ruby-opencv/test/test_iplimage.rb

233 lines
6.4 KiB
Ruby
Executable File

#!/usr/bin/env ruby
# -*- mode: ruby; coding: utf-8 -*-
require 'test/unit'
require 'opencv'
require File.expand_path(File.dirname(__FILE__)) + '/helper'
include OpenCV
# Tests for OpenCV::IplImage
class TestIplImage < OpenCVTestCase
def should_classify_images_as(filename, classification)
assert_equal(OpenCV::IplImage::load(filename, OpenCV::CV_LOAD_IMAGE_GRAYSCALE).smoothness[0], classification)
end
def test_initialize
img = IplImage.new(10, 20)
assert_equal(10, img.width)
assert_equal(20, img.height)
assert_equal(:cv8u, img.depth)
assert_equal(3, img.channel)
img = IplImage.new(30, 40, :cv32f, 1)
assert_equal(30, img.width)
assert_equal(40, img.height)
assert_equal(:cv32f, img.depth)
assert_equal(1, img.channel)
end
def test_load
img1 = IplImage.load(FILENAME_CAT)
assert_equal(IplImage, img1.class)
assert_equal(375, img1.width)
assert_equal(500, img1.height)
assert_equal(:cv8u, img1.depth)
assert_equal(3, img1.channel)
img2 = IplImage.load(FILENAME_CAT, CV_LOAD_IMAGE_GRAYSCALE)
assert_equal(IplImage, img2.class)
assert_equal(375, img2.width)
assert_equal(500, img2.height)
assert_equal(:cv8u, img2.depth)
assert_equal(1, img2.channel)
img3 = IplImage.load(FILENAME_CAT, CV_LOAD_IMAGE_ANYDEPTH | CV_LOAD_IMAGE_ANYCOLOR)
assert_equal(IplImage, img3.class)
assert_equal(375, img3.width)
assert_equal(500, img3.height)
assert_equal(:cv8u, img3.depth)
assert_equal(3, img3.channel)
assert_raise(ArgumentError) {
IplImage.load
}
assert_raise(TypeError) {
IplImage.load(123)
}
assert_raise(TypeError) {
IplImage.load(FILENAME_CAT, 'foobar')
}
assert_raise(StandardError) {
IplImage.load('file/does/not/exist')
}
# Uncomment the following lines to show the results
# snap img1, img2, img3
end
def test_decode
data = nil
open(FILENAME_CAT, 'rb') { |f|
data = f.read
}
data_ary = data.unpack("c*")
data_mat = CvMat.new(1, data_ary.size).set_data(data_ary)
expected = IplImage.load(FILENAME_CAT)
img1 = IplImage.decode(data)
img2 = IplImage.decode(data_ary)
img3 = IplImage.decode(data_mat)
img4 = IplImage.decode(data, CV_LOAD_IMAGE_COLOR)
img5 = IplImage.decode(data_ary, CV_LOAD_IMAGE_COLOR)
img6 = IplImage.decode(data_mat, CV_LOAD_IMAGE_COLOR)
[img1, img2, img3, img4, img5, img6].each { |img|
assert_equal(IplImage, img.class)
assert_equal(expected.rows, img.rows)
assert_equal(expected.cols, img.cols)
assert_equal(expected.channel, img.channel)
}
expected_c1 = IplImage.load(FILENAME_CAT, CV_LOAD_IMAGE_GRAYSCALE)
img1c1 = IplImage.decode(data, CV_LOAD_IMAGE_GRAYSCALE)
img2c1 = IplImage.decode(data_ary, CV_LOAD_IMAGE_GRAYSCALE)
img3c1 = IplImage.decode(data_mat, CV_LOAD_IMAGE_GRAYSCALE)
[img1c1, img2c1, img3c1].each { |img|
assert_equal(IplImage, img.class)
assert_equal(expected_c1.rows, img.rows)
assert_equal(expected_c1.cols, img.cols)
assert_equal(expected_c1.channel, img.channel)
}
