compute_overlap.pyx
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# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Sergey Karayev
# --------------------------------------------------------
cimport cython
import numpy as np
cimport numpy as np
def compute_overlap(
np.ndarray[double, ndim=2] boxes,
np.ndarray[double, ndim=2] query_boxes
):
"""
Args
a: (N, 4) ndarray of float
b: (K, 4) ndarray of float
Returns
overlaps: (N, K) ndarray of overlap between boxes and query_boxes
"""
cdef unsigned int N = boxes.shape[0]
cdef unsigned int K = query_boxes.shape[0]
cdef np.ndarray[double, ndim=2] overlaps = np.zeros((N, K), dtype=np.float64)
cdef double iw, ih, box_area
cdef double ua
cdef unsigned int k, n
for k in range(K):
box_area = (
(query_boxes[k, 2] - query_boxes[k, 0]) *
(query_boxes[k, 3] - query_boxes[k, 1])
)
for n in range(N):
iw = (
min(boxes[n, 2], query_boxes[k, 2]) -
max(boxes[n, 0], query_boxes[k, 0])
)
if iw > 0:
ih = (
min(boxes[n, 3], query_boxes[k, 3]) -
max(boxes[n, 1], query_boxes[k, 1])
)
if ih > 0:
ua = np.float64(
(boxes[n, 2] - boxes[n, 0]) *
(boxes[n, 3] - boxes[n, 1]) +
box_area - iw * ih
)
overlaps[n, k] = iw * ih / ua
return overlaps