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ruby-opencv/test/test_mat_imgproc.rb
ser1zw aeda43902a add Mat#adaptive_threshold!
2017-04-30 04:45:50 +09:00

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#!/usr/bin/env ruby
# -*- mode: ruby; coding: utf-8 -*-
require 'opencv'
require File.expand_path(File.dirname(__FILE__)) + '/helper'
include Cv
class TestCvMat < OpenCVTestCase
def test_resize
m0 = Mat.ones(200, 300, CV_8U)
s = Size.new(150, 100)
m = m0.resize(s)
assert_equal(s.height, m.rows)
assert_equal(s.width, m.cols)
assert_equal(m0.depth, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
[INTER_NEAREST, INTER_LINEAR, INTER_AREA,
INTER_CUBIC, INTER_LANCZOS4].each { |interpolation|
m = m0.resize(s, interpolation)
assert_equal(s.height, m.rows)
assert_equal(s.width, m.cols)
assert_equal(m0.depth, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
m.resize(DUMMY_OBJ)
}
end
def test_cvt_color
m = Mat.new(1, 1, CV_32FC3)
m[0, 0] = Scalar.new(1.0, 2.0, 3.0)
delta = 0.01
m2 = m.cvt_color(COLOR_BGR2GRAY)
assert_in_delta(2.1849999, m2[0, 0][0], delta)
m2 = m.cvt_color(COLOR_BGR2HSV)
[30, 0.66666669, 3].each_with_index { |expected, i|
assert_in_delta(expected, m2[0, 0][i], delta, "Failed at m2[0, 0][#{i}]")
}
assert_raise(TypeError) {
m.cvt_color(DUMMY_OBJ)
}
end
def test_cvt_color_bang
m0 = Mat.new(1, 1, CV_32FC3)
m0[0, 0] = Scalar.new(1.0, 2.0, 3.0)
delta = 0.01
m = m0.clone
m.cvt_color!(COLOR_BGR2GRAY)
assert_in_delta(2.1849999, m[0, 0][0], delta)
m = m0.clone
m.cvt_color!(COLOR_BGR2HSV)
[30, 0.66666669, 3].each_with_index { |expected, i|
assert_in_delta(expected, m[0, 0][i], delta, "Failed at m[0, 0][#{i}]")
}
assert_raise(TypeError) {
m.cvt_color!(DUMMY_OBJ)
}
end
def test_resize_bang
m0 = Mat.ones(200, 300, CV_8U)
m = m0.clone
s = Size.new(150, 100)
m.resize!(s)
assert_equal(s.height, m.rows)
assert_equal(s.width, m.cols)
assert_equal(m0.depth, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
[INTER_NEAREST, INTER_LINEAR, INTER_AREA,
INTER_CUBIC, INTER_LANCZOS4].each { |interpolation|
m = m0.clone
m.resize!(s, interpolation)
assert_equal(s.height, m.rows)
assert_equal(s.width, m.cols)
assert_equal(m0.depth, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
m.resize!(DUMMY_OBJ)
}
end
def test_sobel
m0 = Cv::imread(FILENAME_LENA256x256, 0)
sobel = []
sobel << m0.sobel(CV_8U, 1, 1)
sobel << m0.sobel(CV_8U, 1, 1, 5, 0.5, 32, BORDER_CONSTANT)
sobel.each { |m|
assert_equal(m0.rows, m.rows)
assert_equal(m0.cols, m.cols)
assert_equal(CV_8U, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
m0.sobel(DUMMY_OBJ, 1, 1, 5, 0.5, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.sobel(CV_8U, DUMMY_OBJ, 1, 5, 0.5, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.sobel(CV_8U, 1, DUMMY_OBJ, 5, 0.5, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.sobel(CV_8U, 1, 1, DUMMY_OBJ, 0.5, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.sobel(CV_8U, 1, 1, 5, DUMMY_OBJ, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.sobel(CV_8U, 1, 1, 5, 0.5, DUMMY_OBJ, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.sobel(CV_8U, 1, 1, 5, 0.5, 32, DUMMY_OBJ)
