.begin : col.last - col.begin + 1
|
|
assert_equal(m1.rows, m3.rows)
|
|
assert_equal(w, m3.cols)
|
|
|
|
m3.rows.times { |j|
|
|
m3.cols.times { |i|
|
|
assert_cvscalar_equal(m1[j, col.begin + i], m3[j, i])
|
|
}
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.get_cols(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_each_row
|
|
m1 = create_cvmat(2, 3)
|
|
a = [[1, 2, 3], [4, 5, 6]]
|
|
a.map! { |a1|
|
|
a1.map! { |a2|
|
|
CvScalar.new(a2, a2, a2, a2).to_ary
|
|
}
|
|
}
|
|
|
|
j = 0
|
|
m1.each_row { |r|
|
|
a[j].size.times { |i|
|
|
assert_cvscalar_equal(a[j][i], r[i])
|
|
}
|
|
j += 1
|
|
}
|
|
end
|
|
|
|
def test_each_col
|
|
m1 = create_cvmat(2, 3)
|
|
a = [[1, 4], [2, 5], [3, 6]]
|
|
a.map! { |a1|
|
|
a1.map! { |a2|
|
|
CvScalar.new(a2, a2, a2, a2).to_ary
|
|
}
|
|
}
|
|
|
|
j = 0
|
|
m1.each_col { |c|
|
|
a[j].size.times { |i|
|
|
assert_cvscalar_equal(a[j][i], c[i])
|
|
}
|
|
j += 1
|
|
}
|
|
|
|
# Alias
|
|
j = 0
|
|
m1.each_column { |c|
|
|
a[j].size.times { |i|
|
|
assert_cvscalar_equal(a[j][i], c[i])
|
|
}
|
|
j += 1
|
|
}
|
|
end
|
|
|
|
def test_diag
|
|
m = create_cvmat(5, 5)
|
|
a = [1, 7, 13, 19, 25].map { |x| CvScalar.new(x, x, x, x) }
|
|
d = m.diag
|
|
|
|
a.each_with_index { |s, i|
|
|
assert_cvscalar_equal(s, d[i])
|
|
}
|
|
|
|
a = [2, 8, 14, 20].map { |x| CvScalar.new(x, x, x, x) }
|
|
d = m.diag(1)
|
|
a.each_with_index { |s, i|
|
|
assert_cvscalar_equal(s, d[i])
|
|
}
|
|
|
|
a = [6, 12, 18, 24].map { |x| CvScalar.new(x, x, x, x) }
|
|
d = m.diag(-1)
|
|
a.each_with_index { |s, i|
|
|
assert_cvscalar_equal(s, d[i])
|
|
}
|
|
|
|
# Alias
|
|
a = [1, 7, 13, 19, 25].map { |x| CvScalar.new(x, x, x, x) }
|
|
d = m.diagonal
|
|
a.each_with_index { |s, i|
|
|
assert_cvscalar_equal(s, d[i])
|
|
}
|
|
|
|
[m.rows, m.cols, -m.rows, -m.cols].each { |d|
|
|
assert_raise(CvStsOutOfRange) {
|
|
m.diag(d)
|
|
}
|
|
}
|
|
end
|
|
|
|
def test_size
|
|
m = CvMat.new(2, 3)
|
|
assert_equal(3, m.size.width)
|
|
assert_equal(2, m.size.height)
|
|
end
|
|
|
|
def test_dims
|
|
m = CvMat.new(2, 3)
|
|
assert_equal([2, 3], m.dims)
|
|
end
|
|
|
|
def test_dim_size
|
|
m = CvMat.new(2, 3)
|
|
assert_equal(2, m.dim_size(0))
|
|
assert_equal(3, m.dim_size(1))
|
|
|
|
assert_raise(TypeError) {
|
|
m.dim_size(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_aref
|
|
m = create_cvmat(2, 3)
|
|
assert_cvscalar_equal(CvScalar.new(1, 1, 1, 1), m[0])
|
|
assert_cvscalar_equal(CvScalar.new(5, 5, 5, 5), m[4])
|
|
assert_cvscalar_equal(CvScalar.new(2, 2, 2, 2), m[0, 1])
|
|
assert_cvscalar_equal(CvScalar.new(4, 4, 4, 4), m[1, 0])
|
|
assert_cvscalar_equal(CvScalar.new(2, 2, 2, 2), m[0, 1, 2])
|
|
assert_cvscalar_equal(CvScalar.new(4, 4, 4, 4), m[1, 0, 3, 4])
|
|
|
|
# Alias
|
|
assert_cvscalar_equal(CvScalar.new(1, 1, 1, 1), m.at(0))
|
|
|
|
assert_raise(TypeError) {
|
|
m[DUMMY_OBJ]
|
|
}
|
|
|
|
assert_raise(CvStsOutOfRange) {
|
|
m[-1]
|
|
}
|
|
assert_raise(CvStsOutOfRange) {
|
|
m[6]
|
|
}
|
|
assert_raise(CvStsOutOfRange) {
|
|
m[2, 2]
|
|
}
|
|
assert_raise(CvStsOutOfRange) {
|
|
m[1, 3]
|
|
}
|
|
assert_raise(CvStsOutOfRange) {
|
|
m[2, 2, 1]
|
|
}
|
|
assert_raise(CvStsOutOfRange) {
|
|
m[1, 3, 1]
|
|
}
|
|
end
|
|
|
|
def test_aset
|
|
m = create_cvmat(2, 3)
|
|
m[0] = CvScalar.new(10, 10, 10, 10)
|
|
assert_cvscalar_equal(CvScalar.new(10, 10, 10, 10), m[0])
|
|
m[1, 0] = CvScalar.new(20, 20, 20, 20)
|
|
assert_cvscalar_equal(CvScalar.new(20, 20, 20, 20), m[1, 0])
|
|
m[1, 0, 2] = CvScalar.new(4, 4, 4, 4)
|
|
assert_cvscalar_equal(CvScalar.new(4, 4, 4, 4), m[1, 0])
|
|
m[1, 0, 2, 4] = CvScalar.new(5, 5, 5, 5)
|
|
assert_cvscalar_equal(CvScalar.new(5, 5, 5, 5), m[1, 0])
|
|
|
|
assert_raise(TypeError) {
|
|
m[DUMMY_OBJ] = CvScalar.new(10, 10, 10, 10)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m[0] = DUMMY_OBJ
|
|
}
|
|
|
|
assert_raise(CvStsOutOfRange) {
|
|
m[-1]
|
|
}
|
|
assert_raise(CvStsOutOfRange) {
|
|
m[6]
|
|
}
|
|
assert_raise(CvStsOutOfRange) {
|
|
m[2, 2]
|
|
}
|
|
assert_raise(CvStsOutOfRange) {
|
|
m[1, 3]
|
|
}
|
|
assert_raise(CvStsOutOfRange) {
|
|
m[2, 2, 1]
|
|
}
|
|
assert_raise(CvStsOutOfRange) {
|
|
m[1, 3, 1]
|
|
}
|
|
end
|
|
|
|
def test_set_data
|
|
[CV_8U, CV_8S, CV_16U, CV_16S, CV_32S].each { |depth|
|
|
a = [10, 20, 30, 40, 50, 60]
|
|
m = CvMat.new(2, 3, depth, 1)
|
|
m.set_data(a)
|
|
(m.rows * m.cols).times { |i|
|
|
assert_equal(a[i], m[i][0])
|
|
}
|
|
}
|
|
|
|
[CV_32F, CV_64F].each { |depth|
|
|
a = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6]
|
|
m = CvMat.new(2, 3, depth, 1)
|
|
m.set_data(a)
|
|
(m.rows * m.cols).times { |i|
|
|
assert_in_delta(a[i], m[i][0], 1.0e-5)
|
|
}
|
|
}
|
|
|
|
a = [[10, 20, 30], [40, 50, 60]]
|
|
m = CvMat.new(2, 3, CV_8U, 1)
|
|
m.set_data(a)
|
|
(m.rows * m.cols).times { |i|
|
|
assert_equal(a.flatten[i], m[i][0])
|
|
}
|
|
|
|
[CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F].each { |depth|
|
|
m = CvMat.new(2, 3, depth, 1)
|
|
assert_raise(TypeError) {
|
|
a = [DUMMY_OBJ] * 6
|
|
m.set_data(a)
|
|
}
|
|
}
|
|
end
|
|
|
|
def test_fill
|
|
m1 = create_cvmat(2, 3)
|
|
m2 = m1.fill(CvScalar.new(1, 2, 3, 4))
|
|
m1.fill!(CvScalar.new(1, 2, 3, 4))
|
|
m2.height.times { |j|
|
|
m2.width.times { |i|
|
|
assert_cvscalar_equal(CvScalar.new(1, 2, 3, 4), m1[j, i])
|
|
assert_cvscalar_equal(CvScalar.new(1, 2, 3, 4), m2[j, i])
|
|
}
|
|
}
|
|
|
|
m1 = create_cvmat(5, 5)
|
|
m0 = m1.clone
|
|
mask = CvMat.new(m1.height, m1.width, :cv8u, 1).clear
|
|
2.times { |j|
|
|
2.times { |i|
|
|
mask[j, i] = CvScalar.new(1, 1, 1, 1)
|
|
}
|
|
}
|
|
|
|
m2 = m1.fill(CvScalar.new(1, 2, 3, 4), mask)
|
|
m1.fill!(CvScalar.new(1, 2, 3, 4), mask)
|
|
m2.height.times { |j|
|
|
m2.width.times { |i|
|
|
if i < 2 and j < 2
|
|
assert_cvscalar_equal(CvScalar.new(1, 2, 3, 4), m1[j, i])
|
|
assert_cvscalar_equal(CvScalar.new(1, 2, 3, 4), m2[j, i])
|
|
else
|
|
assert_cvscalar_equal(m0[j, i], m1[j, i])
|
|
assert_cvscalar_equal(m0[j, i], m2[j, i])
|
|
end
|
|
}
|
|
}
|
|
|
|
# Alias
|
|
m1 = create_cvmat(2, 3)
|
|
m2 = m1.set(CvScalar.new(1, 2, 3, 4))
|
|
m1.set!(CvScalar.new(1, 2, 3, 4))
|
|
m2.height.times { |j|
|
|
m2.width.times { |i|
|
|
assert_cvscalar_equal(CvScalar.new(1, 2, 3, 4), m1[j, i])
|
|
assert_cvscalar_equal(CvScalar.new(1, 2, 3, 4), m2[j, i])
|
|
}
|
|
}
|
|
|
|
m1 = create_cvmat(5, 5)
|
|
m0 = m1.clone
|
|
mask = CvMat.new(m1.height, m1.width, CV_8U, 1).clear
|
|
2.times { |j|
|
|
2.times { |i|
|
|
mask[j, i] = CvScalar.new(1, 1, 1, 1)
|
|
}
|
|
}
|
|
|
|
m2 = m1.set(CvScalar.new(1, 2, 3, 4), mask)
|
|
m1.set!(CvScalar.new(1, 2, 3, 4), mask)
|
|
m2.height.times { |j|
|
|
m2.width.times { |i|
|
|
if i < 2 and j < 2
|
|
assert_cvscalar_equal(CvScalar.new(1, 2, 3, 4), m1[j, i])
|
|
assert_cvscalar_equal(CvScalar.new(1, 2, 3, 4), m2[j, i])
|
|
else
|
|
assert_cvscalar_equal(m0[j, i], m1[j, i])
|
|
assert_cvscalar_equal(m0[j, i], m2[j, i])
|
|
end
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.fill(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m1.fill(CvScalar.new(1), DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_clear
|
|
m1 = create_cvmat(2, 3)
|
|
m2 = m1.clear
|
|
m1.clear!
