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@ -68,6 +68,85 @@ def custom_boundingRect(array): |
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# G-API - array of tuples (n_points). |
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return cv.boundingRect(np.array(array)) |
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# Test input mat |
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def add(g_in1, g_in2, dtype): |
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def custom_add_meta(img_desc1, img_desc2, dtype): |
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return img_desc1 |
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return cv.gapi_wip_op('custom.add', custom_add_meta, g_in1, g_in2, dtype).getGMat() |
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# Test multiple output mat |
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def split3(g_in): |
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def custom_split3_meta(img_desc): |
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out_desc = img_desc.withType(img_desc.depth, 1) |
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return out_desc, out_desc, out_desc |
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op = cv.gapi_wip_op('custom.split3', custom_split3_meta, g_in) |
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ch1 = op.getGMat() |
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ch2 = op.getGMat() |
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ch3 = op.getGMat() |
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return ch1, ch2, ch3 |
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# Test output scalar |
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def mean(g_in): |
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def custom_mean_meta(img_desc): |
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return cv.empty_scalar_desc() |
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op = cv.gapi_wip_op('custom.mean', custom_mean_meta, g_in) |
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return op.getGScalar() |
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# Test input scalar |
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def addC(g_in, g_sc, dtype): |
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def custom_addC_meta(img_desc, sc_desc, dtype): |
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return img_desc |
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op = cv.gapi_wip_op('custom.addC', custom_addC_meta, g_in, g_sc, dtype) |
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return op.getGMat() |
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# Test output opaque. |
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def size(g_in): |
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def custom_size_meta(img_desc): |
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return cv.empty_gopaque_desc() |
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op = cv.gapi_wip_op('custom.size', custom_size_meta, g_in) |
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return op.getGOpaque(cv.gapi.CV_SIZE) |
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# Test input opaque. |
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def sizeR(g_rect): |
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def custom_sizeR_meta(opaque_desc): |
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return cv.empty_gopaque_desc() |
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op = cv.gapi_wip_op('custom.sizeR', custom_sizeR_meta, g_rect) |
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return op.getGOpaque(cv.gapi.CV_SIZE) |
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# Test input array. |
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def boundingRect(g_array): |
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def custom_boundingRect_meta(array_desc): |
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return cv.empty_gopaque_desc() |
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op = cv.gapi_wip_op('custom.boundingRect', custom_boundingRect_meta, g_array) |
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return op.getGOpaque(cv.gapi.CV_RECT) |
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# Test output GArray. |
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def goodFeaturesToTrack(g_in, max_corners, quality_lvl, |
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min_distance, mask, block_sz, |
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use_harris_detector, k): |
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def custom_goodFeaturesToTrack_meta(img_desc, max_corners, quality_lvl, |
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min_distance, mask, block_sz, use_harris_detector, k): |
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return cv.empty_array_desc() |
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op = cv.gapi_wip_op('custom.goodFeaturesToTrack', custom_goodFeaturesToTrack_meta, g_in, |
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max_corners, quality_lvl, min_distance, mask, block_sz, use_harris_detector, k) |
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return op.getGArray(cv.gapi.CV_POINT2F) |
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class gapi_sample_pipelines(NewOpenCVTests): |
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@ -270,5 +349,178 @@ class gapi_sample_pipelines(NewOpenCVTests): |
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self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF)) |
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def test_custom_op_add(self): |
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sz = (3, 3) |
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in_mat1 = np.full(sz, 45, dtype=np.uint8) |
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in_mat2 = np.full(sz, 50, dtype=np.uint8) |
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# OpenCV |
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expected = cv.add(in_mat1, in_mat2) |
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# G-API |
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g_in1 = cv.GMat() |
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g_in2 = cv.GMat() |
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g_out = add(g_in1, g_in2, cv.CV_8UC1) |
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comp = cv.GComputation(cv.GIn(g_in1, g_in2), cv.GOut(g_out)) |
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pkg = cv.gapi_wip_kernels((custom_add, 'custom.add')) |
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actual = comp.apply(cv.gin(in_mat1, in_mat2), args=cv.compile_args(pkg)) |
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self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF)) |
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def test_custom_op_split3(self): |
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sz = (4, 4) |
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in_ch1 = np.full(sz, 1, dtype=np.uint8) |
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in_ch2 = np.full(sz, 2, dtype=np.uint8) |
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in_ch3 = np.full(sz, 3, dtype=np.uint8) |
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# H x W x C |
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in_mat = np.stack((in_ch1, in_ch2, in_ch3), axis=2) |
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# G-API |
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g_in = cv.GMat() |
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g_ch1, g_ch2, g_ch3 = split3(g_in) |
