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- # Copyright (c) OpenMMLab. All rights reserved.
- import logging
- import os.path as osp
- from argparse import ArgumentParser
-
- from mmcv import Config
-
- from mmdet.apis import inference_detector, init_detector, show_result_pyplot
- from mmdet.utils import get_root_logger
-
-
- def parse_args():
- parser = ArgumentParser()
- parser.add_argument('config', help='test config file path')
- parser.add_argument('checkpoint_root', help='Checkpoint file root path')
- parser.add_argument('--img', default='demo/demo.jpg', help='Image file')
- parser.add_argument('--aug', action='store_true', help='aug test')
- parser.add_argument('--model-name', help='model name to inference')
- parser.add_argument('--show', action='store_true', help='show results')
- parser.add_argument(
- '--wait-time',
- type=float,
- default=1,
- help='the interval of show (s), 0 is block')
- parser.add_argument(
- '--device', default='cuda:0', help='Device used for inference')
- parser.add_argument(
- '--score-thr', type=float, default=0.3, help='bbox score threshold')
- args = parser.parse_args()
- return args
-
-
- def inference_model(config_name, checkpoint, args, logger=None):
- cfg = Config.fromfile(config_name)
- if args.aug:
- if 'flip' in cfg.data.test.pipeline[1]:
- cfg.data.test.pipeline[1].flip = True
- else:
- if logger is not None:
- logger.error(f'{config_name}: unable to start aug test')
- else:
- print(f'{config_name}: unable to start aug test', flush=True)
-
- model = init_detector(cfg, checkpoint, device=args.device)
- # test a single image
- result = inference_detector(model, args.img)
-
- # show the results
- if args.show:
- show_result_pyplot(
- model,
- args.img,
- result,
- score_thr=args.score_thr,
- wait_time=args.wait_time)
- return result
-
-
- # Sample test whether the inference code is correct
- def main(args):
- config = Config.fromfile(args.config)
-
- # test single model
- if args.model_name:
- if args.model_name in config:
- model_infos = config[args.model_name]
- if not isinstance(model_infos, list):
- model_infos = [model_infos]
- model_info = model_infos[0]
- config_name = model_info['config'].strip()
- print(f'processing: {config_name}', flush=True)
- checkpoint = osp.join(args.checkpoint_root,
- model_info['checkpoint'].strip())
- # build the model from a config file and a checkpoint file
- inference_model(config_name, checkpoint, args)
- return
- else:
- raise RuntimeError('model name input error.')
-
- # test all model
- logger = get_root_logger(
- log_file='benchmark_test_image.log', log_level=logging.ERROR)
-
- for model_key in config:
- model_infos = config[model_key]
- if not isinstance(model_infos, list):
- model_infos = [model_infos]
- for model_info in model_infos:
- print('processing: ', model_info['config'], flush=True)
- config_name = model_info['config'].strip()
- checkpoint = osp.join(args.checkpoint_root,
- model_info['checkpoint'].strip())
- try:
- # build the model from a config file and a checkpoint file
- inference_model(config_name, checkpoint, args, logger)
- except Exception as e:
- logger.error(f'{config_name} " : {repr(e)}')
-
-
- if __name__ == '__main__':
- args = parse_args()
- main(args)
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