|
|
m2.height.times { |j|
|
|
m2.width.times { |i|
|
|
assert_cvscalar_equal(CvScalar.new(0, 0, 0, 0), m1[j, i])
|
|
assert_cvscalar_equal(CvScalar.new(0, 0, 0, 0), m2[j, i])
|
|
}
|
|
}
|
|
|
|
# Alias
|
|
m1 = create_cvmat(2, 3)
|
|
m2 = m1.set_zero
|
|
m1.set_zero!
|
|
m3 = create_cvmat(2, 3)
|
|
m4 = m3.zero
|
|
m3.zero!
|
|
m2.height.times { |j|
|
|
m2.width.times { |i|
|
|
assert_cvscalar_equal(CvScalar.new(0, 0, 0, 0), m1[j, i])
|
|
assert_cvscalar_equal(CvScalar.new(0, 0, 0, 0), m2[j, i])
|
|
assert_cvscalar_equal(CvScalar.new(0, 0, 0, 0), m3[j, i])
|
|
assert_cvscalar_equal(CvScalar.new(0, 0, 0, 0), m4[j, i])
|
|
}
|
|
}
|
|
end
|
|
|
|
def test_identity
|
|
m1 = create_cvmat(5, 5)
|
|
m2 = m1.identity
|
|
m1.identity!
|
|
m2.height.times { |j|
|
|
m2.width.times { |i|
|
|
if i == j
|
|
assert_cvscalar_equal(CvScalar.new(1, 0, 0, 0), m1[j, i])
|
|
assert_cvscalar_equal(CvScalar.new(1, 0, 0, 0), m2[j, i])
|
|
else
|
|
assert_cvscalar_equal(CvScalar.new(0, 0, 0, 0), m1[j, i])
|
|
assert_cvscalar_equal(CvScalar.new(0, 0, 0, 0), m2[j, i])
|
|
end
|
|
}
|
|
}
|
|
|
|
m1 = CvMat.new(5, 5, :cv8u, 4)
|
|
s = CvScalar.new(1, 2, 3, 4)
|
|
m2 = m1.identity(s)
|
|
m1.identity!(s)
|
|
m2.height.times { |j|
|
|
m2.width.times { |i|
|
|
if i == j
|
|
assert_cvscalar_equal(s, m1[j, i])
|
|
assert_cvscalar_equal(s, m2[j, i])
|
|
else
|
|
assert_cvscalar_equal(CvScalar.new(0, 0, 0, 0), m1[j, i])
|
|
assert_cvscalar_equal(CvScalar.new(0, 0, 0, 0), m2[j, i])
|
|
end
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.identity(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_range
|
|
m1 = CvMat.new(1, 10, CV_32S, 1)
|
|
m2 = m1.range(0, m1.cols)
|
|
m1.range!(0, m1.cols)
|
|
m2.width.times { |i|
|
|
assert_cvscalar_equal(CvScalar.new(i, 0, 0, 0), m1[0, i])
|
|
assert_cvscalar_equal(CvScalar.new(i, 0, 0, 0), m2[0, i])
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.range(DUMMY_OBJ, 2)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m1.range(1, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_reshape
|
|
m = create_cvmat(2, 3, CV_8U, 3)
|
|
|
|
vec = m.reshape(:rows => 1)
|
|
assert_equal(6, vec.width)
|
|
assert_equal(1, vec.height)
|
|
size = m.width * m.height
|
|
size.times { |i|
|
|
assert_cvscalar_equal(m[i], vec[i])
|
|
}
|
|
|
|
ch1 = m.reshape(:channel => 1)
|
|
assert_equal(9, ch1.width)
|
|
assert_equal(2, ch1.height)
|
|
|
|
m.height.times { |j|
|
|
m.width.times { |i|
|
|
s1 = ch1[j, i * 3][0]
|
|
s2 = ch1[j, i * 3 + 1][0]
|
|
s3 = ch1[j, i * 3 + 2][0]
|
|
assert_cvscalar_equal(m[j, i], CvScalar.new(s1, s2, s3, 0))
|
|
}
|
|
}
|
|
|
|
[DUMMY_OBJ, { :rows => DUMMY_OBJ }, { :channel => DUMMY_OBJ }].each { |arg|
|
|
assert_raise(TypeError) {
|
|
m.reshape(arg)
|
|
}
|
|
}
|
|
end
|
|
|
|
def test_repeat
|
|
m1 = create_cvmat(2, 3, :cv8u, 3)
|
|
m2 = CvMat.new(6, 9, :cv8u, 3)
|
|
m2 = m1.repeat(m2)
|
|
m2.height.times { |j|
|
|
m2.width.times { |i|
|
|
a = m1[j % m1.height, i % m1.width]
|
|
assert_cvscalar_equal(m2[j, i], a)
|
|
}
|
|
}
|
|
assert_raise(TypeError) {
|
|
m1.repeat(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_flip
|
|
m0 = create_cvmat(2, 3)
|
|
|
|
m1 = m0.clone
|
|
m1.flip!(:x)
|
|
m2 = m0.flip(:x)
|
|
m3 = m0.clone
|
|
m3.flip!(:y)
|
|
m4 = m0.flip(:y)
|
|
m5 = m0.clone
|
|
m5.flip!(:xy)
|
|
m6 = m0.flip(:xy)
|
|
m7 = m0.clone
|
|
m7.flip!
|
|
m8 = m0.flip
|
|
|
|
[m1, m2, m3, m4, m5, m6, m7, m8].each { |m|
|
|
assert_equal(m0.height, m.height)
|
|
assert_equal(m0.width, m.width)
|
|
}
|
|
m0.height.times { |j|
|
|
m0.width.times { |i|
|
|
ri = m0.width - i - 1
|
|
rj = m0.height - j - 1
|
|
assert_cvscalar_equal(m0[j, ri], m1[j, i])
|
|
assert_cvscalar_equal(m0[j, ri], m2[j, i])
|
|
assert_cvscalar_equal(m0[rj, i], m3[j, i])
|
|
assert_cvscalar_equal(m0[rj, i], m4[j, i])
|
|
assert_cvscalar_equal(m0[rj, ri], m5[j, i])
|
|
assert_cvscalar_equal(m0[rj, ri], m6[j, i])
|
|
assert_cvscalar_equal(m0[j, ri], m7[j, i])
|
|
assert_cvscalar_equal(m0[j, ri], m8[j, i])
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m0.flip(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m0.flip!(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_split
|
|
m0 = create_cvmat(2, 3, :cv8u, 3) { |j, i, c|
|
|
CvScalar.new(c * 10, c * 20, c * 30)
|
|
}
|
|
|
|
splitted = m0.split
|
|
assert_equal(m0.channel, splitted.size)
|
|
splitted.each_with_index { |m, idx|
|
|
assert_equal(CvMat, m.class)
|
|
assert_equal(m0.height, m.height)
|
|
assert_equal(m0.width, m.width)
|
|
assert_equal(1, m.channel)
|
|
|
|
c = 0
|
|
m0.height.times { |j|
|
|
m0.width.times { |i|
|
|
val = c * 10 * (idx + 1)
|
|
assert_cvscalar_equal(CvScalar.new(val), m[j, i])
|
|
c += 1
|
|
}
|
|
}
|
|
}
|
|
|
|
# IplImage#split should return Array<IplImage>
|
|
image = create_iplimage(2, 3, :cv8u, 3) { |j, i, c|
|
|
CvScalar.new(c * 10, c * 20, c * 30)
|
|
}
|
|
|
|
splitted = image.split
|
|
assert_equal(3, splitted.size)
|
|
splitted.each_with_index { |img, channel|
|
|
assert_equal(IplImage, img.class)
|
|
assert_equal(image.height, img.height)
|
|
assert_equal(image.width, img.width)
|
|
assert_equal(1, img.channel)
|
|
|
|
img.height.times { |j|
|
|
img.width.times { |i|
|
|
val = image[j, i][channel]
|
|
assert_cvscalar_equal(CvScalar.new(val), img[j, i])
|
|
}
|
|
}
|
|
}
|
|
end
|
|
|
|
def test_merge
|
|
m0 = create_cvmat(2, 3, :cv8u, 4) { |j, i, c|
|
|
CvScalar.new(c * 10, c * 20, c * 30, c * 40)
|
|
}
|
|
m1 = create_cvmat(2, 3, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(c * 10)
|
|
}
|
|
m2 = create_cvmat(2, 3, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(c * 20)
|
|
}
|
|
m3 = create_cvmat(2, 3, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(c * 30)
|
|
}
|
|
m4 = create_cvmat(2, 3, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(c * 40)
|
|
}
|
|
|
|
m = CvMat.merge(m1, m2, m3, m4)
|
|
|
|
assert_equal(m0.height, m.height)
|
|
assert_equal(m0.width, m.width)
|
|
m0.height.times { |j|
|
|
m0.width.times { |i|
|
|
assert_cvscalar_equal(m0[j, i], m[j, i])
|
|
}
|
|
}
|
|
|
|
m5 = create_cvmat(2, 3, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(c * 50)
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
CvMat.merge(DUMMY_OBJ)
|
|
}
|
|
assert_raise(ArgumentError) {
|
|
CvMat.merge
|
|
}
|
|
assert_raise(ArgumentError) {
|
|
CvMat.merge(m1, m2, m3, m4, m5)
|
|
}
|
|
assert_raise(ArgumentError) {
|
|
CvMat.merge(CvMat.new(1, 2, :cv8u, 2))
|
|
}
|
|
assert_raise(ArgumentError) {
|
|
CvMat.merge(CvMat.new(1, 2, :cv8u, 1),
|
|
CvMat.new(2, 2, :cv8u, 1))
|
|
}
|
|
assert_raise(ArgumentError) {
|
|
CvMat.merge(CvMat.new(1, 2, :cv8u, 1),
|
|
CvMat.new(1, 2, :cv32f, 1))
|
|
}
|
|
end
|
|
|
|
def test_rand_shuffle
|
|
m0 = create_cvmat(2, 3)
|
|
m1 = m0.clone
|
|
m1.rand_shuffle!
