def run_check_nms():
# test nms:
H, W = 480, 640
num_objects = 10
rois = []
for n in range(num_objects):
w = np.random.randint(64, 256)
h = np.random.randint(64, 256)
x0 = np.random.randint(0, W - w)
y0 = np.random.randint(0, H - h)
x1 = x0 + w
y1 = y0 + h
gt = [x0, y0, x1, y1]
M = np.random.randint(10, 20)
for m in range(M):
dw = int(np.random.uniform(0.5, 2) * w)
dh = int(np.random.uniform(0.5, 2) * h)
dx = int(np.random.uniform(-1, 1) * w * 0.5)
dy = int(np.random.uniform(-1, 1) * h * 0.5)
xx0 = x0 - dw // 2 + dx
yy0 = y0 - dh // 2 + dy
xx1 = xx0 + w + dw
yy1 = yy0 + h + dh
score = np.random.uniform(0.5, 2)
rois.append([xx0, yy0, xx1, yy1, score])
pass
rois = np.array(rois).astype(np.float32)
if 1:
tic = time.time()
keep = py_nms(rois, 0.5)
toc = time.time()
print('py_nms :', np.array(keep))
print('time used: ', toc - tic)
if 1:
# keep = gpu_nms(rois, 0.5)
# print('gpu_nms :', keep)
tic = time.time()
keep = cython_nms(rois, 0.5)
toc = time.time()
print('cython_nms :', np.array(keep))
print('time used: ', toc - tic)
if 1:
rois = torch.from_numpy(rois)
rois = rois.cuda() if torch.cuda.is_available() else rois
tic = time.time()
keep = torch_nms(rois, 0.5)
toc = time.time()
keep = keep.cpu().numpy()
print('torch_nms :', keep)
print('time used: ', toc - tic)
def run_check_nms():
#test nms:
H, W = 480, 640
num_objects = 4
rois = []
for n in range(num_objects):
w = np.random.randint(64, 256)
h = np.random.randint(64, 256)
x0 = np.random.randint(0, W - w)
y0 = np.random.randint(0, H - h)
x1 = x0 + w
y1 = y0 + h
gt = [x0, y0, x1, y1]
M = np.random.randint(10, 20)
for m in range(M):
dw = int(np.random.uniform(0.5, 2) * w)
dh = int(np.random.uniform(0.5, 2) * h)
dx = int(np.random.uniform(-1, 1) * w * 0.5)
dy = int(np.random.uniform(-1, 1) * h * 0.5)
xx0 = x0 - dw // 2 + dx
yy0 = y0 - dh // 2 + dy
xx1 = xx0 + w + dw
yy1 = yy0 + h + dh
score = np.random.uniform(0.5, 2)
rois.append([xx0, yy0, xx1, yy1, score])
pass
rois = np.array(rois).astype(np.float32)
if 1:
keep = gpu_nms(rois, 0.5)
print('gpu_nms :', keep)
keep = cython_nms(rois, 0.5)
print('cython_nms :', keep)
#gpu [52, 39, 48, 43, 47, 21, 9, 6, 32, 8, 16, 36, 28, 29, 53, 41]
#py [52, 39, 48, 43, 47, 21, 9, 6, 32, 8, 16, 36, 28, 29, 53, 41]
#cython [52, 39, 48, 43, 47, 21, 9, 6, 32, 8, 16, 36, 28, 29, 53, 41]
if 1:
rois = torch.from_numpy(rois).cuda()
keep = torch_nms(rois, 0.5)
keep = keep.cpu().numpy()
print('torch_nms :', keep)