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cimport cython |
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import numpy as np |
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cimport numpy as np |
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def compute_overlap( |
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np.ndarray[double, ndim=2] boxes, |
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np.ndarray[double, ndim=2] query_boxes |
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): |
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""" |
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Args |
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a: (N, 4) ndarray of float |
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b: (K, 4) ndarray of float |
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Returns |
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overlaps: (N, K) ndarray of overlap between boxes and query_boxes |
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""" |
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cdef unsigned int N = boxes.shape[0] |
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cdef unsigned int K = query_boxes.shape[0] |
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cdef np.ndarray[double, ndim=2] overlaps = np.zeros((N, K), dtype=np.float64) |
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cdef double iw, ih, box_area |
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cdef double ua |
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cdef unsigned int k, n |
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for k in range(K): |
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box_area = ( |
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(query_boxes[k, 2] - query_boxes[k, 0]) * |
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(query_boxes[k, 3] - query_boxes[k, 1]) |
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) |
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for n in range(N): |
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iw = ( |
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min(boxes[n, 2], query_boxes[k, 2]) - |
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max(boxes[n, 0], query_boxes[k, 0]) |
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) |
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if iw > 0: |
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ih = ( |
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min(boxes[n, 3], query_boxes[k, 3]) - |
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max(boxes[n, 1], query_boxes[k, 1]) |
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) |
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if ih > 0: |
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ua = np.float64( |
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(boxes[n, 2] - boxes[n, 0]) * |
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(boxes[n, 3] - boxes[n, 1]) + |
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box_area - iw * ih |
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) |
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overlaps[n, k] = iw * ih / ua |
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return overlaps |
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