mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
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127 lines
4.2 KiB
127 lines
4.2 KiB
#!/usr/bin/env python |
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import numpy as np |
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import cv2 as cv |
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import os |
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import sys |
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import unittest |
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from tests_common import NewOpenCVTests |
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try: |
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if sys.version_info[:2] < (3, 0): |
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raise unittest.SkipTest('Python 2.x is not supported') |
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# Plaidml is an optional backend |
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pkgs = [ |
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('ocl' , cv.gapi.core.ocl.kernels()), |
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('cpu' , cv.gapi.core.cpu.kernels()), |
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('fluid' , cv.gapi.core.fluid.kernels()) |
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# ('plaidml', cv.gapi.core.plaidml.kernels()) |
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] |
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class gapi_imgproc_test(NewOpenCVTests): |
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def test_good_features_to_track(self): |
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# TODO: Extend to use any type and size here |
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img_path = self.find_file('cv/face/david2.jpg', [os.environ.get('OPENCV_TEST_DATA_PATH')]) |
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in1 = cv.cvtColor(cv.imread(img_path), cv.COLOR_RGB2GRAY) |
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# NB: goodFeaturesToTrack configuration |
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max_corners = 50 |
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quality_lvl = 0.01 |
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min_distance = 10 |
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block_sz = 3 |
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use_harris_detector = True |
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k = 0.04 |
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mask = None |
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# OpenCV |
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expected = cv.goodFeaturesToTrack(in1, max_corners, quality_lvl, |
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min_distance, mask=mask, |
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blockSize=block_sz, useHarrisDetector=use_harris_detector, k=k) |
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# G-API |
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g_in = cv.GMat() |
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g_out = cv.gapi.goodFeaturesToTrack(g_in, max_corners, quality_lvl, |
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min_distance, mask, block_sz, use_harris_detector, k) |
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comp = cv.GComputation(cv.GIn(g_in), cv.GOut(g_out)) |
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for pkg_name, pkg in pkgs: |
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actual = comp.apply(cv.gin(in1), args=cv.gapi.compile_args(pkg)) |
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# NB: OpenCV & G-API have different output shapes: |
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# OpenCV - (num_points, 1, 2) |
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# G-API - (num_points, 2) |
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# Comparison |
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self.assertEqual(0.0, cv.norm(expected.flatten(), |
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np.array(actual, dtype=np.float32).flatten(), |
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cv.NORM_INF), |
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'Failed on ' + pkg_name + ' backend') |
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def test_rgb2gray(self): |
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# TODO: Extend to use any type and size here |
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img_path = self.find_file('cv/face/david2.jpg', [os.environ.get('OPENCV_TEST_DATA_PATH')]) |
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in1 = cv.imread(img_path) |
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# OpenCV |
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expected = cv.cvtColor(in1, cv.COLOR_RGB2GRAY) |
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# G-API |
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g_in = cv.GMat() |
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g_out = cv.gapi.RGB2Gray(g_in) |
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comp = cv.GComputation(cv.GIn(g_in), cv.GOut(g_out)) |
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for pkg_name, pkg in pkgs: |
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actual = comp.apply(cv.gin(in1), args=cv.gapi.compile_args(pkg)) |
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# Comparison |
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self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF), |
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'Failed on ' + pkg_name + ' backend') |
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def test_bounding_rect(self): |
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sz = 1280 |
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fscale = 256 |
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def sample_value(fscale): |
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return np.random.uniform(0, 255 * fscale) / fscale |
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points = np.array([(sample_value(fscale), sample_value(fscale)) for _ in range(1280)], np.float32) |
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# OpenCV |
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expected = cv.boundingRect(points) |
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# G-API |
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g_in = cv.GMat() |
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g_out = cv.gapi.boundingRect(g_in) |
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comp = cv.GComputation(cv.GIn(g_in), cv.GOut(g_out)) |
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for pkg_name, pkg in pkgs: |
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actual = comp.apply(cv.gin(points), args=cv.gapi.compile_args(pkg)) |
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# Comparison |
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self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF), |
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'Failed on ' + pkg_name + ' backend') |
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except unittest.SkipTest as e: |
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message = str(e) |
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class TestSkip(unittest.TestCase): |
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def setUp(self): |
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self.skipTest('Skip tests: ' + message) |
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def test_skip(): |
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pass |
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pass |
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if __name__ == '__main__': |
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NewOpenCVTests.bootstrap()
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