MMDet / mmdetection /.dev_scripts /benchmark_test.py
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MMdet Model for Image Segmentation
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# Copyright (c) OpenMMLab. All rights reserved.
import logging
import os
import os.path as osp
from argparse import ArgumentParser
from mmengine.config import Config, DictAction
from mmengine.logging import MMLogger
from mmengine.registry import RUNNERS
from mmengine.runner import Runner
from mmdet.testing import replace_to_ceph
from mmdet.utils import register_all_modules, replace_cfg_vals
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('--work-dir', help='the dir to save logs')
parser.add_argument('--ceph', action='store_true')
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)
args = parser.parse_args()
return args
# TODO: Need to refactor test.py so that it can be reused.
def fast_test_model(config_name, checkpoint, args, logger=None):
cfg = Config.fromfile(config_name)
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 = osp.join(args.work_dir,
osp.splitext(osp.basename(config_name))[0])
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(config_name))[0])
if args.ceph:
replace_to_ceph(cfg)
cfg.load_from = checkpoint
# TODO: temporary plan
if 'visualizer' in cfg:
if 'name' in cfg.visualizer:
del cfg.visualizer.name
# 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)
runner.test()
# Sample test whether the inference code is correct
def main(args):
# register all modules in mmdet into the registries
register_all_modules(init_default_scope=False)
config = Config.fromfile(args.config)
# test all model
logger = MMLogger.get_instance(
name='MMLogger',
log_file='benchmark_test.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:
fast_test_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)