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- # Copyright (c) OpenMMLab. All rights reserved.
- import argparse
-
- import mmcv
- from mmcv import Config, DictAction
- from mmcv.parallel import MMDataParallel
-
- from mmdet.apis import single_gpu_test
- from mmdet.datasets import (build_dataloader, build_dataset,
- replace_ImageToTensor)
-
-
- def parse_args():
- parser = argparse.ArgumentParser(
- description='MMDet test (and eval) an ONNX model using ONNXRuntime')
- parser.add_argument('config', help='test config file path')
- parser.add_argument('model', help='Input model file')
- parser.add_argument('--out', help='output result file in pickle format')
- parser.add_argument(
- '--format-only',
- action='store_true',
- help='Format the output results without perform evaluation. It is'
- 'useful when you want to format the result to a specific format and '
- 'submit it to the test server')
- parser.add_argument(
- '--backend',
- required=True,
- choices=['onnxruntime', 'tensorrt'],
- help='Backend for input model to run. ')
- parser.add_argument(
- '--eval',
- type=str,
- nargs='+',
- help='evaluation metrics, which depends on the dataset, e.g., "bbox",'
- ' "segm", "proposal" for COCO, and "mAP", "recall" for PASCAL VOC')
- parser.add_argument('--show', action='store_true', help='show results')
- parser.add_argument(
- '--show-dir', help='directory where painted images will be saved')
- parser.add_argument(
- '--show-score-thr',
- type=float,
- default=0.3,
- help='score threshold (default: 0.3)')
- parser.add_argument(
- '--cfg-options',
- nargs='+',
- action=DictAction,
- help='override some settings in the used config, the key-value pair '
- 'in xxx=yyy format will be merged into config file. If the value to '
- 'be overwritten is a list, it should be like key="[a,b]" or key=a,b '
- 'It also allows nested list/tuple values, e.g. key="[(a,b),(c,d)]" '
- 'Note that the quotation marks are necessary and that no white space '
- 'is allowed.')
- parser.add_argument(
- '--eval-options',
- nargs='+',
- action=DictAction,
- help='custom options for evaluation, the key-value pair in xxx=yyy '
- 'format will be kwargs for dataset.evaluate() function')
-
- args = parser.parse_args()
- return args
-
-
- def main():
- args = parse_args()
-
- assert args.out or args.eval or args.format_only or args.show \
- or args.show_dir, \
- ('Please specify at least one operation (save/eval/format/show the '
- 'results / save the results) with the argument "--out", "--eval"'
- ', "--format-only", "--show" or "--show-dir"')
-
- if args.eval and args.format_only:
- raise ValueError('--eval and --format_only cannot be both specified')
-
- if args.out is not None and not args.out.endswith(('.pkl', '.pickle')):
- raise ValueError('The output file must be a pkl file.')
-
- cfg = Config.fromfile(args.config)
- if args.cfg_options is not None:
- cfg.merge_from_dict(args.cfg_options)
-
- # in case the test dataset is concatenated
- samples_per_gpu = 1
- if isinstance(cfg.data.test, dict):
- cfg.data.test.test_mode = True
- samples_per_gpu = cfg.data.test.pop('samples_per_gpu', 1)
- if samples_per_gpu > 1:
- # Replace 'ImageToTensor' to 'DefaultFormatBundle'
- cfg.data.test.pipeline = replace_ImageToTensor(
- cfg.data.test.pipeline)
- elif isinstance(cfg.data.test, list):
- for ds_cfg in cfg.data.test:
- ds_cfg.test_mode = True
- samples_per_gpu = max(
- [ds_cfg.pop('samples_per_gpu', 1) for ds_cfg in cfg.data.test])
- if samples_per_gpu > 1:
- for ds_cfg in cfg.data.test:
- ds_cfg.pipeline = replace_ImageToTensor(ds_cfg.pipeline)
-
- # build the dataloader
- dataset = build_dataset(cfg.data.test)
- data_loader = build_dataloader(
- dataset,
- samples_per_gpu=samples_per_gpu,
- workers_per_gpu=cfg.data.workers_per_gpu,
- dist=False,
- shuffle=False)
-
- if args.backend == 'onnxruntime':
- from mmdet.core.export.model_wrappers import ONNXRuntimeDetector
- model = ONNXRuntimeDetector(
- args.model, class_names=dataset.CLASSES, device_id=0)
- elif args.backend == 'tensorrt':
- from mmdet.core.export.model_wrappers import TensorRTDetector
- model = TensorRTDetector(
- args.model, class_names=dataset.CLASSES, device_id=0)
-
- model = MMDataParallel(model, device_ids=[0])
- outputs = single_gpu_test(model, data_loader, args.show, args.show_dir,
- args.show_score_thr)
-
- if args.out:
- print(f'\nwriting results to {args.out}')
- mmcv.dump(outputs, args.out)
- kwargs = {} if args.eval_options is None else args.eval_options
- if args.format_only:
- dataset.format_results(outputs, **kwargs)
- if args.eval:
- eval_kwargs = cfg.get('evaluation', {}).copy()
- # hard-code way to remove EvalHook args
- for key in [
- 'interval', 'tmpdir', 'start', 'gpu_collect', 'save_best',
- 'rule'
- ]:
- eval_kwargs.pop(key, None)
- eval_kwargs.update(dict(metric=args.eval, **kwargs))
- print(dataset.evaluate(outputs, **eval_kwargs))
-
-
- if __name__ == '__main__':
- main()
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