Loading functional_tests/test_two_image.py +4 −8 Original line number Diff line number Diff line Loading @@ -67,12 +67,7 @@ class TestTwoImageMatching(unittest.TestCase): # Perform the ratio check cg.ratio_checks(clean_keys = ['symmetry']) # Create fundamental matrix cg.compute_fundamental_matrices(clean_keys = ['symmetry', 'ratio']) # print(edge.masks['fundamental'].sum()) cg.suppress(clean_keys = ['fundamental']) # print(edge.masks['suppress'].sum()) for source, destination, edge in cg.edges_iter(data=True): Loading @@ -83,10 +78,8 @@ class TestTwoImageMatching(unittest.TestCase): self.assertIn(edge.masks['ratio'].sum(), range(30, 100)) # Range needs to be set self.assertIn(edge.masks['fundamental'].sum(), range(10, 1000)) self.assertIn(edge.masks['fundamental'].sum(), range(30, 50)) # Range needs to be set self.assertIn(edge.masks['suppress'].sum(), range(10, 1000)) # Step: Compute the homographies and apply RANSAC cg.compute_homographies(clean_keys=['symmetry', 'ratio']) Loading @@ -98,6 +91,9 @@ class TestTwoImageMatching(unittest.TestCase): # Step: Compute subpixel offsets for candidate points cg.subpixel_register(clean_keys=['ransac']) # Step: cg.suppress(clean_keys = 'ratio') # Step: And create a C object cnet = cg.to_cnet(clean_keys=['symmetry', 'ratio', 'ransac', 'subpixel']) Loading Loading
functional_tests/test_two_image.py +4 −8 Original line number Diff line number Diff line Loading @@ -67,12 +67,7 @@ class TestTwoImageMatching(unittest.TestCase): # Perform the ratio check cg.ratio_checks(clean_keys = ['symmetry']) # Create fundamental matrix cg.compute_fundamental_matrices(clean_keys = ['symmetry', 'ratio']) # print(edge.masks['fundamental'].sum()) cg.suppress(clean_keys = ['fundamental']) # print(edge.masks['suppress'].sum()) for source, destination, edge in cg.edges_iter(data=True): Loading @@ -83,10 +78,8 @@ class TestTwoImageMatching(unittest.TestCase): self.assertIn(edge.masks['ratio'].sum(), range(30, 100)) # Range needs to be set self.assertIn(edge.masks['fundamental'].sum(), range(10, 1000)) self.assertIn(edge.masks['fundamental'].sum(), range(30, 50)) # Range needs to be set self.assertIn(edge.masks['suppress'].sum(), range(10, 1000)) # Step: Compute the homographies and apply RANSAC cg.compute_homographies(clean_keys=['symmetry', 'ratio']) Loading @@ -98,6 +91,9 @@ class TestTwoImageMatching(unittest.TestCase): # Step: Compute subpixel offsets for candidate points cg.subpixel_register(clean_keys=['ransac']) # Step: cg.suppress(clean_keys = 'ratio') # Step: And create a C object cnet = cg.to_cnet(clean_keys=['symmetry', 'ratio', 'ransac', 'subpixel']) Loading