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2d69dd1215
Migrate G-API module from main repo to opencv_contrib #3827 Related to https://github.com/opencv/opencv/pull/26469 Required https://github.com/opencv/opencv/pull/26527 CI: https://github.com/opencv/ci-gha-workflow/pull/201 TODO: - [x] Python types generator fix - [x] CI update ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [ ] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake
128 lines
4.2 KiB
Python
128 lines
4.2 KiB
Python
#!/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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