}
# w = Window.new('Sobel')
# w.show(m0.sobel(CV_8U, 1, 1))
# Cv::wait_key
end
def test_sobel_bang
m0 = Cv::imread(FILENAME_LENA256x256, 0)
m1 = m0.clone
m0.sobel!(CV_8U, 1, 1)
m1.sobel!(CV_8U, 1, 1, 5, 0.5, 32, BORDER_CONSTANT)
sobel = [m0, m1]
sobel.each { |m|
assert_equal(m0.rows, m.rows)
assert_equal(m0.cols, m.cols)
assert_equal(CV_8U, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
m0.sobel!(DUMMY_OBJ, 1, 1, 5, 0.5, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.sobel!(CV_8U, DUMMY_OBJ, 1, 5, 0.5, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.sobel!(CV_8U, 1, DUMMY_OBJ, 5, 0.5, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.sobel!(CV_8U, 1, 1, DUMMY_OBJ, 0.5, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.sobel!(CV_8U, 1, 1, 5, DUMMY_OBJ, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.sobel!(CV_8U, 1, 1, 5, 0.5, DUMMY_OBJ, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.sobel!(CV_8U, 1, 1, 5, 0.5, 32, DUMMY_OBJ)
}
# w = Window.new('Sobel')
# m0 = Cv::imread(FILENAME_LENA256x256, 0)
# m0.sobel!(CV_8U, 1, 1)
# w.show(m0)
# Cv::wait_key
end
def test_canny
m0 = Cv::imread(FILENAME_LENA256x256, 0)
canny = []
canny << m0.canny(50, 200)
canny << m0.canny(50, 200, 5, true)
canny.each { |m|
assert_equal(m0.rows, m.rows)
assert_equal(m0.cols, m.cols)
assert_equal(m0.depth, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
m0.canny(DUMMY_OBJ, 200, 5, true)
}
assert_raise(TypeError) {
m0.canny(50, DUMMY_OBJ, 5, true)
}
assert_raise(TypeError) {
m0.canny(50, 200, DUMMY_OBJ, true)
}
assert_nothing_raised {
m0.canny(50, 200, 5, DUMMY_OBJ)
}
# w = Window.new('Canny')
# w.show(m0.canny(50, 200))
# Cv::wait_key
end
def test_canny_bang
m0 = Cv::imread(FILENAME_LENA256x256, 0)
m1 = m0.clone
m0.canny!(50, 200)
m1.canny!(50, 200, 5, true)
canny = [m0, m1]
canny.each { |m|
assert_equal(m0.rows, m.rows)
assert_equal(m0.cols, m.cols)
assert_equal(m0.depth, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
m0.canny!(DUMMY_OBJ, 200, 5, true)
}
assert_raise(TypeError) {
m0.canny!(50, DUMMY_OBJ, 5, true)
}
assert_raise(TypeError) {
m0.canny!(50, 200, DUMMY_OBJ, true)
}
assert_nothing_raised {
m0.canny!(50, 200, 5, DUMMY_OBJ)
}
# w = Window.new('Canny')
# m0 = Cv::imread(FILENAME_LENA256x256, 0)
# m0.canny!(50, 200)
# w.show(m0)
# Cv::wait_key
end
def test_laplacian
m0 = Cv::imread(FILENAME_LENA256x256, 0)
laplacian = []
laplacian << m0.laplacian(CV_8U)
laplacian << m0.laplacian(CV_8U, 5, 0.5, 32, BORDER_CONSTANT)
laplacian.each { |m|
assert_equal(m0.rows, m.rows)
assert_equal(m0.cols, m.cols)
assert_equal(CV_8U, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
m0.laplacian(DUMMY_OBJ, 5, 0.5, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.laplacian(CV_8U, DUMMY_OBJ, 0.5, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.laplacian(CV_8U, 5, DUMMY_OBJ, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.laplacian(CV_8U, 5, 0.5, DUMMY_OBJ, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.laplacian(CV_8U, 5, 0.5, 32, DUMMY_OBJ)