|
|
m2 = m0.rand_shuffle
|
|
m3 = m0.clone
|
|
m3.rand_shuffle!(123, 234)
|
|
m4 = m0.rand_shuffle(123, 234)
|
|
|
|
assert_shuffled_equal = lambda { |src, shuffled|
|
|
assert_equal(src.width, shuffled.width)
|
|
assert_equal(src.height, shuffled.height)
|
|
mat0, mat1 = [], []
|
|
src.height { |j|
|
|
src.width { |i|
|
|
mat0 << src[j, i].to_s
|
|
mat1 << shuffled[j, i].to_s
|
|
}
|
|
}
|
|
assert_equal(0, (mat0 - mat1).size)
|
|
}
|
|
|
|
[m1, m2, m3, m4].each { |m|
|
|
assert_shuffled_equal.call(m0, m)
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m0.rand_shuffle(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m0.rand_shuffle(123, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_lut
|
|
m0 = create_cvmat(2, 3, :cv8u, 3)
|
|
lut_mat = create_cvmat(1, 256, :cv8u, 3) { |j, i, c|
|
|
CvScalar.new(255 - c, 255 - c, 255 - c)
|
|
}
|
|
|
|
m = m0.lut(lut_mat)
|
|
assert_equal(m0.height, m.height)
|
|
assert_equal(m0.width, m.width)
|
|
m0.height.times { |j|
|
|
m0.width.times { |i|
|
|
r, g, b = m0[j, i].to_ary.map { |c| 255 - c }
|
|
assert_cvscalar_equal(CvScalar.new(r, g, b, 0), m[j, i])
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m0.lut(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_convert_scale
|
|
m0 = create_cvmat(2, 3, :cv32f, 4) { |j, i, c|
|
|
CvScalar.new(-c, -c, -c, -c)
|
|
}
|
|
|
|
m1 = m0.convert_scale(:depth => :cv8u)
|
|
m2 = m0.convert_scale(:scale => 1.5)
|
|
m3 = m0.convert_scale(:shift => 10.0)
|
|
m4 = m0.convert_scale(:depth => CV_16U)
|
|
|
|
[m1, m2, m3, m4].each { |m|
|
|
assert_equal(m0.height, m.height)
|
|
assert_equal(m0.width, m.width)
|
|
}
|
|
m0.height.times { |j|
|
|
m0.width.times { |i|
|
|
assert_cvscalar_equal(CvScalar.new(0, 0, 0, 0), m1[j, i])
|
|
a = m0[j, i].to_ary.map { |x| x * 1.5 }
|
|
assert_in_delta(a, m2[j, i], 0.001)
|
|
a = m0[j, i].to_ary.map { |x| x + 10.0 }
|
|
assert_in_delta(a, m3[j, i], 0.001)
|
|
assert_cvscalar_equal(CvScalar.new(0, 0, 0, 0), m4[j, i])
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m0.convert_scale(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_convert_scale_abs
|
|
m0 = create_cvmat(2, 3, :cv8u, 4) { |j, i, c|
|
|
CvScalar.new(c, c, c, c)
|
|
}
|
|
|
|
m1 = m0.convert_scale_abs(:depth => :cv64f)
|
|
m2 = m0.convert_scale_abs(:scale => 2)
|
|
m3 = m0.convert_scale_abs(:shift => 10.0)
|
|
m4 = m0.convert_scale_abs(:depth => CV_64F)
|
|
|
|
[m1, m2, m3, m4].each { |m|
|
|
assert_equal(m0.height, m.height)
|
|
assert_equal(m0.width, m.width)
|
|
}
|
|
m0.height.times { |j|
|
|
m0.width.times { |i|
|
|
assert_cvscalar_equal(m0[j, i], m1[j, i])
|
|
a = m0[j, i].to_ary.map { |x| (x * 2).abs }
|
|
assert_in_delta(a, m2[j, i], 0.001)
|
|
a = m0[j, i].to_ary.map { |x| (x + 10.0).abs }
|
|
assert_in_delta(a, m3[j, i], 0.001)
|
|
assert_cvscalar_equal(m0[j, i], m4[j, i])
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m0.convert_scale(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_add
|
|
m1 = create_cvmat(6, 4, :cv32f, 4) { |j, i, c|
|
|
CvScalar.new(c * 0.1, c * 0.2, c * 0.3, c * 0.4)
|
|
}
|
|
m2 = create_cvmat(6, 4, :cv32f, 4) { |j, i, c|
|
|
CvScalar.new(c * 1, c * 2, c * 3, c * 4)
|
|
}
|
|
|
|
# CvMat + CvMat
|
|
m3 = m1.add(m2)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
n = 0
|
|
m1.height.times { |j|
|
|
m1.width.times { |i|
|
|
s = CvScalar.new(n * 1.1, n * 2.2, n * 3.3, n * 4.4)
|
|
assert_in_delta(s, m3[j, i], 0.001)
|
|
n += 1
|
|
}
|
|
}
|
|
|
|
# CvMat + CvScalar
|
|
s1 = CvScalar.new(1, 2, 3, 4)
|
|
m3 = m1.add(s1)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
n = 0
|
|
m1.height.times { |j|
|
|
m1.width.times { |i|
|
|
s = CvScalar.new(n * 0.1 + 1, n * 0.2 + 2, n * 0.3 + 3, n * 0.4 + 4)
|
|
assert_in_delta(s, m3[j, i], 0.001)
|
|
n += 1
|
|
}
|
|
}
|
|
|
|
# Alias
|
|
m3 = m1 + m2
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
n = 0
|
|
m1.height.times { |j|
|
|
m1.width.times { |i|
|
|
s = CvScalar.new(n * 1.1, n * 2.2, n * 3.3, n * 4.4)
|
|
assert_in_delta(s, m3[j, i], 0.001)
|
|
n += 1
|
|
}
|
|
}
|
|
|
|
# CvMat + CvMat with Mask
|
|
mask = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
(i < 3 and j < 2) ? 1 : 0
|
|
}
|
|
|
|
m4 = m1.add(m2, mask)
|
|
assert_equal(m1.height, m4.height)
|
|
assert_equal(m1.width, m4.width)
|
|
n = 0
|
|
m1.height.times { |j|
|
|
m1.width.times { |i|
|
|
if i < 3 and j < 2
|
|
s = CvScalar.new(n * 1.1, n * 2.2, n * 3.3, n * 4.4)
|
|
else
|
|
s = m1[j, i]
|
|
end
|
|
assert_in_delta(s, m4[j, i], 0.001)
|
|
n += 1
|
|
}
|
|
}
|
|
|
|
# CvMat + CvScalar with Mask
|
|
m4 = m1.add(s1, mask)
|
|
assert_equal(m1.height, m4.height)
|
|
assert_equal(m1.width, m4.width)
|
|
n = 0
|
|
m1.height.times { |j|
|
|
m1.width.times { |i|
|
|
if i < 3 and j < 2
|
|
s = CvScalar.new(n * 0.1 + 1, n * 0.2 + 2, n * 0.3 + 3, n * 0.4 + 4)
|
|
else
|
|
s = m1[j, i]
|
|
end
|
|
assert_in_delta(s, m4[j, i], 0.001)
|
|
n += 1
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.add(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m1.add(CvScalar.new(1), DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_sub
|
|
m1 = create_cvmat(6, 4, :cv32f, 4) { |j, i, c|
|
|
CvScalar.new(c * 0.1, c * 0.2, c * 0.3, c * 0.4)
|
|
}
|
|
m2 = create_cvmat(6, 4, :cv32f, 4) { |j, i, c|
|
|
CvScalar.new(c * 1, c * 2, c * 3, c * 4)
|
|
}
|
|
|
|
# CvMat - CvMat
|
|
m3 = m1.sub(m2)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
n = 0
|
|
m1.height.times { |j|
|
|
m1.width.times { |i|
|
|
s = CvScalar.new(-n * 0.9, -n * 1.8, -n * 2.7, -n * 3.6)
|
|
assert_in_delta(s, m3[j, i], 0.001)
|
|
n += 1
|
|
}
|
|
}
|
|
|
|
# CvMat - CvScalar
|
|
s1 = CvScalar.new(1, 2, 3, 4)
|
|
m3 = m1.sub(s1)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
n = 0
|
|
m1.height.times { |j|
|
|
m1.width.times { |i|
|
|
s = CvScalar.new(n * 0.1 - 1, n * 0.2 - 2, n * 0.3 - 3, n * 0.4 - 4)
|
|
assert_in_delta(s, m3[j, i], 0.001)
|
|
n += 1
|
|
}
|
|
}
|
|
|
|
# Alias
|
|
m3 = m1 - m2
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
n = 0
|
|
m1.height.times { |j|
|
|
m1.width.times { |i|
|
|
s = CvScalar.new(-n * 0.9, -n * 1.8, -n * 2.7, -n * 3.6)
|
|
assert_in_delta(s, m3[j, i], 0.001)
|
|
n += 1
|
|
}
|
|
}
|
|
|
|
mask = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
(i < 3 and j < 2) ? 1 : 0
|
|
}
|
|
|
|
# CvMat - CvMat with Mask
|
|
m4 = m1.sub(m2, mask)
|
|
assert_equal(m1.height, m4.height)
|
|
assert_equal(m1.width, m4.width)
|
|
n = 0
|
|
m1.height.times { |j|
|
|
m1.width.times { |i|
|
|
if i < 3 and j < 2
|
|
s = CvScalar.new(-n * 0.9, -n * 1.8, -n * 2.7, -n * 3.6)
|
|
else
|
|
s = m1[j, i]
|
|
end
|
|
assert_in_delta(s, m4[j, i], 0.001)
|
|
n += 1
|
|
}
|
|
}
|
|
|
|
# CvMat - CvScalar with Mask
|
|
m4 = m1.sub(s1, mask)
|
|
assert_equal(m1.height, m4.height)
|
|
assert_equal(m1.width, m4.width)
|
|
n = 0
|
|
m1.height.times { |j|
|
|
m1.width.times { |i|
|
|
if i < 3 and j < 2
|
|
s = CvScalar.new(n * 0.1 - 1, n * 0.2 - 2, n * 0.3 - 3, n * 0.4 - 4)
|
|
else
|
|
s = m1[j, i]
|
|
end
|
|
assert_in_delta(s, m4[j, i], 0.001)
|
|
n += 1
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.sub(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m1.sub(CvScalar.new(1), DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_mul
|
|
m1 = create_cvmat(3, 3, :cv32f)
|
|
s1 = CvScalar.new(0.1, 0.2, 0.3, 0.4)
|
|
m2 = create_cvmat(3, 3, :cv32f) { s1 }
|
|
|
|
# CvMat * CvMat
|
|
m3 = m1.mul(m2)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3, 0.001) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n * 0.1, n * 0.2, n * 0.3, n * 0.4)
|
|
}
|
|
|
|
# CvMat * CvMat * scale
|
|
scale = 2.5
|
|
m3 = m1.mul(m2, scale)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3, 0.001) { |j, i, c|
|
|
n = (c + 1) * scale
|
|
CvScalar.new(n * 0.1, n * 0.2, n * 0.3, n * 0.4)
|
|
}
|
|
|
|
# CvMat * CvScalar
|
|
scale = 2.5
|
|
m3 = m1.mul(s1)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3, 0.001) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n * 0.1, n * 0.2, n * 0.3, n * 0.4)
|
|
}
|
|
|
|
# CvMat * CvScalar * scale
|
|
m3 = m1.mul(s1, scale)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3, 0.001) { |j, i, c|
|
|
n = (c + 1) * scale
|
|
CvScalar.new(n * 0.1, n * 0.2, n * 0.3, n * 0.4)