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comp = cv.GComputation(cv.GIn(g_in), cv.GOut(g_ch1, g_ch2, g_ch3)) |
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pkg = cv.gapi_wip_kernels((custom_split3, 'custom.split3')) |
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ch1, ch2, ch3 = comp.apply(cv.gin(in_mat), args=cv.compile_args(pkg)) |
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self.assertEqual(0.0, cv.norm(in_ch1, ch1, cv.NORM_INF)) |
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self.assertEqual(0.0, cv.norm(in_ch2, ch2, cv.NORM_INF)) |
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self.assertEqual(0.0, cv.norm(in_ch3, ch3, cv.NORM_INF)) |
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def test_custom_op_mean(self): |
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img_path = self.find_file('cv/face/david2.jpg', [os.environ.get('OPENCV_TEST_DATA_PATH')]) |
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in_mat = cv.imread(img_path) |
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# OpenCV |
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expected = cv.mean(in_mat) |
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# G-API |
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g_in = cv.GMat() |
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g_out = mean(g_in) |
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comp = cv.GComputation(g_in, g_out) |
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pkg = cv.gapi_wip_kernels((custom_mean, 'custom.mean')) |
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actual = comp.apply(cv.gin(in_mat), args=cv.compile_args(pkg)) |
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# Comparison |
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self.assertEqual(expected, actual) |
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def test_custom_op_addC(self): |
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sz = (3, 3, 3) |
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in_mat = np.full(sz, 45, dtype=np.uint8) |
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sc = (50, 10, 20) |
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# Numpy reference, make array from sc to keep uint8 dtype. |
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expected = in_mat + np.array(sc, dtype=np.uint8) |
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# G-API |
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g_in = cv.GMat() |
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g_sc = cv.GScalar() |
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g_out = addC(g_in, g_sc, cv.CV_8UC1) |
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comp = cv.GComputation(cv.GIn(g_in, g_sc), cv.GOut(g_out)) |
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pkg = cv.gapi_wip_kernels((custom_addC, 'custom.addC')) |
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actual = comp.apply(cv.gin(in_mat, sc), args=cv.compile_args(pkg)) |
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self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF)) |
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def test_custom_op_size(self): |
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sz = (100, 150, 3) |
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in_mat = np.full(sz, 45, dtype=np.uint8) |
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# Open_cV |
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expected = (100, 150) |
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# G-API |
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g_in = cv.GMat() |
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g_sz = size(g_in) |
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comp = cv.GComputation(cv.GIn(g_in), cv.GOut(g_sz)) |
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pkg = cv.gapi_wip_kernels((custom_size, 'custom.size')) |
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actual = comp.apply(cv.gin(in_mat), args=cv.compile_args(pkg)) |
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self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF)) |
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def test_custom_op_sizeR(self): |
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# x, y, h, w |
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roi = (10, 15, 100, 150) |
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expected = (100, 150) |
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# G-API |
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g_r = cv.GOpaqueT(cv.gapi.CV_RECT) |
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g_sz = sizeR(g_r) |
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comp = cv.GComputation(cv.GIn(g_r), cv.GOut(g_sz)) |
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pkg = cv.gapi_wip_kernels((custom_sizeR, 'custom.sizeR')) |
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actual = comp.apply(cv.gin(roi), args=cv.compile_args(pkg)) |
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# cv.norm works with tuples ? |
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self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF)) |
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def test_custom_op_boundingRect(self): |
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points = [(0,0), (0,1), (1,0), (1,1)] |
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# OpenCV |
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expected = cv.boundingRect(np.array(points)) |
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# G-API |
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g_pts = cv.GArrayT(cv.gapi.CV_POINT) |
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g_br = boundingRect(g_pts) |
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comp = cv.GComputation(cv.GIn(g_pts), cv.GOut(g_br)) |
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pkg = cv.gapi_wip_kernels((custom_boundingRect, 'custom.boundingRect')) |
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actual = comp.apply(cv.gin(points), args=cv.compile_args(pkg)) |
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# cv.norm works with tuples ? |
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self.assertEqual(0.0, cv.norm(expected, actual, cv.NORM_INF)) |
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def test_custom_op_goodFeaturesToTrack(self): |
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# G-API |
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img_path = self.find_file('cv/face/david2.jpg', [os.environ.get('OPENCV_TEST_DATA_PATH')]) |
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in_mat = 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(in_mat, 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 = 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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pkg = cv.gapi_wip_kernels((custom_goodFeaturesToTrack, 'custom.goodFeaturesToTrack')) |
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actual = comp.apply(cv.gin(in_mat), args=cv.compile_args(pkg)) |
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# NB: OpenCV & G-API have different output types. |
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# OpenCV - numpy array with shape (num_points, 1, 2) |
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# G-API - list of tuples with size - num_points |
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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(), cv.NORM_INF)) |
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if __name__ == '__main__': |
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NewOpenCVTests.bootstrap() |
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