}
# w = Window.new('Laplacian')
# w.show(m0.laplacian(CV_8U))
# Cv::wait_key
end
def test_laplacian_bang
m0 = Cv::imread(FILENAME_LENA256x256, 0)
m1 = m0.clone
m0.laplacian!(CV_8U)
m1.laplacian!(CV_8U, 5, 0.5, 32, BORDER_CONSTANT)
laplacian = [m0, m1]
laplacian.each { |m|
assert_equal(m0.rows, m.rows)
assert_equal(m0.cols, m.cols)
assert_equal(CV_8U, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
m0.laplacian!(DUMMY_OBJ, 5, 0.5, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.laplacian!(CV_8U, DUMMY_OBJ, 0.5, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.laplacian!(CV_8U, 5, DUMMY_OBJ, 32, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.laplacian!(CV_8U, 5, 0.5, DUMMY_OBJ, BORDER_CONSTANT)
}
assert_raise(TypeError) {
m0.laplacian!(CV_8U, 5, 0.5, 32, DUMMY_OBJ)
}
# w = Window.new('Laplacian')
# m0 = Cv::imread(FILENAME_LENA256x256, 0)
# m0.laplacian!(CV_8U)
# w.show(m0)
# Cv::wait_key
end
def test_add_weighted
m0 = Mat.ones(3, 3, CV_32F) * 32
m1 = Mat.ones(3, 3, CV_32F) * 64
results = []
results << Cv::add_weighted(m0, 0.5, m1, 0.5, 0)
results << Cv::add_weighted(m0, 0.5, m1, 0.5, 32, CV_32F)
results.each { |m|
assert_equal(m0.rows, m.rows)
assert_equal(m0.cols, m.cols)
assert_equal(CV_32F, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
Cv::add_weighted(DUMMY_OBJ, 0.5, m1, 0.5, 32, CV_32F)
}
assert_raise(TypeError) {
Cv::add_weighted(m0, DUMMY_OBJ, m1, 0.5, 32, CV_32F)
}
assert_raise(TypeError) {
Cv::add_weighted(m0, 0.5, DUMMY_OBJ, 0.5, 32, CV_32F)
}
assert_raise(TypeError) {
Cv::add_weighted(m0, 0.5, m1, DUMMY_OBJ, 32, CV_32F)
}
assert_raise(TypeError) {
Cv::add_weighted(m0, 0.5, m1, 0.5, DUMMY_OBJ, CV_32F)
}
assert_raise(TypeError) {
Cv::add_weighted(m0, 0.5, m1, 0.5, 32, DUMMY_OBJ)
}
end
def test_blur
m0 = Cv::imread(FILENAME_LENA256x256, -1)
ksize = Cv::Size.new(3, 3)
anchor = Cv::Point.new(1, 1)
blurs = []
blurs << m0.blur(ksize)
blurs << m0.blur(ksize, anchor)
blurs << m0.blur(ksize, anchor, Cv::BORDER_REPLICATE)
blurs.each { |m|
assert_equal(m0.rows, m.rows)
assert_equal(m0.cols, m.cols)
assert_equal(m0.depth, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
m0.blur(DUMMY_OBJ)
}
assert_raise(TypeError) {
m0.blur(ksize, DUMMY_OBJ)
}
assert_raise(TypeError) {
m0.blur(ksize, anchor, DUMMY_OBJ)
}
# w = Window.new('Blur')
# w.show(m0.blur(ksize, anchor, Cv::BORDER_REPLICATE))
# Cv::wait_key
end
def test_blur_bang
m0 = Cv::imread(FILENAME_LENA256x256, -1)
m1 = m0.clone
m2 = m0.clone
m3 = m0.clone
ksize = Cv::Size.new(3, 3)
anchor = Cv::Point.new(1, 1)
m0.blur!(ksize)
m0.blur!(ksize, anchor)
m0.blur!(ksize, anchor, Cv::BORDER_REPLICATE)
blurs = [m1, m2, m3]
blurs.each { |m|
assert_equal(m0.rows, m.rows)
assert_equal(m0.cols, m.cols)
assert_equal(m0.depth, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
m0.blur!(DUMMY_OBJ)
}
assert_raise(TypeError) {
m0.blur!(ksize, DUMMY_OBJ)
}
assert_raise(TypeError) {
m0.blur!(ksize, anchor, DUMMY_OBJ)
}
