|
- # 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.
- # ============================================================================
- '''post process for 310 inference'''
- import os
- import argparse
- import numpy as np
-
- parser = argparse.ArgumentParser(description='fasterrcnn_export')
- parser.add_argument("--result_path", type=str, required=True, help="result file path")
- parser.add_argument("--label_file", type=str, required=True, help="label file")
- args = parser.parse_args()
-
- def read_label(label_file):
- f = open(label_file, "r")
- lines = f.readlines()
-
- img_label = {}
- for line in lines:
- img_id = line.split(":")[0]
- label = line.split(":")[1]
- img_label[img_id] = label
-
- return img_label
-
- def cal_acc(result_path, label_file):
- step = 0
- sum_a = 0
- img_label = read_label(label_file)
-
- files = os.listdir(result_path)
- for file in files:
- full_file_path = os.path.join(result_path, file)
- if os.path.isfile(full_file_path):
- result = np.fromfile(full_file_path, dtype=np.float32).reshape(1, 1000)
- pred = np.argmax(result, axis=1)
- step = step + 1
- if pred == int(img_label[file[:-6]]):
- sum_a = sum_a + 1
-
- print("========step:{}========".format(step))
- print("========sum:{}========".format(sum_a))
- accuracy = sum_a * 100.0 / step
- print("========accuracy:{}========".format(accuracy))
-
- if __name__ == "__main__":
- cal_acc(args.result_path, args.label_file)
|