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.mul(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m1.mul(m2, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_mat_mul
|
|
m0 = create_cvmat(3, 3, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(c * 0.1)
|
|
}
|
|
m1 = create_cvmat(3, 3, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(c)
|
|
}
|
|
m2 = create_cvmat(3, 3, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(c + 1)
|
|
}
|
|
|
|
m3 = m0.mat_mul(m1)
|
|
m4 = m0 * m1
|
|
|
|
[m3, m4].each { |m|
|
|
assert_equal(m1.width, m.width)
|
|
assert_equal(m1.height, m.height)
|
|
assert_in_delta(1.5, m[0, 0][0], 0.001)
|
|
assert_in_delta(1.8, m[0, 1][0], 0.001)
|
|
assert_in_delta(2.1, m[0, 2][0], 0.001)
|
|
assert_in_delta(4.2, m[1, 0][0], 0.001)
|
|
assert_in_delta(5.4, m[1, 1][0], 0.001)
|
|
assert_in_delta(6.6, m[1, 2][0], 0.001)
|
|
assert_in_delta(6.9, m[2, 0][0], 0.001)
|
|
assert_in_delta(9, m[2, 1][0], 0.001)
|
|
assert_in_delta(11.1, m[2, 2][0], 0.001)
|
|
}
|
|
|
|
m5 = m0.mat_mul(m1, m2)
|
|
[m5].each { |m|
|
|
assert_equal(m1.width, m.width)
|
|
assert_equal(m1.height, m.height)
|
|
assert_in_delta(2.5, m[0, 0][0], 0.001)
|
|
assert_in_delta(3.8, m[0, 1][0], 0.001)
|
|
assert_in_delta(5.1, m[0, 2][0], 0.001)
|
|
assert_in_delta(8.2, m[1, 0][0], 0.001)
|
|
assert_in_delta(10.4, m[1, 1][0], 0.001)
|
|
assert_in_delta(12.6, m[1, 2][0], 0.001)
|
|
assert_in_delta(13.9, m[2, 0][0], 0.001)
|
|
assert_in_delta(17, m[2, 1][0], 0.001)
|
|
assert_in_delta(20.1, m[2, 2][0], 0.001)
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m0.mat_mul(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m0.mat_mul(m1, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_div
|
|
m1 = create_cvmat(3, 3, :cv32f)
|
|
s1 = CvScalar.new(0.1, 0.2, 0.3, 0.4)
|
|
m2 = create_cvmat(3, 3, :cv32f) { s1 }
|
|
|
|
# CvMat / CvMat
|
|
m3 = m1.div(m2)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3, 0.001) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n / 0.1, n / 0.2, n / 0.3, n / 0.4)
|
|
}
|
|
|
|
# scale * CvMat / CvMat
|
|
scale = 2.5
|
|
m3 = m1.div(m2, scale)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3, 0.001) { |j, i, c|
|
|
n = (c + 1) * scale
|
|
CvScalar.new(n / 0.1, n / 0.2, n / 0.3, n / 0.4)
|
|
}
|
|
|
|
# CvMat / CvScalar
|
|
scale = 2.5
|
|
m3 = m1.div(s1)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3, 0.001) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n / 0.1, n / 0.2, n / 0.3, n / 0.4)
|
|
}
|
|
|
|
# scale * CvMat / CvScalar
|
|
m3 = m1.div(s1, scale)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3, 0.001) { |j, i, c|
|
|
n = (c + 1) * scale
|
|
CvScalar.new(n / 0.1, n / 0.2, n / 0.3, n / 0.4)
|
|
}
|
|
|
|
# Alias
|
|
m3 = m1 / m2
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3, 0.001) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n / 0.1, n / 0.2, n / 0.3, n / 0.4)
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.div(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m1.div(m2, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_add_weighted
|
|
m1 = create_cvmat(3, 2, :cv8u) { |j, i, c| c + 1 }
|
|
m2 = create_cvmat(3, 2, :cv8u) { |j, i, c| (c + 1) * 10 }
|
|
a = 2.0
|
|
b = 0.1
|
|
g = 100
|
|
m3 = CvMat.add_weighted(m1, a, m2, b, g)
|
|
assert_equal(m1.class, m3.class)
|
|
assert_equal(m1.rows, m3.rows)
|
|
assert_equal(m1.cols, m3.cols)
|
|
assert_equal(m1.depth, m3.depth)
|
|
assert_equal(m1.channel, m3.channel)
|
|
|
|
m1.rows.times { |j|
|
|
m1.cols.times { |i|
|
|
expected = m1[j, i][0] * a + m2[j, i][0] * b + g
|
|
assert_equal(expected, m3[j, i][0])
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
CvMat.add_weighted(DUMMY_OBJ, a, m2, b, g)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.add_weighted(m1, DUMMY_OBJ, m2, b, g)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.add_weighted(m1, a, DUMMY_OBJ, b, g)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.add_weighted(m1, a, m2, DUMMY_OBJ, g)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.add_weighted(m1, a, m2, b, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_and
|
|
m1 = create_cvmat(6, 4)
|
|
s1 = CvScalar.new(1, 2, 3, 4)
|
|
m2 = create_cvmat(6, 4) { s1 }
|
|
mask = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
s = (i < 3 and j < 2) ? 1 : 0
|
|
CvScalar.new(s)
|
|
}
|
|
|
|
# CvMat & CvMat
|
|
m3 = m1.and(m2)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n & 1, n & 2, n & 3, n & 4)
|
|
}
|
|
|
|
# CvMat & CvMat with mask
|
|
m3 = m1.and(m2, mask)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
if i < 3 and j < 2
|
|
CvScalar.new(n & 1, n & 2, n & 3, n & 4)
|
|
else
|
|
CvScalar.new(n, n, n, n)
|
|
end
|
|
}
|
|
|
|
# CvMat & CvScalar
|
|
m3 = m1.and(s1)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n & 1, n & 2, n & 3, n & 4)
|
|
}
|
|
|
|
# CvMat & CvScalar with mask
|
|
m3 = m1.and(s1, mask)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
if i < 3 and j < 2
|
|
CvScalar.new(n & 1, n & 2, n & 3, n & 4)
|
|
else
|
|
CvScalar.new(n, n, n, n)
|
|
end
|
|
}
|
|
|
|
# Alias
|
|
m3 = m1 & m2
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n & 1, n & 2, n & 3, n & 4)
|
|
}
|
|
|
|
m3 = m1 & s1
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n & 1, n & 2, n & 3, n & 4)
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.and(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m1.and(m2, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_or
|
|
m1 = create_cvmat(6, 4)
|
|
s1 = CvScalar.new(1, 2, 3, 4)
|
|
m2 = create_cvmat(6, 4) { s1 }
|
|
mask = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
s = (i < 3 and j < 2) ? 1 : 0
|
|
CvScalar.new(s)
|
|
}
|
|
|
|
# CvMat | CvMat
|
|
m3 = m1.or(m2)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n | 1, n | 2, n | 3, n | 4)
|
|
}
|
|
|
|
# CvMat | CvMat with mask
|
|
m3 = m1.or(m2, mask)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
if i < 3 and j < 2
|
|
CvScalar.new(n | 1, n | 2, n | 3, n | 4)
|
|
else
|
|
CvScalar.new(n, n, n, n)
|
|
end
|
|
}
|
|
|
|
# CvMat | CvScalar
|
|
m3 = m1.or(s1)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n | 1, n | 2, n | 3, n | 4)
|
|
}
|
|
|
|
# CvMat | CvScalar with mask
|
|
m3 = m1.or(s1, mask)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
if i < 3 and j < 2
|
|
CvScalar.new(n | 1, n | 2, n | 3, n | 4)
|
|
else
|
|
CvScalar.new(n, n, n, n)
|
|
end
|
|
}
|
|
|
|
# Alias
|
|
m3 = m1 | m2
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n | 1, n | 2, n | 3, n | 4)
|
|
}
|
|
|
|
m3 = m1 | s1
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n | 1, n | 2, n | 3, n | 4)
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.or(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m1.or(m2, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_xor
|
|
m1 = create_cvmat(6, 4)
|
|
s1 = CvScalar.new(1, 2, 3, 4)
|
|
m2 = create_cvmat(6, 4) { s1 }
|
|
mask = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
s = (i < 3 and j < 2) ? 1 : 0
|
|
CvScalar.new(s)
|
|
}
|
|
|
|
# CvMat ^ CvMat
|
|
m3 = m1.xor(m2)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n ^ 1, n ^ 2, n ^ 3, n ^ 4)
|
|
}
|
|
|
|
# CvMat ^ CvMat with mask
|
|
m3 = m1.xor(m2, mask)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
if i < 3 and j < 2
|
|
CvScalar.new(n ^ 1, n ^ 2, n ^ 3, n ^ 4)
|
|
else
|
|
CvScalar.new(n, n, n, n)
|
|
end
|
|
}
|
|
|
|
# CvMat ^ CvScalar
|
|
m3 = m1.xor(s1)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n ^ 1, n ^ 2, n ^ 3, n ^ 4)
|
|
}
|
|
|
|
# CvMat ^ CvScalar with mask
|
|
m3 = m1.xor(s1, mask)
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
if i < 3 and j < 2
|
|
CvScalar.new(n ^ 1, n ^ 2, n ^ 3, n ^ 4)
|
|
else
|
|
CvScalar.new(n, n, n, n)
|
|
end
|
|
}
|
|
|
|
# Alias
|
|
m3 = m1 ^ m2
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n ^ 1, n ^ 2, n ^ 3, n ^ 4)
|
|
}
|
|
|
|
m3 = m1 ^ s1
|
|
assert_equal(m1.height, m3.height)
|
|
assert_equal(m1.width, m3.width)
|
|
assert_each_cvscalar(m3) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(n ^ 1, n ^ 2, n ^ 3, n ^ 4)
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.xor(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m1.xor(m2, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_not
|
|
m1 = create_cvmat(6, 4, :cv8s)
|
|
m2 = m1.not;
|
|
m3 = m1.clone
|
|
m3.not!
