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val.py
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val.py
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
import os
import paddle
from medicalseg.cvlibs import Config
from medicalseg.core import evaluate
from medicalseg.utils import get_sys_env, logger, config_check, utils
def parse_args():
parser = argparse.ArgumentParser(description='Model evaluation')
# params of evaluate
parser.add_argument(
"--config", dest="cfg", help="The config file.", default=None, type=str)
parser.add_argument(
'--model_path',
dest='model_path',
help='The path of model for evaluation',
type=str,
default="saved_model/vnet_lung_coronavirus_128_128_128_15k/best_model/model.pdparams"
)
parser.add_argument(
'--save_dir',
dest='save_dir',
help='The path to save result',
type=str,
default="saved_model/vnet_lung_coronavirus_128_128_128_15k/best_model")
parser.add_argument(
'--num_workers',
dest='num_workers',
help='Num workers for data loader',
type=int,
default=0)
parser.add_argument(
'--print_detail', # the dest cannot have space in it
help='Whether to print evaluate values',
type=bool,
default=True)
parser.add_argument(
'--use_vdl',
help='Whether to use visualdl to record result images',
type=bool,
default=True)
parser.add_argument(
'--auc_roc',
help='Whether to use auc_roc metric',
type=bool,
default=False)
return parser.parse_args()
def main(args):
env_info = get_sys_env()
place = 'gpu' if env_info['Paddle compiled with cuda'] and env_info[
'GPUs used'] else 'cpu'
paddle.set_device(place)
if not args.cfg:
raise RuntimeError('No configuration file specified.')
cfg = Config(args.cfg)
losses = cfg.loss
val_dataset = cfg.val_dataset
if val_dataset is None:
raise RuntimeError(
'The verification dataset is not specified in the configuration file.'
)
elif len(val_dataset) == 0:
raise ValueError(
'The length of val_dataset is 0. Please check if your dataset is valid'
)
msg = '\n---------------Config Information---------------\n'
msg += str(cfg)
msg += '------------------------------------------------'
logger.info(msg)
model = cfg.model
if args.model_path:
utils.load_entire_model(model, args.model_path)
logger.info('Loaded trained params of model successfully')
if args.use_vdl:
from visualdl import LogWriter
log_writer = LogWriter(args.save_dir)
config_check(cfg, val_dataset=val_dataset)
evaluate(
model,
val_dataset,
losses,
num_workers=args.num_workers,
print_detail=args.print_detail,
auc_roc=args.auc_roc,
writer=log_writer,
save_dir=args.save_dir)
if __name__ == '__main__':
args = parse_args()
main(args)