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| 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) | |