|
|
[m2, m3].each { |m|
|
|
assert_equal(m1.height, m.height)
|
|
assert_equal(m1.width, m.width)
|
|
assert_each_cvscalar(m) { |j, i, c|
|
|
n = c + 1
|
|
CvScalar.new(~n, ~n, ~n, ~n)
|
|
}
|
|
}
|
|
end
|
|
|
|
def test_eq
|
|
m1 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
n = (c.even?) ? 10 : c
|
|
CvScalar.new(n, 0, 0, 0)
|
|
}
|
|
m2 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(10, 0, 0, 0)
|
|
}
|
|
s1 = CvScalar.new(10, 0, 0, 0)
|
|
m3 = m1.eq(m2)
|
|
m4 = m1.eq(s1)
|
|
m5 = m1.eq(10)
|
|
|
|
[m3, m4, m5].each { |m|
|
|
assert_equal(m1.height, m.height)
|
|
assert_equal(m1.width, m.width)
|
|
assert_each_cvscalar(m) { |j, i, c|
|
|
n = (c.even?) ? 0xff : 0
|
|
CvScalar.new(n, 0, 0, 0)
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.eq(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_gt
|
|
m1 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(c, 0, 0, 0)
|
|
}
|
|
m2 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(10, 0, 0, 0)
|
|
}
|
|
s1 = CvScalar.new(10, 0, 0, 0)
|
|
m3 = m1.gt(m2)
|
|
m4 = m1.gt(s1)
|
|
m5 = m1.gt(10)
|
|
|
|
[m3, m4, m5].each { |m|
|
|
assert_equal(m1.height, m.height)
|
|
assert_equal(m1.width, m.width)
|
|
assert_each_cvscalar(m) { |j, i, c|
|
|
n = (c > 10) ? 0xff : 0
|
|
CvScalar.new(n, 0, 0, 0)
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.gt(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_ge
|
|
m1 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(c, 0, 0, 0)
|
|
}
|
|
m2 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(10, 0, 0, 0)
|
|
}
|
|
s1 = CvScalar.new(10, 0, 0, 0)
|
|
m3 = m1.ge(m2)
|
|
m4 = m1.ge(s1)
|
|
m5 = m1.ge(10)
|
|
|
|
[m3, m4, m5].each { |m|
|
|
assert_equal(m1.height, m.height)
|
|
assert_equal(m1.width, m.width)
|
|
assert_each_cvscalar(m) { |j, i, c|
|
|
n = (c >= 10) ? 0xff : 0
|
|
CvScalar.new(n, 0, 0, 0)
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.ge(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_lt
|
|
m1 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(c, 0, 0, 0)
|
|
}
|
|
m2 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(10, 0, 0, 0)
|
|
}
|
|
s1 = CvScalar.new(10, 0, 0, 0)
|
|
m3 = m1.lt(m2)
|
|
m4 = m1.lt(s1)
|
|
m5 = m1.lt(10)
|
|
|
|
[m3, m4, m5].each { |m|
|
|
assert_equal(m1.height, m.height)
|
|
assert_equal(m1.width, m.width)
|
|
assert_each_cvscalar(m) { |j, i, c|
|
|
n = (c < 10) ? 0xff : 0
|
|
CvScalar.new(n, 0, 0, 0)
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.lt(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_le
|
|
m1 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(c, 0, 0, 0)
|
|
}
|
|
m2 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(10, 0, 0, 0)
|
|
}
|
|
s1 = CvScalar.new(10, 0, 0, 0)
|
|
m3 = m1.le(m2)
|
|
m4 = m1.le(s1)
|
|
m5 = m1.le(10)
|
|
|
|
[m3, m4, m5].each { |m|
|
|
assert_equal(m1.height, m.height)
|
|
assert_equal(m1.width, m.width)
|
|
assert_each_cvscalar(m) { |j, i, c|
|
|
n = (c <= 10) ? 0xff : 0
|
|
CvScalar.new(n, 0, 0, 0)
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m1.le(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_in_range
|
|
lower, upper = 10, 20
|
|
m0 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(c + 5, 0, 0, 0)
|
|
}
|
|
m1 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(lower, 0, 0, 0)
|
|
}
|
|
m2 = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
CvScalar.new(upper, 0, 0, 0)
|
|
}
|
|
s1 = CvScalar.new(lower, 0, 0, 0)
|
|
s2 = CvScalar.new(upper, 0, 0, 0)
|
|
|
|
m3 = m0.in_range(m1, m2)
|
|
m4 = m0.in_range(s1, s2)
|
|
m5 = m0.in_range(lower, upper)
|
|
|
|
[m3, m4, m5].each { |m|
|
|
assert_equal(m0.height, m.height)
|
|
assert_equal(m0.width, m.width)
|
|
assert_each_cvscalar(m) { |j, i, c|
|
|
val = m0[j, i][0]
|
|
n = ((lower..upper).include? val) ? 0xff : 0
|
|
CvScalar.new(n, 0, 0, 0)
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m0.in_range(DUMMY_OBJ, m2)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m0.in_range(m1, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_abs_diff
|
|
m0 = create_cvmat(6, 4, :cv32f, 4) { |j, i, c|
|
|
CvScalar.new(-10 + 10.5, 20 + 10.5, -30 + 10.5, 40 - 10.5)
|
|
}
|
|
m1 = create_cvmat(6, 4, :cv32f, 4) { |j, i, c|
|
|
CvScalar.new(c + 10.5, c - 10.5, c + 10.5, c - 10.5)
|
|
}
|
|
m2 = create_cvmat(6, 4, :cv32f, 4) { |j, i, c|
|
|
CvScalar.new(c, c, c, c)
|
|
}
|
|
|
|
s1 = CvScalar.new(-10, 20, -30, 40)
|
|
m3 = m1.abs_diff(m2)
|
|
m4 = m0.abs_diff(s1)
|
|
|
|
[m3, m4].each { |m|
|
|
assert_equal(m1.width, m.width)
|
|
assert_equal(m1.height, m.height)
|
|
assert_each_cvscalar(m, 0.001) {
|
|
CvScalar.new(10.5, 10.5, 10.5, 10.5)
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m0.abs_diff(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_normalize
|
|
mat = create_cvmat(2, 2, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(c, 0, 0, 0)
|
|
}
|
|
|
|
m = mat.normalize
|
|
expected = [0.0, 0.267, 0.534, 0.801]
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, m[i][0], 0.001)
|
|
}
|
|
|
|
minf = mat.normalize(1, 0, CV_NORM_INF)
|
|
expected = [0.0, 0.333, 0.666, 1.0]
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, minf[i][0], 0.001)
|
|
}
|
|
|
|
ml1 = mat.normalize(1, 0, CV_NORM_L1)
|
|
expected = [0.0, 0.166, 0.333, 0.5]
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, ml1[i][0], 0.001)
|
|
}
|
|
|
|
ml2 = mat.normalize(1, 0, CV_NORM_L2)
|
|
expected = [0.0, 0.267, 0.534, 0.801]
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, ml2[i][0], 0.001)
|
|
}
|
|
|
|
mminmax = mat.normalize(10, 5, CV_NORM_MINMAX)
|
|
expected = [5.0, 6.666, 8.333, 10.0]
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, mminmax[i][0], 0.001)
|
|
}
|
|
|
|
mask = mat.to_8u.zero
|
|
mask[0, 0] = CvScalar.new(255, 0, 0)
|
|
mask[1, 0] = CvScalar.new(255, 0, 0)
|
|
minf = mat.normalize(1, 0, CV_NORM_INF, mask)
|
|
expected = [0.0, 0.0, 1.0, 0.0]
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, minf[i][0], 0.001)
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
mat.normalize(DUMMY_OBJ, 0, CV_NORM_INF)
|
|
}
|
|
assert_raise(TypeError) {
|
|
mat.normalize(1, DUMMY_OBJ, CV_NORM_INF)
|
|
}
|
|
assert_raise(TypeError) {
|
|
mat.normalize(1, 0, DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
mat.normalize(1, 0, CV_NORM_INF, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_count_non_zero
|
|
m0 = create_cvmat(6, 4, :cv32f, 1) { |j, i, c|
|
|
n = 0
|
|
n = 1 if i == 0
|
|
CvScalar.new(n, 0, 0, 0)
|
|
}
|
|
assert_equal(6, m0.count_non_zero)
|
|
end
|
|
|
|
def test_sum
|
|
m0 = create_cvmat(6, 4, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(c, c, c, c)
|
|
}
|
|
assert_cvscalar_equal(CvScalar.new(276, 0, 0, 0), m0.sum)
|
|
|
|
m0 = create_cvmat(6, 4, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(-c)
|
|
}
|
|
assert_cvscalar_equal(CvScalar.new(-276, 0, 0, 0), m0.sum)
|
|
end
|
|
|
|
def test_avg_sdv
|
|
m0 = create_cvmat(6, 4, :cv32f, 4) { |j, i, c|
|
|
CvScalar.new(c * 0.1, -c * 0.1, c, -c)
|
|
}
|
|
# CvMat#avg
|
|
assert_in_delta(CvScalar.new(1.15, -1.15, 11.5, -11.5), m0.avg, 0.001)
|
|
# CvMat#sdv
|
|
assert_in_delta(CvScalar.new(0.69221, 0.69221, 6.9221, 6.9221), m0.sdv, 0.001)
|
|
# CvMat#avg_sdv
|
|
avg, sdv = m0.avg_sdv
|
|
assert_in_delta(CvScalar.new(1.15, -1.15, 11.5, -11.5), avg, 0.001)
|
|
assert_in_delta(CvScalar.new(0.69221, 0.69221, 6.9221, 6.9221), sdv, 0.001)
|
|
|
|
mask = create_cvmat(6, 4, :cv8u, 1) { |j, i, c|
|
|
n = (i == j) ? 1 : 0
|
|
CvScalar.new(n)
|
|
}
|
|
# CvMat#avg
|
|
assert_in_delta(CvScalar.new(0.75, -0.75, 7.5, -7.5), m0.avg(mask), 0.001)
|
|
# CvMat#sdv
|
|
assert_in_delta(CvScalar.new(0.55901, 0.55901, 5.5901, 5.5901), m0.sdv(mask), 0.001)
|
|
# CvMat#avg_sdv
|
|
avg, sdv = m0.avg_sdv(mask)
|
|
assert_in_delta(CvScalar.new(0.75, -0.75, 7.5, -7.5), avg, 0.001)
|
|
