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Returning the keypoints and scales separately
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@@ -10,7 +10,7 @@ from .censure_cy import _censure_dob_loop
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def _get_filtered_image(image, n_scales, mode):
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# TODO : Implement the STAR mode
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scales = np.zeros((image.shape[0], image.shape[1], n_scales),
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dtype=np.double)
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@@ -132,7 +132,7 @@ def _suppress_line(response, sigma, rpc_threshold):
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return response
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def censure_keypoints(image, n_scales=7, mode='DoB', nms_threshold=0.03,
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def censure_keypoints(image, n_scales=7, mode='DoB', nms_threshold=0.15,
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rpc_threshold=10):
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"""
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Extracts Censure keypoints along with the corresponding scale using
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@@ -161,8 +161,11 @@ def censure_keypoints(image, n_scales=7, mode='DoB', nms_threshold=0.03,
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Returns
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-------
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keypoints : (N, 3) array
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Location of extracted keypoints along with the corresponding scale.
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keypoints : (N, 2) array
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Location of extracted keypoints.
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scale : (N, 1) array
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The corresponding scale of the N extracted keypoints.
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References
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----------
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@@ -206,6 +209,10 @@ def censure_keypoints(image, n_scales=7, mode='DoB', nms_threshold=0.03,
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rpc_threshold)
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# Returning keypoints with its scale
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keypoints = (np.transpose(np.nonzero(response[:, :, 1:n_scales - 1]))
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keypoints_with_scale = (np.transpose(np.nonzero(response[:, :, 1:n_scales - 1]))
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+ [0, 0, 2])
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return keypoints
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keypoints = keypoints_with_scale[:, :2]
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scale = keypoints_with_scale[:, -1]
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return keypoints, scale
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