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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 sys
- import paddle
- import yaml
- import paddleseg
- from paddleseg.cvlibs import manager
- from paddleseg.utils import logger
- LOCAL_PATH = os.path.dirname(os.path.abspath(__file__))
- sys.path.append(os.path.join(LOCAL_PATH, '..'))
- manager.BACKBONES._components_dict.clear()
- manager.TRANSFORMS._components_dict.clear()
- import ppmatting
- from ppmatting.utils import get_input_spec, Config, MatBuilder
- def parse_args():
- parser = argparse.ArgumentParser(description='Model export.')
- # params of training
- parser.add_argument(
- "--config",
- dest="cfg",
- help="The config file.",
- default=None,
- type=str,
- required=True)
- parser.add_argument(
- '--save_dir',
- dest='save_dir',
- help='The directory for saving the exported model',
- type=str,
- default='./output')
- parser.add_argument(
- '--model_path',
- dest='model_path',
- help='The path of model for export',
- type=str,
- default=None)
- parser.add_argument(
- '--trimap',
- dest='trimap',
- help='Whether to input trimap',
- action='store_true')
- parser.add_argument(
- "--input_shape",
- nargs='+',
- help="Export the model with fixed input shape, such as 1 3 1024 1024.",
- type=int,
- default=None)
- return parser.parse_args()
- def main(args):
- assert args.cfg is not None, \
- 'No configuration file specified, please set --config'
- cfg = Config(args.cfg)
- builder = MatBuilder(cfg)
- paddleseg.utils.show_env_info()
- paddleseg.utils.show_cfg_info(cfg)
- os.environ['PADDLESEG_EXPORT_STAGE'] = 'True'
- net = builder.model
- net.eval()
- if args.model_path:
- para_state_dict = paddle.load(args.model_path)
- net.set_dict(para_state_dict)
- logger.info('Loaded trained params of model successfully.')
- if args.input_shape is None:
- shape = [None, 3, None, None]
- else:
- shape = args.input_shape
- input_spec = get_input_spec(
- net.__class__.__name__, shape=shape, trimap=args.trimap)
- net = paddle.jit.to_static(net, input_spec=input_spec)
- save_path = os.path.join(args.save_dir, 'model')
- paddle.jit.save(net, save_path)
- yml_file = os.path.join(args.save_dir, 'deploy.yaml')
- with open(yml_file, 'w') as file:
- transforms = cfg.val_dataset_cfg.get('transforms', [{
- 'type': 'Normalize'
- }])
- data = {
- 'Deploy': {
- 'transforms': transforms,
- 'model': 'model.pdmodel',
- 'params': 'model.pdiparams',
- 'input_shape': shape
- },
- 'ModelName': net.__class__.__name__
- }
- yaml.dump(data, file)
- logger.info(f'Model is saved in {args.save_dir}.')
- if __name__ == '__main__':
- args = parse_args()
- main(args)
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