assert_in_delta(CvScalar.new(0.55901, 0.55901, 5.5901, 5.5901), sdv, 0.001)
|
|
|
|
assert_raise(TypeError) {
|
|
m0.avg(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m0.sdv(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m0.avg_sdv(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_min_max_loc
|
|
m0 = create_cvmat(6, 4, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(c * 0.5)
|
|
}
|
|
m0[2, 3] = CvScalar.new(100.5) # Max
|
|
m0[5, 1] = CvScalar.new(-100.5) # Min
|
|
|
|
min_val, max_val, min_loc, max_loc = m0.min_max_loc
|
|
assert_equal(-100.5, min_val)
|
|
assert_equal(5, min_loc.y)
|
|
assert_equal(1, min_loc.x)
|
|
assert_equal(100.5, max_val)
|
|
assert_equal(2, max_loc.y)
|
|
assert_equal(3, max_loc.x)
|
|
|
|
assert_raise(TypeError) {
|
|
m0.min_max_loc(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_dot_product
|
|
m1 = create_cvmat(2, 2, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(c * 0.5)
|
|
}
|
|
m2 = create_cvmat(2, 2, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(c * 1.5)
|
|
}
|
|
assert_in_delta(10.5, m1.dot_product(m2), 0.001)
|
|
|
|
m1 = create_cvmat(2, 2, :cv32f) { |j, i, c|
|
|
CvScalar.new(c * 0.5, c * 0.6, c * 0.7, c * 0.8)
|
|
}
|
|
m2 = create_cvmat(2, 2, :cv32f) { |j, i, c|
|
|
CvScalar.new(c * 1.5, c * 2.0, c * 2.5, c * 3.0)
|
|
}
|
|
assert_in_delta(85.39999, m1.dot_product(m2), 0.001)
|
|
|
|
assert_raise(TypeError) {
|
|
m1.dot_product(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_cross_product
|
|
m1 = create_cvmat(1, 3, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(c * 0.5)
|
|
}
|
|
m2 = create_cvmat(1, 3, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(c + 1)
|
|
}
|
|
m3 = m1.cross_product(m2)
|
|
|
|
assert_in_delta(CvScalar.new(-0.5), m3[0, 0], 0.001)
|
|
assert_in_delta(CvScalar.new(1), m3[0, 1], 0.001)
|
|
assert_in_delta(CvScalar.new(-0.5), m3[0, 2], 0.001)
|
|
|
|
assert_raise(TypeError) {
|
|
m1.cross_product(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_transform
|
|
m0 = create_cvmat(5, 5, :cv32f, 3) { |j, i, c|
|
|
CvScalar.new(c * 0.5, c * 1.0, c * 1.5)
|
|
}
|
|
transmat = CvMat.new(3, 3, :cv32f, 1);
|
|
transmat[0, 0] = CvScalar.new(0.0)
|
|
transmat[1, 0] = CvScalar.new(0.0)
|
|
transmat[2, 0] = CvScalar.new(0.0)
|
|
|
|
transmat[0, 1] = CvScalar.new(0.0)
|
|
transmat[1, 1] = CvScalar.new(0.0)
|
|
transmat[2, 1] = CvScalar.new(1.0)
|
|
|
|
transmat[0, 2] = CvScalar.new(1.0)
|
|
transmat[1, 2] = CvScalar.new(0.0)
|
|
transmat[2, 2] = CvScalar.new(0.0)
|
|
|
|
m1 = m0.transform(transmat)
|
|
assert_each_cvscalar(m1, 0.01) { |j, i, c|
|
|
CvScalar.new(c * 1.5, 0, c, 0)
|
|
}
|
|
|
|
stf = CvMat.new(3, 1, :cv32f, 1)
|
|
stf[0, 0] = CvScalar.new(-10)
|
|
stf[1, 0] = CvScalar.new(0.0)
|
|
stf[2, 0] = CvScalar.new(5)
|
|
|
|
m1 = m0.transform(transmat, stf)
|
|
assert_each_cvscalar(m1, 0.01) { |j, i, c|
|
|
CvScalar.new(c * 1.5 - 10, 0, c + 5, 0)
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m0.transform(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m0.transform(transmat, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_perspective_transform
|
|
mat = CvMat.new(1, 1, :cv32f, 2)
|
|
mat[0] = CvScalar.new(2, 3)
|
|
transmat = CvMat.new(3, 3, :cv32f, 1).clear
|
|
mat.channel.times { |c|
|
|
transmat[c, c] = CvScalar.new(1.0)
|
|
}
|
|
transmat[2, 2] = CvScalar.new(0.5)
|
|
|
|
m = mat.perspective_transform(transmat)
|
|
assert_equal(1, m.height)
|
|
assert_equal(1, m.width)
|
|
assert_equal(:cv32f, m.depth)
|
|
assert_equal(2, m.channel)
|
|
assert_in_delta(CvScalar.new(4, 6), m[0], 0.001);
|
|
|
|
mat = CvMat.new(1, 1, :cv32f, 3)
|
|
mat[0] = CvScalar.new(2, 3, 4)
|
|
transmat = CvMat.new(4, 4, :cv32f, 1).clear
|
|
mat.channel.times { |c|
|
|
transmat[c, c] = CvScalar.new(1.0)
|
|
}
|
|
transmat[3, 3] = CvScalar.new(0.5)
|
|
|
|
m = mat.perspective_transform(transmat)
|
|
assert_equal(1, m.height)
|
|
assert_equal(1, m.width)
|
|
assert_equal(:cv32f, m.depth)
|
|
assert_equal(3, m.channel)
|
|
assert_in_delta(CvScalar.new(4, 6, 8), m[0], 0.001);
|
|
|
|
assert_raise(TypeError) {
|
|
mat.perspective_transform(DUMMY_OBJ)
|
|
}
|
|
assert_raise(CvStsAssert) {
|
|
mat.perspective_transform(CvMat.new(3, 3, :cv32f, 3))
|
|
}
|
|
end
|
|
|
|
def test_mul_transposed
|
|
mat0 = create_cvmat(2, 2, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new((c + 1) * 2)
|
|
}
|
|
delta = create_cvmat(2, 2, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(c + 1)
|
|
}
|
|
|
|
[mat0.mul_transposed,
|
|
mat0.mul_transposed(:delta => nil),
|
|
mat0.mul_transposed(:order => 0),
|
|
mat0.mul_transposed(:scale => 1.0)].each { |m|
|
|
expected = [20, 44,
|
|
44, 100]
|
|
assert_equal(2, m.rows)
|
|
assert_equal(2, m.cols)
|
|
assert_equal(:cv32f, m.depth)
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, m[i][0], 0.1)
|
|
}
|
|
}
|
|
|
|
m = mat0.mul_transposed(:delta => delta)
|
|
expected = [5, 11,
|
|
11, 25]
|
|
assert_equal(2, m.rows)
|
|
assert_equal(2, m.cols)
|
|
assert_equal(:cv32f, m.depth)
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, m[i][0], 0.1)
|
|
}
|
|
|
|
m = mat0.mul_transposed(:delta => delta, :order => 1, :scale => 2.0)
|
|
expected = [20, 28,
|
|
28, 40]
|
|
assert_equal(2, m.rows)
|
|
assert_equal(2, m.cols)
|
|
assert_equal(:cv32f, m.depth)
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, m[i][0], 0.1)
|
|
}
|
|
end
|
|
|
|
def test_trace
|
|
m0 = create_cvmat(5, 5, :cv32f, 4) { |j, i, c|
|
|
CvScalar.new(c * 0.5, c * 1.0, c * 1.5, c * 2.0)
|
|
}
|
|
assert_in_delta(CvScalar.new(30, 60, 90, 120), m0.trace, 0.001)
|
|
end
|
|
|
|
def test_transpose
|
|
m0 = create_cvmat(2, 3, :cv32f, 4) { |j, i, c|
|
|
CvScalar.new(c * 0.5, c * 1.0, c * 1.5, c * 2.0)
|
|
}
|
|
m1 = m0.transpose
|
|
m2 = m0.t
|
|
|
|
[m1, m2].each { |m|
|
|
assert_equal(m0.rows, m.cols)
|
|
assert_equal(m0.cols, m.rows)
|
|
assert_each_cvscalar(m, 0.001) { |j, i, c|
|
|
m0[i, j]
|
|
}
|
|
}
|
|
end
|
|
|
|
def test_det
|
|
elems = [2.5, 4.5, 2.0,
|
|
3.0, 2.5, -0.5,
|
|
1.0, 0.5, 1.5]
|
|
m0 = create_cvmat(3, 3, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(elems[c])
|
|
}
|
|
assert_in_delta(-14.5, m0.det, 0.001)
|
|
end
|
|
|
|
def test_invert
|
|
elems = [1, 2, 3,
|
|
2, 6, 9,
|
|
1, 4, 7]
|
|
m0 = create_cvmat(3, 3, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(elems[c])
|
|
}
|
|
m1 = m0.invert
|
|
m2 = m0.invert(:lu)
|
|
m3 = m0.invert(:svd)
|
|
m4 = m0.invert(:svd_sym)
|
|
m5 = m0.invert(:svd_symmetric)
|
|
|
|
expected = [3, -1, 0, -2.5, 2, -1.5, 1, -1, 1]
|
|
[m1, m2, m3].each { |m|
|
|
assert_equal(m0.width, m.width)
|
|
assert_equal(m0.height, m.height)
|
|
assert_each_cvscalar(m, 0.001) { |j, i, c|
|
|
CvScalar.new(expected[c])
|
|
}
|
|
}
|
|
|
|
expected = [3, -1, 0, -1.0, 0.15, 0.23, 0, 0.23, -0.15]
|
|
[m4, m5].each { |m|
|
|
assert_equal(m0.width, m.width)
|
|
assert_equal(m0.height, m.height)
|
|
assert_each_cvscalar(m, 0.1) { |j, i, c|
|
|
CvScalar.new(expected[c])
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
m0.invert(DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_solve
|
|
elems1 = [3, 4, 5,
|
|
8, 9, 6,
|
|
3, 5, 9]
|
|
elems2 = [3,
|
|
4,
|
|
5]
|
|
a = create_cvmat(3, 3, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(elems1[c])
|
|
}
|
|
b = create_cvmat(3, 1, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(elems2[c])
|
|
}
|
|
|
|
m1 = CvMat.solve(a, b)
|
|
m2 = CvMat.solve(a, b, :lu)
|
|
m3 = CvMat.solve(a, b, :svd)
|
|
m4 = CvMat.solve(a, b, :svd_sym)
|
|
m5 = CvMat.solve(a, b, :svd_symmetric)
|
|
expected = [2, -2, 1]
|
|
[m1, m2, m3].each { |m|
|
|
assert_equal(b.width, m.width)
|
|
assert_equal(a.height, m.height)
|
|
assert_each_cvscalar(m, 0.001) { |j, i, c|
|
|
CvScalar.new(expected[c])
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
