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- # Copyright (c) 2021 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
- import paddleseg
- from paddleseg.cvlibs import manager, Config
- from paddleseg.utils import get_sys_env, logger
-
- from core import evaluate
- from datasets import CityscapesPanoptic
- from models import PanopticDeepLab
-
-
- 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=None)
- parser.add_argument(
- '--num_workers',
- dest='num_workers',
- help='Num workers for data loader',
- type=int,
- default=0)
- parser.add_argument(
- '--threshold',
- dest='threshold',
- help='Threshold applied to center heatmap score',
- type=float,
- default=0.1)
- parser.add_argument(
- '--nms_kernel',
- dest='nms_kernel',
- help='NMS max pooling kernel size',
- type=int,
- default=7)
- parser.add_argument(
- '--top_k',
- dest='top_k',
- help='Top k centers to keep',
- type=int,
- default=200)
-
- 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)
- cfg.check_sync_info()
- 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:
- paddleseg.utils.utils.load_entire_model(model, args.model_path)
- logger.info('Loaded trained params of model successfully')
-
- evaluate(
- model,
- val_dataset,
- threshold=args.threshold,
- nms_kernel=args.nms_kernel,
- top_k=args.top_k,
- num_workers=args.num_workers, )
-
-
- if __name__ == '__main__':
- args = parse_args()
- main(args)
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