mirror of https://github.com/open-mmlab/mmyolo.git
151 lines
5.3 KiB
Python
151 lines
5.3 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
|
|
import argparse
|
|
import os
|
|
import os.path as osp
|
|
|
|
from mmdet.engine.hooks.utils import trigger_visualization_hook
|
|
from mmengine.config import Config, ConfigDict, DictAction
|
|
from mmengine.evaluator import DumpResults
|
|
from mmengine.runner import Runner
|
|
|
|
from mmyolo.registry import RUNNERS
|
|
from mmyolo.utils import is_metainfo_lower
|
|
|
|
|
|
# TODO: support fuse_conv_bn
|
|
def parse_args():
|
|
parser = argparse.ArgumentParser(
|
|
description='MMYOLO 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(
|
|
'--out',
|
|
type=str,
|
|
help='output result file (must be a .pkl file) in pickle format')
|
|
parser.add_argument(
|
|
'--json-prefix',
|
|
type=str,
|
|
help='the prefix of the output json file without perform evaluation, '
|
|
'which is useful when you want to format the result to a specific '
|
|
'format and submit it to the test server')
|
|
parser.add_argument(
|
|
'--tta',
|
|
action='store_true',
|
|
help='Whether to use test time augmentation')
|
|
parser.add_argument(
|
|
'--show', action='store_true', help='show prediction results')
|
|
parser.add_argument(
|
|
'--deploy',
|
|
action='store_true',
|
|
help='Switch model to deployment mode')
|
|
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('--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 main():
|
|
args = parse_args()
|
|
|
|
# load config
|
|
cfg = Config.fromfile(args.config)
|
|
# replace the ${key} with the value of cfg.key
|
|
# cfg = replace_cfg_vals(cfg)
|
|
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
|
|
|
|
if args.show or args.show_dir:
|
|
cfg = trigger_visualization_hook(cfg, args)
|
|
|
|
if args.deploy:
|
|
cfg.custom_hooks.append(dict(type='SwitchToDeployHook'))
|
|
|
|
# add `format_only` and `outfile_prefix` into cfg
|
|
if args.json_prefix is not None:
|
|
cfg_json = {
|
|
'test_evaluator.format_only': True,
|
|
'test_evaluator.outfile_prefix': args.json_prefix
|
|
}
|
|
cfg.merge_from_dict(cfg_json)
|
|
|
|
# Determine whether the custom metainfo fields are all lowercase
|
|
is_metainfo_lower(cfg)
|
|
|
|
if args.tta:
|
|
assert 'tta_model' in cfg, 'Cannot find ``tta_model`` in config.' \
|
|
" Can't use tta !"
|
|
assert 'tta_pipeline' in cfg, 'Cannot find ``tta_pipeline`` ' \
|
|
"in config. Can't use tta !"
|
|
|
|
cfg.model = ConfigDict(**cfg.tta_model, module=cfg.model)
|
|
test_data_cfg = cfg.test_dataloader.dataset
|
|
while 'dataset' in test_data_cfg:
|
|
test_data_cfg = test_data_cfg['dataset']
|
|
|
|
# batch_shapes_cfg will force control the size of the output image,
|
|
# it is not compatible with tta.
|
|
if 'batch_shapes_cfg' in test_data_cfg:
|
|
test_data_cfg.batch_shapes_cfg = None
|
|
test_data_cfg.pipeline = cfg.tta_pipeline
|
|
|
|
# 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)
|
|
|
|
# add `DumpResults` dummy metric
|
|
if args.out is not None:
|
|
assert args.out.endswith(('.pkl', '.pickle')), \
|
|
'The dump file must be a pkl file.'
|
|
runner.test_evaluator.metrics.append(
|
|
DumpResults(out_file_path=args.out))
|
|
|
|
# start testing
|
|
runner.test()
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main()
|