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47 lines
1.9 KiB
47 lines
1.9 KiB
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""export checkpoint file into air models"""
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import argparse
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import numpy as np
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from mindspore import Tensor, context, load_checkpoint, load_param_into_net, export
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from src.maskrcnn.mask_rcnn_r50 import Mask_Rcnn_Resnet50
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from src.config import config
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='maskrcnn_export')
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parser.add_argument('--ckpt_file', type=str, default='', help='maskrcnn ckpt file.')
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parser.add_argument('--output_file', type=str, default='', help='maskrcnn output air name.')
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args_opt = parser.parse_args()
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net = Mask_Rcnn_Resnet50(config=config)
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param_dict = load_checkpoint(args_opt.ckpt_file)
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load_param_into_net(net, param_dict)
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net.set_train(False)
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bs = config.test_batch_size
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img = Tensor(np.zeros([bs, 3, 768, 1280], np.float16))
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img_metas = Tensor(np.zeros([bs, 4], np.float16))
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gt_bboxes = Tensor(np.zeros([bs, 128, 4], np.float16))
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gt_labels = Tensor(np.zeros([bs, 128], np.int32))
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gt_num = Tensor(np.zeros([bs, 128], np.bool))
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gt_mask = Tensor(np.zeros([bs, 128], np.bool))
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export(net, img, img_metas, gt_bboxes, gt_labels, gt_num, gt_mask, file_name=args_opt.output_file,
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file_format="AIR")
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