# w = Window.new('Blur')
# m0 = Cv::imread(FILENAME_LENA256x256, -1)
# m0.blur!(ksize, anchor, Cv::BORDER_REPLICATE)
# w.show(m0)
# Cv::wait_key
end
def test_gaussian_blur
m0 = Cv::imread(FILENAME_LENA256x256, -1)
ksize = Cv::Size.new(3, 3)
gaussian_blurs = []
gaussian_blurs << m0.gaussian_blur(ksize, 3)
gaussian_blurs << m0.gaussian_blur(ksize, 3, 5)
gaussian_blurs << m0.gaussian_blur(ksize, 3, 5, Cv::BORDER_REPLICATE)
gaussian_blurs.each { |m|
assert_equal(m0.rows, m.rows)
assert_equal(m0.cols, m.cols)
assert_equal(m0.depth, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
m0.gaussian_blur(ksize, DUMMY_OBJ)
}
assert_raise(TypeError) {
m0.gaussian_blur(ksize, 3, DUMMY_OBJ)
}
assert_raise(TypeError) {
m0.gaussian_blur(ksize, 3, 5, DUMMY_OBJ)
}
# w = Window.new('Gaussian blur')
# w.show(m0.gaussian_blur(ksize, 3, 5, Cv::BORDER_REPLICATE))
# Cv::wait_key
end
def test_gaussian_blur_bang
m0 = Cv::imread(FILENAME_LENA256x256, -1)
m1 = m0.clone
m2 = m0.clone
m3 = m0.clone
ksize = Cv::Size.new(3, 3)
m1.gaussian_blur!(ksize, 3)
m2.gaussian_blur!(ksize, 3, 5)
m3.gaussian_blur!(ksize, 3, 5, Cv::BORDER_REPLICATE)
gaussian_blurs = [m1, m2, m3]
gaussian_blurs.each { |m|
assert_equal(m0.rows, m.rows)
assert_equal(m0.cols, m.cols)
assert_equal(m0.depth, m.depth)
assert_equal(m0.dims, m.dims)
assert_equal(m0.channels, m.channels)
}
assert_raise(TypeError) {
m0.gaussian_blur!(ksize, DUMMY_OBJ)
}
assert_raise(TypeError) {
m0.gaussian_blur!(ksize, 3, DUMMY_OBJ)
}
assert_raise(TypeError) {
m0.gaussian_blur!(ksize, 3, 5, DUMMY_OBJ)
}
# w = Window.new('Gaussian blur')
# m0 = Cv::imread(FILENAME_LENA256x256, -1)
# ksize = Cv::Size.new(13, 13)
# m0.gaussian_blur!(ksize, 3, 5, Cv::BORDER_REPLICATE)
# w.show(m0)
# Cv::wait_key
end
def test_median_blur
m0 = Cv::Mat.ones(3, 3, Cv::CV_8U)
m0[1, 1] = Cv::Scalar.new(0)
m1 = m0.median_blur(3)
assert_equal(m0.class, m1.class)
assert_equal(m0.rows, m1.rows)
assert_equal(m0.cols, m1.cols)
assert_equal(m0.depth, m1.depth)
assert_equal(m0.dims, m1.dims)
assert_equal(m0.channels, m1.channels)
m1.rows.times { |r|
m1.cols.times { |c|
assert_equal(1, m1[r, c][0].to_i)
}
}
assert_raise(TypeError) {
m0.median_blur(DUMMY_OBJ)
}
# m = Cv::imread(FILENAME_LENA256x256, -1)
# m2 = m.median_blur(9)
# snap(['Original', m], ['Median blur', m2])
end
def test_median_blur_bang
m0 = Cv::Mat.ones(3, 3, Cv::CV_8U)
m0[1, 1] = Cv::Scalar.new(0)
m1 = m0.clone
m1.median_blur!(3)
assert_equal(m0.class, m1.class)
assert_equal(m0.rows, m1.rows)
assert_equal(m0.depth, m1.depth)
assert_equal(m0.dims, m1.dims)
assert_equal(m0.channels, m1.channels)
m1.rows.times { |r|
m1.cols.times { |c|
assert_equal(1, m1[r, c][0].to_i)
}
}
assert_raise(TypeError) {
m0.median_blur(DUMMY_OBJ)
}
# m = Cv::imread(FILENAME_LENA256x256, -1)
# m2 = m.clone
# m2.median_blur!(9)
# snap(['Original', m], ['Median blur', m2])
end
def test_threshold
m0 = Cv::Mat.zeros(2, 2, Cv::CV_8U)
m0[0, 0] = Cv::Scalar.new(10)
m0[0, 1] = Cv::Scalar.new(20)
m0[1, 0] = Cv::Scalar.new(30)
m0[1, 1] = Cv::Scalar.new(40)
m = m0.threshold(25, 255, Cv::THRESH_BINARY)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 0, 0;\n 255, 255]>"
