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# Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os
import os.path as osp
from mmengine.config import Config, DictAction
from mmengine.registry import RUNNERS
from mmengine.runner import Runner
def parse_args():
parser = argparse.ArgumentParser(description='Test (and eval) a model')
parser.add_argument('config', help='Test config file path')
parser.add_argument('checkpoint', help='Checkpoint file')
parser.add_argument(
'--work-dir',
help='The directory to save the file containing evaluation metrics')
parser.add_argument(
'--save-preds',
action='store_true',
help='Dump predictions to a pickle file for offline evaluation')
parser.add_argument(
'--show', action='store_true', help='Show prediction results')
parser.add_argument(
'--show-dir',
help='Directory where painted images will be saved. '
'If specified, it will be automatically saved '
'to the work_dir/timestamp/show_dir')
parser.add_argument(
'--wait-time', type=float, default=2, help='The interval of show (s)')
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(
'--launcher',
choices=['none', 'pytorch', 'slurm', 'mpi'],
default='none',
help='Job launcher')
parser.add_argument(
'--tta', action='store_true', help='Test time augmentation')
# When using PyTorch version >= 2.0.0, the `torch.distributed.launch`
# will pass the `--local-rank` parameter to `tools/test.py` instead
# of `--local_rank`.
parser.add_argument('--local_rank', '--local-rank', type=int, default=0)
args = parser.parse_args()
if 'LOCAL_RANK' not in os.environ:
os.environ['LOCAL_RANK'] = str(args.local_rank)
return args
def trigger_visualization_hook(cfg, args):
default_hooks = cfg.default_hooks
if 'visualization' in default_hooks:
visualization_hook = default_hooks['visualization']
# Turn on visualization
visualization_hook['enable'] = True
visualization_hook['draw_gt'] = True
visualization_hook['draw_pred'] = True
if args.show:
visualization_hook['show'] = True
visualization_hook['wait_time'] = args.wait_time
if args.show_dir:
cfg.visualizer['save_dir'] = args.show_dir
cfg.visualizer['vis_backends'] = [dict(type='LocalVisBackend')]
else:
raise RuntimeError(
'VisualizationHook must be included in default_hooks.'
'refer to usage '
'"visualization=dict(type=\'VisualizationHook\')"')
return cfg
def main():
args = parse_args()
# load config
cfg = Config.fromfile(args.config)
cfg.launcher = args.launcher
if args.cfg_options is not None:
cfg.merge_from_dict(args.cfg_options)
# work_dir is determined in this priority: CLI > segment in file > filename
if args.work_dir is not None:
# update configs according to CLI args if args.work_dir is not None
cfg.work_dir = args.work_dir
elif cfg.get('work_dir', None) is None:
# use config filename as default work_dir if cfg.work_dir is None
cfg.work_dir = osp.join('./work_dirs',
osp.splitext(osp.basename(args.config))[0])
cfg.load_from = args.checkpoint
# TODO: It will be supported after refactoring the visualizer
if args.show and args.show_dir:
raise NotImplementedError('--show and --show-dir cannot be set '
'at the same time')
if args.show or args.show_dir:
cfg = trigger_visualization_hook(cfg, args)
if args.tta:
cfg.test_dataloader.dataset.pipeline = cfg.tta_pipeline
cfg.tta_model.module = cfg.model
cfg.model = cfg.tta_model
# save predictions
if args.save_preds:
dump_metric = dict(
type='DumpResults',
out_file_path=osp.join(
cfg.work_dir,
f'{osp.basename(args.checkpoint)}_predictions.pkl'))
if isinstance(cfg.test_evaluator, (list, tuple)):
cfg.test_evaluator = list(cfg.test_evaluator)
cfg.test_evaluator.append(dump_metric)
else:
cfg.test_evaluator = [cfg.test_evaluator, dump_metric]
# build the runner from config
if 'runner_type' not in cfg:
# build the default runner
runner = Runner.from_cfg(cfg)
else:
# build customized runner from the registry
# if 'runner_type' is set in the cfg
runner = RUNNERS.build(cfg)
# start testing
runner.test()
if __name__ == '__main__':
main()
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