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- # Copyright 2020 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.
- # ============================================================================
- """eval deeplabv3."""
-
- import os
- import argparse
-
- from mindspore import context
- from mindspore.train.serialization import load_checkpoint, load_param_into_net
- from src.nets import net_factory
- from src.utils.eval_utils import BuildEvalNetwork, net_eval
-
- context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", save_graphs=False,
- device_id=int(os.getenv('DEVICE_ID')))
-
-
- def parse_args():
- parser = argparse.ArgumentParser('mindspore deeplabv3 eval')
-
- # val data
- parser.add_argument('--data_root', type=str, default='', help='root path of val data')
- parser.add_argument('--data_lst', type=str, default='', help='list of val data')
- parser.add_argument('--batch_size', type=int, default=16, help='batch size')
- parser.add_argument('--crop_size', type=int, default=513, help='crop size')
- parser.add_argument('--image_mean', type=list, default=[103.53, 116.28, 123.675], help='image mean')
- parser.add_argument('--image_std', type=list, default=[57.375, 57.120, 58.395], help='image std')
- parser.add_argument('--scales', type=float, action='append', help='scales of evaluation')
- parser.add_argument('--flip', action='store_true', help='perform left-right flip')
- parser.add_argument('--ignore_label', type=int, default=255, help='ignore label')
- parser.add_argument('--num_classes', type=int, default=21, help='number of classes')
-
- # model
- parser.add_argument('--model', type=str, default='deeplab_v3_s16', help='select model')
- parser.add_argument('--ckpt_path', type=str, default='', help='model to evaluate')
- args_space, _ = parser.parse_known_args()
- return args_space
-
-
- if __name__ == '__main__':
- args = parse_args()
- # network
- if args.model == 'deeplab_v3_s16':
- network = net_factory.nets_map[args.model](args.num_classes, 16)
- elif args.model == 'deeplab_v3_s8':
- network = net_factory.nets_map[args.model](args.num_classes, 8)
- else:
- raise NotImplementedError('model [{:s}] not recognized'.format(args.model))
- eval_net = BuildEvalNetwork(network, args.input_format)
- # load model
- param_dict = load_checkpoint(args.ckpt_path)
- load_param_into_net(eval_net, param_dict)
- eval_net.set_train(False)
-
- net_eval(args, eval_net)
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