assert_equal(expected, m.to_s)
m = m0.threshold(25, 255, Cv::THRESH_BINARY_INV)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[255, 255;\n 0, 0]>"
assert_equal(expected, m.to_s)
m = m0.threshold(25, 255, Cv::THRESH_TRUNC)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 10, 20;\n 25, 25]>"
assert_equal(expected, m.to_s)
m = m0.threshold(25, 255, Cv::THRESH_TOZERO)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 0, 0;\n 30, 40]>"
assert_equal(expected, m.to_s)
m = m0.threshold(25, 255, Cv::THRESH_TOZERO_INV)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 10, 20;\n 0, 0]>"
assert_equal(expected, m.to_s)
m, optimal_threshold = m0.threshold(25, 255, Cv::THRESH_BINARY | Cv::THRESH_OTSU)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 0, 0;\n 255, 255]>"
assert_equal(expected, m.to_s)
assert_in_delta(20, optimal_threshold, 0.1)
m, optimal_threshold = m0.threshold(25, 255, Cv::THRESH_BINARY | Cv::THRESH_TRIANGLE)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 0, 255;\n 255, 255]>"
assert_equal(expected, m.to_s)
assert_in_delta(12, optimal_threshold, 0.1)
assert_raise(TypeError) {
m0.threshold(DUMMY_OBJ, 255, Cv::THRESH_BINARY)
}
assert_raise(TypeError) {
m0.threshold(25, DUMMY_OBJ, Cv::THRESH_BINARY)
}
assert_raise(TypeError) {
m0.threshold(25, 255, DUMMY_OBJ)
}
# m0 = Cv::imread(FILENAME_LENA256x256, 0)
# m = m0.threshold(127, 255, Cv::THRESH_BINARY)
# w = Window.new('Original | Binary')
# w.show(Cv::hconcat([m0, m]))
# Cv::wait_key
end
def test_threshold_bang
m0 = Cv::Mat.zeros(2, 2, Cv::CV_8U)
m0[0, 0] = Cv::Scalar.new(10)
m0[0, 1] = Cv::Scalar.new(20)
m0[1, 0] = Cv::Scalar.new(30)
m0[1, 1] = Cv::Scalar.new(40)
m = m0.clone
m.threshold!(25, 255, Cv::THRESH_BINARY)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 0, 0;\n 255, 255]>"
assert_equal(expected, m.to_s)
m = m0.clone
m.threshold!(25, 255, Cv::THRESH_BINARY_INV)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[255, 255;\n 0, 0]>"
assert_equal(expected, m.to_s)
m = m0.clone
m.threshold!(25, 255, Cv::THRESH_TRUNC)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 10, 20;\n 25, 25]>"
assert_equal(expected, m.to_s)
m = m0.clone
m.threshold!(25, 255, Cv::THRESH_TOZERO)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 0, 0;\n 30, 40]>"
assert_equal(expected, m.to_s)
m = m0.clone
m.threshold!(25, 255, Cv::THRESH_TOZERO_INV)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 10, 20;\n 0, 0]>"
assert_equal(expected, m.to_s)
m = m0.clone
_, optimal_threshold = m.threshold!(25, 255, Cv::THRESH_BINARY | Cv::THRESH_OTSU)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 0, 0;\n 255, 255]>"
assert_equal(expected, m.to_s)
assert_in_delta(20, optimal_threshold, 0.1)
m = m0.clone
_, optimal_threshold = m.threshold!(25, 255, Cv::THRESH_BINARY | Cv::THRESH_TRIANGLE)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 0, 255;\n 255, 255]>"
assert_equal(expected, m.to_s)
assert_in_delta(12, optimal_threshold, 0.1)
assert_raise(TypeError) {