assert_raise(TypeError) {
IplImage.decode(DUMMY_OBJ)
}
assert_raise(TypeError) {
IplImage.decode(data, DUMMY_OBJ)
}
# Uncomment the following line to show the result images
# snap img1, img2, img3
end
def test_roi
img = IplImage.new(20, 30)
rect = img.roi
assert_equal(0, rect.x)
assert_equal(0, rect.y)
assert_equal(img.width, rect.width)
assert_equal(img.height, rect.height)
img.set_roi(CvRect.new(2, 3, 10, 20))
rect = img.roi
assert_equal(2, rect.x)
assert_equal(3, rect.y)
assert_equal(10, rect.width)
assert_equal(20, rect.height)
img.reset_roi
rect = img.roi
assert_equal(0, rect.x)
assert_equal(0, rect.y)
assert_equal(img.width, rect.width)
assert_equal(img.height, rect.height)
img.set_roi(CvRect.new(1, 2, 5, 6)) {|image|
rect = image.roi
assert_equal(1, rect.x)
assert_equal(2, rect.y)
assert_equal(5, rect.width)
assert_equal(6, rect.height)
}
rect = img.roi
assert_equal(0, rect.x)
assert_equal(0, rect.y)
assert_equal(img.width, rect.width)
assert_equal(img.height, rect.height)
# Alias
img.roi = CvRect.new(4, 5, 11, 12)
rect = img.roi
assert_equal(4, rect.x)
assert_equal(5, rect.y)
assert_equal(11, rect.width)
assert_equal(12, rect.height)
end
def test_coi
img = IplImage.new(20, 30)
assert_equal(0, img.coi)
img.set_coi(1)
assert_equal(1, img.coi)
img.reset_coi
assert_equal(0, img.coi)
img.set_coi(2) {|image|
assert_equal(2, image.coi)
}
assert_equal(0, img.coi)
# Alias
img.coi = 1
assert_equal(1, img.coi)
end
def test_smoothness
asset_path = File.join(File.dirname(__FILE__), 'samples')
for image in Array.new(7) { |e| e = File.join(asset_path, "smooth%d.jpg") % e } do
should_classify_images_as image, :smooth
end
for image in Array.new(2) { |e| e = File.join(asset_path, "messy%d.jpg") % e } do
should_classify_images_as image, :messy
end
for image in Array.new(10) { |e| e = File.join(asset_path, "blank%d.jpg") % e } do
should_classify_images_as image, :blank
end
for image in Array.new(2) { |e| e = File.join(asset_path, "partially_blank%d.jpg") % e } do
should_classify_images_as image, :blank
end
end
def test_pyr_segmentation
img0 = IplImage.load(FILENAME_CAT, CV_LOAD_IMAGE_ANYCOLOR | CV_LOAD_IMAGE_ANYDEPTH)
img0.set_roi(CvRect.new(0, 0, 256, 512))
img1, seq1 = img0.pyr_segmentation(2, 255, 50)
assert_equal('963b26f51b14f175fbbf128e9b9e979f', hash_img(img1))
assert_equal(11, seq1.total)
assert_raise(CvStsAssert) {
img0.pyr_segmentation(-1, 255, 50)
}
assert_raise(CvStsAssert) {
img0.pyr_segmentation(1000, 255, 50)
}
assert_raise(CvStsAssert) {
img0.pyr_segmentation(4, -1, 50)
}
assert_raise(CvStsAssert) {
img0.pyr_segmentation(4, 255, -1)
}
assert_raise(TypeError) {
img0.pyr_segmentation(DUMMY_OBJ, 255, 50)
}
assert_raise(TypeError) {
img0.pyr_segmentation(4, DUMMY_OBJ, 50)
}
assert_raise(TypeError) {
img0.pyr_segmentation(4, 255, DUMMY_OBJ)
}
assert_raise(CvBadDepth) {
IplImage.new(10, 10, :cv32f, 2).pyr_segmentation(4, 255, 50)
}
end
end