Spaces:
Sleeping
Sleeping
File size: 1,443 Bytes
d7e58f0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 |
import numpy as np
import torch
from mmcv.ops import box_iou_rotated
from mmcv.utils import collect_env
def check_installation():
"""Check whether mmcv-full has been installed successfully."""
np_boxes1 = np.asarray(
[[1.0, 1.0, 3.0, 4.0, 0.5], [2.0, 2.0, 3.0, 4.0, 0.6],
[7.0, 7.0, 8.0, 8.0, 0.4]],
dtype=np.float32)
np_boxes2 = np.asarray(
[[0.0, 2.0, 2.0, 5.0, 0.3], [2.0, 1.0, 3.0, 3.0, 0.5],
[5.0, 5.0, 6.0, 7.0, 0.4]],
dtype=np.float32)
boxes1 = torch.from_numpy(np_boxes1)
boxes2 = torch.from_numpy(np_boxes2)
# test mmcv-full with CPU ops
box_iou_rotated(boxes1, boxes2)
print('CPU ops were compiled successfully.')
# test mmcv-full with both CPU and CUDA ops
if torch.cuda.is_available():
boxes1 = boxes1.cuda()
boxes2 = boxes2.cuda()
box_iou_rotated(boxes1, boxes2)
print('CUDA ops were compiled successfully.')
else:
print('No CUDA runtime is found, skipping the checking of CUDA ops.')
if __name__ == '__main__':
print('Start checking the installation of mmcv-full ...')
check_installation()
print('mmcv-full has been installed successfully.\n')
env_info_dict = collect_env()
env_info = '\n'.join([(f'{k}: {v}') for k, v in env_info_dict.items()])
dash_line = '-' * 60 + '\n'
print('Environment information:')
print(dash_line + env_info + '\n' + dash_line)
|