m0.threshold!(DUMMY_OBJ, 255, Cv::THRESH_BINARY)
}
assert_raise(TypeError) {
m0.threshold!(25, DUMMY_OBJ, Cv::THRESH_BINARY)
}
assert_raise(TypeError) {
m0.threshold!(25, 255, DUMMY_OBJ)
}
# m0 = Cv::imread(FILENAME_LENA256x256, 0)
# m = m0.clone
# m.threshold!(127, 255, Cv::THRESH_BINARY)
# w = Window.new('Original | Binary')
# w.show(Cv::hconcat([m0, m]))
# Cv::wait_key
end
def test_adaptive_threshold
m0 = Cv::Mat.new(2, 2, Cv::CV_8U)
m0[0, 0] = Cv::Scalar.new(10)
m0[0, 1] = Cv::Scalar.new(20)
m0[1, 0] = Cv::Scalar.new(30)
m0[1, 1] = Cv::Scalar.new(40)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 0, 0;\n 255, 255]>"
m = m0.adaptive_threshold(255, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, 3, 0)
assert_equal(expected, m.to_s)
m = m0.adaptive_threshold(255, Cv::ADAPTIVE_THRESH_GAUSSIAN_C, Cv::THRESH_BINARY, 3, 0)
assert_equal(expected, m.to_s)
assert_raise(TypeError) {
m0.adaptive_threshold(DUMMY_OBJ, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, 3, 0)
}
assert_raise(TypeError) {
m0.adaptive_threshold(255, DUMMY_OBJ, Cv::THRESH_BINARY, 3, 0)
}
assert_raise(TypeError) {
m0.adaptive_threshold(255, Cv::ADAPTIVE_THRESH_MEAN_C, DUMMY_OBJ, 3, 0)
}
assert_raise(TypeError) {
m0.adaptive_threshold(DUMMY_OBJ, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, DUMMY_OBJ, 0)
}
assert_raise(TypeError) {
m0.adaptive_threshold(DUMMY_OBJ, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, 3, DUMMY_OBJ)
}
# m0 = Cv::imread(FILENAME_LENA256x256, 0)
# m = m0.adaptive_threshold(255, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, 25, 0)
# w = Window.new('Original | Binary')
# w.show(Cv::hconcat([m0, m]))
# Cv::wait_key
end
def test_adaptive_threshold_bang
m0 = Cv::Mat.new(2, 2, Cv::CV_8U)
m0[0, 0] = Cv::Scalar.new(10)
m0[0, 1] = Cv::Scalar.new(20)
m0[1, 0] = Cv::Scalar.new(30)
m0[1, 1] = Cv::Scalar.new(40)
expected = "<Cv::Mat:2x2,depth=0,channels=1,\n[ 0, 0;\n 255, 255]>"
m = m0.clone
m.adaptive_threshold!(255, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, 3, 0)
assert_equal(expected, m.to_s)
m = m0.clone
m.adaptive_threshold!(255, Cv::ADAPTIVE_THRESH_GAUSSIAN_C, Cv::THRESH_BINARY, 3, 0)
assert_equal(expected, m.to_s)
assert_raise(TypeError) {
m0.adaptive_threshold!(DUMMY_OBJ, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, 3, 0)
}
assert_raise(TypeError) {
m0.adaptive_threshold!(255, DUMMY_OBJ, Cv::THRESH_BINARY, 3, 0)
}
assert_raise(TypeError) {
m0.adaptive_threshold!(255, Cv::ADAPTIVE_THRESH_MEAN_C, DUMMY_OBJ, 3, 0)
}
assert_raise(TypeError) {
m0.adaptive_threshold!(DUMMY_OBJ, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, DUMMY_OBJ, 0)
}
assert_raise(TypeError) {
m0.adaptive_threshold!(DUMMY_OBJ, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, 3, DUMMY_OBJ)
}
# m0 = Cv::imread(FILENAME_LENA256x256, 0)
# m = m0.clone
# m.adaptive_threshold!(255, Cv::ADAPTIVE_THRESH_MEAN_C, Cv::THRESH_BINARY, 25, 0)
# w = Window.new('Original | Binary')
# w.show(Cv::hconcat([m0, m]))
# Cv::wait_key
end
end
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