forked from mindspore-Ecosystem/mindspore
59 lines
2.0 KiB
Python
59 lines
2.0 KiB
Python
# Copyright 2021 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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"""post process for 310 inference"""
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import os
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import argparse
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import numpy as np
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batch_size = 1
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parser = argparse.ArgumentParser(description="mobilenetv2 acc calculation")
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parser.add_argument("--result_path", type=str, required=True, help="result files path.")
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parser.add_argument("--label_path", type=str, required=True, help="label path.")
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args = parser.parse_args()
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def calcul_acc(labels, preds):
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return sum(1 for x, y in zip(labels, preds) if x == y) / len(labels)
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def read_label(label_path):
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label_dict = {}
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with open(label_path, 'r') as f:
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lines = f.readlines()
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for line in lines:
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file_name = line.split(':')[0]
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label = line.split(':')[1]
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label_dict[file_name] = label
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return label_dict
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def get_result(result_path, label_path):
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files = os.listdir(result_path)
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preds = []
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labels = []
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label_dict = read_label(label_path)
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for file in files:
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file_name = file.split('.')[0]
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label = int(label_dict[file_name])
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labels.append(label)
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output = np.fromfile(os.path.join(result_path, file), dtype=np.float32)
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preds.append(np.argmax(output, axis=0))
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acc = calcul_acc(labels, preds)
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print("total{}, accuracy: {}".format(len(labels), acc))
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if __name__ == '__main__':
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get_result(args.result_path, args.label_path)
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