CvMat.solve(DUMMY_OBJ, b)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.solve(a, DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.solve(a, b, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_svd
|
|
rows = 2
|
|
cols = 3
|
|
m0 = create_cvmat(rows, cols, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(c + 1)
|
|
}
|
|
|
|
[m0.svd, m0.clone.svd(CV_SVD_MODIFY_A)].each { |w, u, v|
|
|
expected = [0.38632, -0.92237,
|
|
0.92237, 0.38632]
|
|
assert_equal(rows, u.rows)
|
|
assert_equal(rows, u.cols)
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, u[i][0], 0.0001)
|
|
}
|
|
|
|
assert_equal(rows, w.rows)
|
|
assert_equal(cols, w.cols)
|
|
expected = [9.50803, 0, 0,
|
|
0, 0.77287, 0]
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, w[i][0], 0.0001)
|
|
}
|
|
|
|
assert_equal(cols, v.rows)
|
|
assert_equal(rows, v.cols)
|
|
expected = [0.42867, 0.80596,
|
|
0.56631, 0.11238,
|
|
0.70395, -0.58120]
|
|
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, v[i][0], 0.0001)
|
|
}
|
|
}
|
|
|
|
w, ut, v = m0.svd(CV_SVD_U_T)
|
|
expected = [0.38632, 0.92237,
|
|
-0.92237, 0.38632]
|
|
assert_equal(rows, ut.rows)
|
|
assert_equal(rows, ut.cols)
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, ut[i][0], 0.0001)
|
|
}
|
|
|
|
assert_equal(rows, w.rows)
|
|
assert_equal(cols, w.cols)
|
|
expected = [9.50803, 0, 0,
|
|
0, 0.77287, 0]
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, w[i][0], 0.0001)
|
|
}
|
|
|
|
assert_equal(cols, v.rows)
|
|
assert_equal(rows, v.cols)
|
|
expected = [0.42867, 0.80596,
|
|
0.56631, 0.11238,
|
|
0.70395, -0.58120]
|
|
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, v[i][0], 0.0001)
|
|
}
|
|
|
|
w, u, vt = m0.svd(CV_SVD_V_T)
|
|
expected = [0.38632, -0.92237,
|
|
0.92237, 0.38632]
|
|
assert_equal(rows, u.rows)
|
|
assert_equal(rows, u.cols)
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, u[i][0], 0.0001)
|
|
}
|
|
|
|
assert_equal(rows, w.rows)
|
|
assert_equal(cols, w.cols)
|
|
expected = [9.50803, 0, 0,
|
|
0, 0.77287, 0]
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, w[i][0], 0.0001)
|
|
}
|
|
|
|
assert_equal(rows, vt.rows)
|
|
assert_equal(cols, vt.cols)
|
|
expected = [0.42867, 0.56631, 0.70395,
|
|
0.80596, 0.11238, -0.58120]
|
|
expected.each_with_index { |x, i|
|
|
assert_in_delta(x, vt[i][0], 0.0001)
|
|
}
|
|
end
|
|
|
|
def test_eigenvv
|
|
elems = [6, -2, -3, 7]
|
|
m0 = create_cvmat(2, 2, :cv32f, 1) { |j, i, c|
|
|
CvScalar.new(elems[c])
|
|
}
|
|
|
|
v1 = m0.eigenvv
|
|
v2 = m0.eigenvv(10 ** -15)
|
|
v3 = m0.eigenvv(10 ** -15, 1, 1)
|
|
|
|
[v1, v2].each { |vec, val|
|
|
assert_in_delta(-0.615, vec[0, 0][0], 0.01)
|
|
assert_in_delta(0.788, vec[0, 1][0], 0.01)
|
|
assert_in_delta(0.788, vec[1, 0][0], 0.01)
|
|
assert_in_delta(0.615, vec[1, 1][0], 0.01)
|
|
assert_in_delta(8.562, val[0][0], 0.01)
|
|
assert_in_delta(4.438, val[1][0], 0.01)
|
|
}
|
|
|
|
vec3, val3 = v3
|
|
assert_in_delta(-0.615, vec3[0, 0][0], 0.01)
|
|
assert_in_delta(0.788, vec3[0, 1][0], 0.01)
|
|
assert_in_delta(8.562, val3[0][0], 0.01)
|
|
|
|
assert_raise(TypeError) {
|
|
m0.eigenvv(DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m0.eigenvv(nil, DUMMY_OBJ)
|
|
}
|
|
assert_raise(TypeError) {
|
|
m0.eigenvv(nil, nil, DUMMY_OBJ)
|
|
}
|
|
end
|
|
|
|
def test_find_homography
|
|
# Nx2
|
|
src = CvMat.new(4, 2, :cv32f, 1)
|
|
dst = CvMat.new(4, 2, :cv32f, 1)
|
|
|
|
# Nx3 (Homogeneous coordinates)
|
|
src2 = CvMat.new(4, 3, :cv32f, 1)
|
|
dst2 = CvMat.new(4, 3, :cv32f, 1)
|
|
|
|
# Homography
|
|
# <src> => <dst>
|
|
# (0, 0) => (50, 0)
|
|
# (255, 0) => (205, 0)
|
|
# (255, 255) => (255, 220)
|
|
# (0, 255) => (0, 275)
|
|
[[0, 0], [255, 0], [255, 255], [0, 255]].each_with_index { |coord, i|
|
|
src[i, 0] = coord[0]
|
|
src[i, 1] = coord[1]
|
|
|
|
src2[i, 0] = coord[0] * 2
|
|
src2[i, 1] = coord[1] * 2
|
|
src2[i, 2] = 2
|
|
}
|
|
[[50, 0], [205, 0], [255, 220], [0, 275]].each_with_index { |coord, i|
|
|
dst[i, 0] = coord[0]
|
|
dst[i, 1] = coord[1]
|
|
|
|
dst2[i, 0] = coord[0] * 2
|
|
dst2[i, 1] = coord[1] * 2
|
|
dst2[i, 2] = 2
|
|
}
|
|
|
|
mat1 = CvMat.find_homography(src, dst)
|
|
mat2 = CvMat.find_homography(src, dst, :all)
|
|
mat3 = CvMat.find_homography(src, dst, :ransac)
|
|
mat4 = CvMat.find_homography(src, dst, :lmeds)
|
|
mat5, status5 = CvMat.find_homography(src, dst, :ransac, 5, true)
|
|
mat6, status6 = CvMat.find_homography(src, dst, :ransac, 5, true)
|
|
mat7 = CvMat.find_homography(src, dst, :ransac, 5, false)
|
|
mat8 = CvMat.find_homography(src, dst, :ransac, 5, nil)
|
|
mat9 = CvMat.find_homography(src, dst, :all, 5, true)
|
|
mat10, status10 = CvMat.find_homography(src2, dst2, :ransac, 5, true)
|
|
|
|
[mat1, mat2, mat3, mat4, mat5, mat6, mat7, mat8, mat9, mat10].each { |mat|
|
|
assert_equal(3, mat.rows)
|
|
assert_equal(3, mat.cols)
|
|
assert_equal(:cv32f, mat.depth)
|
|
assert_equal(1, mat.channel)
|
|
[0.72430, -0.19608, 50.0,
|
|
0.0, 0.62489, 0.0,
|
|
0.00057, -0.00165, 1.0].each_with_index { |x, i|
|
|
assert_in_delta(x, mat[i][0], 0.0001)
|
|
}
|
|
}
|
|
|
|
[status5, status6, status10].each { |status|
|
|
assert_equal(1, status.rows)
|
|
assert_equal(4, status.cols)
|
|
assert_equal(:cv8u, status.depth)
|
|
assert_equal(1, status.channel)
|
|
4.times { |i|
|
|
assert_in_delta(1.0, status[i][0], 0.0001)
|
|
}
|
|
}
|
|
|
|
assert_raise(TypeError) {
|
|
CvMat.find_homography(DUMMY_OBJ, dst, :ransac, 5, true)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.find_homography(src, DUMMY_OBJ, :ransac, 5, true)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.find_homography(src, dst, DUMMY_OBJ, 5, true)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.find_homography(src, dst, :ransac, DUMMY_OBJ, true)
|
|
}
|
|
CvMat.find_homography(src, dst, :ransac, 5, DUMMY_OBJ)
|
|
end
|
|
|
|
def test_find_fundamental_mat
|
|
points1 = [[488.362, 169.911],
|
|
[449.488, 174.44],
|
|
[408.565, 179.669],
|
|
[364.512, 184.56],
|
|
[491.483, 122.366],
|
|
[451.512, 126.56],
|
|
[409.502, 130.342],
|
|
[365.5, 134.0],
|
|
[494.335, 74.544],
|
|
[453.5, 76.5],
|
|
[411.646, 79.5901],
|
|
[366.498, 81.6577],
|
|
[453.5, 76.5],
|
|
[411.646, 79.5901],
|
|
[366.498, 81.6577]]
|
|
|
|
points2 = [[526.605, 213.332],
|
|
[470.485, 207.632],
|
|
[417.5, 201.0],
|
|
[367.485, 195.632],
|
|
[530.673, 156.417],
|
|
[473.749, 151.39],
|
|
[419.503, 146.656],
|
|
[368.669, 142.565],
|
|
[534.632, 97.5152],
|
|
[475.84, 94.6777],
|
|
[421.16, 90.3223],
|
|
[368.5, 87.5],
|
|
[475.84, 94.6777],
|
|
[421.16, 90.3223],
|
|
[368.5, 87.5]]
|
|
|
|
# 7 point
|
|
num_points = 7
|
|
mat1 = CvMat.new(num_points, 2, :cv64f, 1)
|
|
mat2 = CvMat.new(num_points, 2, :cv64f, 1)
|
|
|
|
points1[0...num_points].each_with_index { |pt, i|
|
|
mat1[i, 0] = CvScalar.new(pt[0])
|
|
mat1[i, 1] = CvScalar.new(pt[1])
|
|
}
|
|
points2[0...num_points].each_with_index { |pt, i|
|
|
mat2[i, 0] = CvScalar.new(pt[0])
|
|
mat2[i, 1] = CvScalar.new(pt[1])
|
|
}
|
|
f_mat1 = CvMat.find_fundamental_mat(mat1, mat2, CV_FM_7POINT)
|
|
f_mat2, status = CvMat.find_fundamental_mat(mat1, mat2, CV_FM_7POINT, :with_status => true)
|
|
|
|
expected = [0.000009, 0.000029, -0.010343,
|
|
-0.000033, 0.000000, 0.014590,
|
|
0.004415, -0.013420, 1.000000,
|
|
0.000000, 0.000001, -0.000223,
|
|
-0.000001, 0.000036, -0.005309,
|
|
-0.000097, -0.006463, 1.000000,
|
|
0.000002, 0.000005, -0.001621,
|
|
-0.000005, 0.000031, -0.002559,
|
|
0.000527, -0.007424, 1.000000]
|
|
[f_mat1, f_mat2].each { |f_mat|
|
|
assert_equal(9, f_mat.rows)
|
|
assert_equal(3, f_mat.cols)
|
|
expected.each_with_index { |val, i|
|
|
assert_in_delta(val, f_mat[i][0], 1.0e-5)
|
|
}
|
|
}
|
|
assert_equal(num_points, status.cols)
|
|
num_points.times { |i|
|
|
assert_in_delta(1, status[i][0], 1.0e-5)
|
|
}
|
|
|
|
# 8 point
|
|
num_points = 8
|
|
mat1 = CvMat.new(num_points, 2, :cv64f, 1)
