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- # Copyright 2021 Huawei Technologies Co., Ltd
- #
- # 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.
- # ============================================================================
-
- """Export checkpoint into mindir or air for 310 inference."""
- import argparse
- import numpy as np
-
- from mindspore import Tensor, context, load_checkpoint, load_param_into_net, export
-
- from src.seg_hrnet_ocr import get_seg_model
- from src.config import config_hrnetv2_w48 as config
-
-
- def main():
- parser = argparse.ArgumentParser("OCRNet Semantic Segmentation exporting.")
- parser.add_argument("--device_id", type=int, default=0, help="Device ID. ")
- parser.add_argument("--checkpoint_file", type=str, help="Checkpoint file path. ")
- parser.add_argument("--file_name", type=str, help="Output file name. ")
- parser.add_argument("--file_format", type=str, default="MINDIR",
- choices=["AIR", "MINDIR"], help="Output file format. ")
-
- args = parser.parse_args()
-
- context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", device_id=args.device_id)
-
- net = get_seg_model(config)
- params_dict = load_checkpoint(args.checkpoint_file)
- load_param_into_net(net, params_dict)
- net.set_train(False)
- height, width = config.eval.image_size[0], config.eval.image_size[1]
- input_data = Tensor(np.zeros([1, 3, height, width], dtype=np.float32))
- export(net, input_data, file_name=args.file_name, file_format=args.file_format)
-
-
- if __name__ == "__main__":
- main()
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