blob: 1d0bef3321d78fc73556906649ab61eaaea60d86 [file] [log] [blame]
# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
import numpy as np
cimport numpy as np
cdef inline np.float32_t max(np.float32_t a, np.float32_t b):
return a if a >= b else b
cdef inline np.float32_t min(np.float32_t a, np.float32_t b):
return a if a <= b else b
def cpu_nms(np.ndarray[np.float32_t, ndim=2] dets, np.float thresh):
cdef np.ndarray[np.float32_t, ndim=1] x1 = dets[:, 0]
cdef np.ndarray[np.float32_t, ndim=1] y1 = dets[:, 1]
cdef np.ndarray[np.float32_t, ndim=1] x2 = dets[:, 2]
cdef np.ndarray[np.float32_t, ndim=1] y2 = dets[:, 3]
cdef np.ndarray[np.float32_t, ndim=1] scores = dets[:, 4]
cdef np.ndarray[np.float32_t, ndim=1] areas = (x2 - x1 + 1) * (y2 - y1 + 1)
cdef np.ndarray[np.int_t, ndim=1] order = scores.argsort()[::-1]
cdef int ndets = dets.shape[0]
cdef np.ndarray[np.int_t, ndim=1] suppressed = \
np.zeros((ndets), dtype=np.int)
# nominal indices
cdef int _i, _j
# sorted indices
cdef int i, j
# temp variables for box i's (the box currently under consideration)
cdef np.float32_t ix1, iy1, ix2, iy2, iarea
# variables for computing overlap with box j (lower scoring box)
cdef np.float32_t xx1, yy1, xx2, yy2
cdef np.float32_t w, h
cdef np.float32_t inter, ovr
keep = []
for _i in range(ndets):
i = order[_i]
if suppressed[i] == 1:
continue
keep.append(i)
ix1 = x1[i]
iy1 = y1[i]
ix2 = x2[i]
iy2 = y2[i]
iarea = areas[i]
for _j in range(_i + 1, ndets):
j = order[_j]
if suppressed[j] == 1:
continue
xx1 = max(ix1, x1[j])
yy1 = max(iy1, y1[j])
xx2 = min(ix2, x2[j])
yy2 = min(iy2, y2[j])
w = max(0.0, xx2 - xx1 + 1)
h = max(0.0, yy2 - yy1 + 1)
inter = w * h
ovr = inter / (iarea + areas[j] - inter)
if ovr >= thresh:
suppressed[j] = 1
return keep