|
|
mat2 = CvMat.new(num_points, 2, :cv64f, 1)
|
|
|
|
points1[0...num_points].each_with_index { |pt, i|
|
|
mat1[i, 0] = CvScalar.new(pt[0])
|
|
mat1[i, 1] = CvScalar.new(pt[1])
|
|
}
|
|
points2[0...num_points].each_with_index { |pt, i|
|
|
mat2[i, 0] = CvScalar.new(pt[0])
|
|
mat2[i, 1] = CvScalar.new(pt[1])
|
|
}
|
|
|
|
f_mat1 = CvMat.find_fundamental_mat(mat1, mat2, CV_FM_8POINT)
|
|
f_mat2, status = CvMat.find_fundamental_mat(mat1, mat2, CV_FM_8POINT, :with_status => true)
|
|
|
|
expected = [0.000001, 0.000004, -0.001127,
|
|
-0.000005, 0.000038, -0.003778,
|
|
0.000819, -0.008325, 1.000000]
|
|
[f_mat1, f_mat2].each { |f_mat|
|
|
assert_equal(3, f_mat.rows)
|
|
assert_equal(3, f_mat.cols)
|
|
expected.each_with_index { |val, i|
|
|
assert_in_delta(val, f_mat[i][0], 1.0e-5)
|
|
}
|
|
}
|
|
assert_equal(num_points, status.cols)
|
|
num_points.times { |i|
|
|
assert_in_delta(1, status[i][0], 1.0e-5)
|
|
}
|
|
|
|
# RANSAC default
|
|
num_points = points1.size
|
|
mat1 = CvMat.new(num_points, 2, :cv64f, 1)
|
|
mat2 = CvMat.new(num_points, 2, :cv64f, 1)
|
|
|
|
points1[0...num_points].each_with_index { |pt, i|
|
|
mat1[i, 0] = CvScalar.new(pt[0])
|
|
mat1[i, 1] = CvScalar.new(pt[1])
|
|
}
|
|
points2[0...num_points].each_with_index { |pt, i|
|
|
mat2[i, 0] = CvScalar.new(pt[0])
|
|
mat2[i, 1] = CvScalar.new(pt[1])
|
|
}
|
|
|
|
[CvMat.find_fundamental_mat(mat1, mat2, CV_FM_RANSAC, :with_status => false,
|
|
:maximum_distance => 1.0, :desirable_level => 0.99),
|
|
CvMat.find_fundamental_mat(mat1, mat2, CV_FM_RANSAC)].each { |f_mat|
|
|
assert_equal(3, f_mat.rows)
|
|
assert_equal(3, f_mat.cols)
|
|
expected = [0.000010, 0.000039, -0.011141,
|
|
-0.000045, -0.000001, 0.019631,
|
|
0.004873, -0.017604, 1.000000]
|
|
expected.each_with_index { |val, i|
|
|
assert_in_delta(val, f_mat[i][0], 1.0e-5)
|
|
}
|
|
}
|
|
|
|
# RANSAC with options
|
|
f_mat, status = CvMat.find_fundamental_mat(mat1, mat2, CV_FM_RANSAC, :with_status => true,
|
|
:maximum_distance => 2.0, :desirable_level => 0.8)
|
|
assert_equal(3, f_mat.rows)
|
|
assert_equal(3, f_mat.cols)
|
|
assert_equal(1, status.rows)
|
|
assert_equal(num_points, status.cols)
|
|
|
|
expected_f_mat = [0.000009, 0.000030, -0.010692,
|
|
-0.000039, 0.000000, 0.020567,
|
|
0.004779, -0.018064, 1.000000]
|
|
expected_f_mat.each_with_index { |val, i|
|
|
assert_in_delta(val, f_mat[i][0], 1.0e-5)
|
|
}
|
|
expected_status = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
|
|
expected_status.each_with_index { |val, i|
|
|
assert_in_delta(val, status[i][0], 1.0e-5)
|
|
}
|
|
|
|
# LMedS default
|
|
num_points = 12
|
|
mat1 = CvMat.new(num_points, 2, :cv64f, 1)
|
|
mat2 = CvMat.new(num_points, 2, :cv64f, 1)
|
|
|
|
points1[0...num_points].each_with_index { |pt, i|
|
|
mat1[i, 0] = CvScalar.new(pt[0])
|
|
mat1[i, 1] = CvScalar.new(pt[1])
|
|
}
|
|
points2[0...num_points].each_with_index { |pt, i|
|
|
mat2[i, 0] = CvScalar.new(pt[0])
|
|
mat2[i, 1] = CvScalar.new(pt[1])
|
|
}
|
|
|
|
[CvMat.find_fundamental_mat(mat1, mat2, CV_FM_LMEDS, :with_status => false,
|
|
:maximum_distance => 1.0, :desirable_level => 0.99),
|
|
CvMat.find_fundamental_mat(mat1, mat2, CV_FM_LMEDS)].each { |f_mat|
|
|
assert_equal(3, f_mat.rows)
|
|
assert_equal(3, f_mat.cols)
|
|
expected = [-2.79e-05, -0.0009362, 0.0396139,
|
|
0.0010285, -2.48e-05, -0.3946452,
|
|
-0.0322220, 0.3695115, 1.0]
|
|
expected.each_with_index { |val, i|
|
|
assert_in_delta(val, f_mat[i][0], 1.0e-5)
|
|
}
|
|
}
|
|
|
|
# LMedS with options
|
|
f_mat, status = CvMat.find_fundamental_mat(mat1, mat2, CV_FM_LMEDS, :with_status => true,
|
|
:desirable_level => 0.8)
|
|
assert_equal(3, f_mat.rows)
|
|
assert_equal(3, f_mat.cols)
|
|
assert_equal(1, status.rows)
|
|
assert_equal(num_points, status.cols)
|
|
|
|
expected_f_mat = [6.48e-05, 0.001502, -0.086036,
|
|
-0.001652, 3.86e-05, 0.638690,
|
|
0.059998, -0.597778, 1.0]
|
|
expected_f_mat.each_with_index { |val, i|
|
|
assert_in_delta(val, f_mat[i][0], 1.0e-5)
|
|
}
|
|
expected_status = [1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0]
|
|
expected_status.each_with_index { |val, i|
|
|
assert_equal(val, status[i][0].to_i)
|
|
}
|
|
|
|
[CV_FM_7POINT, CV_FM_8POINT, CV_FM_RANSAC, CV_FM_LMEDS].each { |method|
|
|
assert_raise(TypeError) {
|
|
CvMat.find_fundamental_mat(DUMMY_OBJ, mat2, method, :with_status => true)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.find_fundamental_mat(mat1, DUMMY_OBJ, method, :with_status => true)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.find_fundamental_mat(mat1, mat2, method, DUMMY_OBJ)
|
|
}
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.find_fundamental_mat(mat1, mat2, DUMMY_OBJ, :with_status => true)
|
|
}
|
|
end
|
|
|
|
def test_compute_correspond_epilines
|
|
test_func = lambda { |mat1, mat2, f_mat_arr, num_points|
|
|
f_mat = CvMat.new(3, 3, CV_64F, 1)
|
|
f_mat_arr.each_with_index { |a, i|
|
|
f_mat[i] = CvScalar.new(a)
|
|
}
|
|
|
|
line = CvMat.compute_correspond_epilines(mat1, 1, f_mat)
|
|
assert_equal(num_points, line.rows)
|
|
assert_equal(3, line.cols)
|
|
|
|
expected = [[-0.221257, -0.975215, 6.03758],
|
|
[0.359337, -0.933208, -3.61419],
|
|
[0.958304, -0.28575, -15.0573],
|
|
[0.73415, -0.678987, -10.4037],
|
|
[0.0208539, -0.999783, 2.11625],
|
|
[0.284451, -0.958691, -2.31993],
|
|
[0.624647, -0.780907, -8.35208],
|
|
[0.618494, -0.785789, -8.23888],
|
|
[0.766694, -0.642012, -11.0298],
|
|
[0.700293, -0.713855, -9.76109]]
|
|
|
|
expected.size.times { |i|
|
|
assert_in_delta(expected[i][0], line[i, 0][0], 1.0e-3)
|
|
assert_in_delta(expected[i][1], line[i, 1][0], 1.0e-3)
|
|
assert_in_delta(expected[i][2], line[i, 2][0], 1.0e-3)
|
|
}
|
|
|
|
assert_raise(ArgumentError) {
|
|
m = CvMat.new(10, 10, CV_32F, 1)
|
|
CvMat.compute_correspond_epilines(m, 1, f_mat)
|
|
}
|
|
}
|
|
|
|
num_points = 10
|
|
# input points are Nx2 matrix
|
|
points1 =[[17, 175],
|
|
[370, 24],
|
|
[192, 456],
|
|
[614, 202],
|
|
[116, 111],
|
|
[305, 32],
|
|
[249, 268],
|
|
[464, 157],
|
|
[259, 333],
|
|
[460, 224]]
|
|
|
|
points2 = [[295, 28],
|
|
[584, 221],
|
|
[67, 172],
|
|
[400, 443],
|
|
[330, 9],
|
|
[480, 140],
|
|
[181, 140],
|
|
[350, 265],
|
|
[176, 193],
|
|
[333, 313]]
|
|
|
|
mat1 = CvMat.new(num_points, 2, CV_64F, 1)
|
|
mat2 = CvMat.new(num_points, 2, CV_64F, 1)
|
|
points1.flatten.each_with_index { |pt, i|
|
|
mat1[i] = CvScalar.new(pt)
|
|
}
|
|
points2.flatten.each_with_index { |pt, i|
|
|
mat2[i] = CvScalar.new(pt)
|
|
}
|
|
|
|
# pre computed f matrix from points1, points2
|
|
# f_mat = CvMat.find_fundamental_mat(mat1, mat2, CV_FM_LMEDS)
|
|
f_mat_arr = [0.000266883, 0.000140277, -0.0445223,
|
|
-0.00012592, 0.000245543, -0.108868,
|
|
-0.00407942, -0.00291097, 1]
|
|
test_func.call(mat1, mat2, f_mat_arr, num_points)
|
|
|
|
# input points are 2xN matrix
|
|
points1 = [[17, 370, 192, 614, 116, 305, 249, 464, 259, 460],
|
|
[175, 24, 456, 202, 111, 32, 268, 157, 333, 224]]
|
|
|
|
points2 = [[295, 584, 67, 400, 330, 480, 181, 350, 176, 333],
|
|
[28, 221, 172, 443, 9, 140, 140, 265, 193, 313]]
|
|
|
|
mat1 = CvMat.new(2, num_points, CV_64F, 1)
|
|
mat2 = CvMat.new(2, num_points, CV_64F, 1)
|
|
points1.flatten.each_with_index { |pt, i|
|
|
mat1[i] = CvScalar.new(pt)
|
|
}
|
|
points2.flatten.each_with_index { |pt, i|
|
|
mat2[i] = CvScalar.new(pt)
|
|
}
|
|
test_func.call(mat1, mat2, f_mat_arr, num_points)
|
|
|
|
|
|
f_mat = CvMat.new(3, 3, CV_64F, 1)
|
|
f_mat_arr.each_with_index { |a, i|
|
|
f_mat[i] = CvScalar.new(a)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.compute_correspond_epilines(DUMMY_OBJ, 1, f_mat)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.compute_correspond_epilines(mat1, DUMMY_OBJ, f_mat)
|
|
}
|
|
assert_raise(TypeError) {
|
|
CvMat.compute_correspond_epilines(mat1, 1, DUMMY_OBJ)
|
|
}
|
|
end
|
|
end
|
|
|