def test_match_keypoints_brief_lena_rotation(): """Verify matched keypoints result between lena image and its rotated version with the expected keypoint pairs.""" img = data.lena() img = rgb2gray(img) img.shape tform = tf.SimilarityTransform(scale=1, rotation=0.10, translation=(0, 0)) rotated_img = tf.warp(img, tform) keypoints1 = corner_peaks(corner_harris(img), min_distance=5) descriptors1, keypoints1 = brief(img, keypoints1, descriptor_size=512) keypoints2 = corner_peaks(corner_harris(rotated_img), min_distance=5) descriptors2, keypoints2 = brief(rotated_img, keypoints2, descriptor_size=512) matched_keypoints = match_keypoints_brief(keypoints1, descriptors1, keypoints2, descriptors2, threshold=0.07) expected = np.array([[[263, 272], [234, 298]], [[271, 120], [258, 146]], [[323, 164], [305, 195]], [[414, 70], [405, 111]], [[435, 181], [415, 223]], [[454, 176], [435, 221]]]) assert_array_equal(matched_keypoints, expected)
def test_match_keypoints_brief_lena_translation(): """Test matched keypoints between lena image and its translated version.""" img = data.lena() img = rgb2gray(img) img.shape tform = tf.SimilarityTransform(scale=1, rotation=0, translation=(15, 20)) translated_img = tf.warp(img, tform) keypoints1 = corner_peaks(corner_harris(img), min_distance=5) descriptors1, keypoints1 = brief(img, keypoints1, descriptor_size=512) keypoints2 = corner_peaks(corner_harris(translated_img), min_distance=5) descriptors2, keypoints2 = brief(translated_img, keypoints2, descriptor_size=512) matched_keypoints = match_keypoints_brief(keypoints1, descriptors1, keypoints2, descriptors2, threshold=0.10) assert_array_equal(matched_keypoints[:, 0, :], matched_keypoints[:, 1, :] + [20, 15])
def compute_feature(self, u, img, dist, mask, dx): return corner_harris(gaussian_filter(img, sigma=self.sigma))