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# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import os
import os.path as osp
from itertools import product
from mmengine.config import Config, DictAction
from mmengine.dist import get_dist_info
from mmengine.logging import MMLogger, print_log
from mmengine.model import is_model_wrapper
from mmengine.registry import init_default_scope
from mmengine.runner import Runner
from mmengine.runner.checkpoint import load_checkpoint
def parse_args():
parser = argparse.ArgumentParser(
description='MMDet tracking test (and eval) a model')
parser.add_argument('config', help='test config file path')
parser.add_argument('--checkpoint', help='checkpoint file')
parser.add_argument('--detector', help='detection checkpoint file')
parser.add_argument('--reid', help='reid checkpoint file')
parser.add_argument(
'--work-dir',
help='the directory to save the file containing evaluation metrics')
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 get_search_params(cfg, search_params=None, prefix=None, logger=None):
if search_params is None:
search_params = dict()
for k, v in cfg.items():
if prefix is not None:
entire_k = prefix + '.' + k
else:
entire_k = k
if isinstance(v, list):
print_log(f'search `{entire_k}` in {v}.', logger)
search_params[entire_k] = v
if isinstance(v, dict):
search_params = get_search_params(v, search_params, entire_k,
logger)
return search_params
def main():
args = parse_args()
# do not init the default scope here because it will be init in the runner
# load config
cfg = Config.fromfile(args.config)
init_default_scope(cfg.get('default_scope', 'mmdet'))
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
logger = MMLogger.get_instance(name='ParamsSearcher', logger_name='Logger')
# get all cases
search_params = get_search_params(cfg.model.tracker, logger=logger)
search_params_names = tuple(search_params.keys())
all_search_cases = []
for values in product(*search_params.values()):
search = dict()
for k, v in zip(search_params_names, values):
search[k] = v
all_search_cases.append(search)
print_log(f'Totally {len(all_search_cases)} cases.', logger)
search_metrics = []
metrics_types = [cfg.test_evaluator.metric] if isinstance(
cfg.test_evaluator.metric, str) else cfg.test_evaluator.metric
if 'HOTA' in metrics_types:
search_metrics.extend(['HOTA', 'AssA', 'DetA'])
if 'CLEAR' in metrics_types:
search_metrics.extend(
['MOTA', 'MOTP', 'IDSW', 'TP', 'FN', 'FP', 'Frag', 'MT', 'ML'])
if 'Identity' in metrics_types:
search_metrics.extend(['IDF1', 'IDTP', 'IDFN', 'IDFP', 'IDP', 'IDR'])
print_log(f'Record {search_metrics}.', logger)
runner = Runner.from_cfg(cfg)
if is_model_wrapper(runner.model):
model = runner.model.module
else:
model = runner.model
if args.detector:
assert not (args.checkpoint and args.detector), \
'Error: checkpoint and detector checkpoint cannot both exist'
load_checkpoint(model.detector, args.detector)
if args.reid:
assert (args.checkpoint is not None) or (args.detector is not None), \
'Error: checkpoint and detector checkpoint cannot both not exist'
assert not (args.checkpoint and args.reid), \
'Error: checkpoint and reid checkpoint cannot both exist'
load_checkpoint(model.reid, args.reid)
for case in all_search_cases:
for name, value in case.items():
if hasattr(runner.model, 'module'):
setattr(runner.model.module.tracker, name, value)
else:
setattr(runner.model.tracker, name, value)
runner.test()
rank, _ = get_dist_info()
if rank == 0:
_records = []
for metric in search_metrics:
res = runner.message_hub.get_scalar(
'test/motchallenge-metric/' + metric).current()
if isinstance(res, float):
_records.append(f'{res:.3f}')
else:
_records.append(f'{res}')
print_log(f'-------------- {case}: {_records} --------------',
logger)
if __name__ == '__main__':
main()
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