mindspore2022/model_zoo/official/cv/resnet/preprocess.py

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1.9 KiB
Python
Executable File

# 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.
# ============================================================================
"""train resnet."""
import os
import argparse
from src.dataset import create_dataset1 as create_dataset
parser = argparse.ArgumentParser(description='preprocess data')
parser.add_argument('--dataset_path', type=str, default=None, help='Dataset path')
parser.add_argument('--output_path', type=str, default=None, help='output path')
args_opt = parser.parse_args()
if __name__ == '__main__':
# create dataset
dataset = create_dataset(dataset_path=args_opt.dataset_path, do_train=False, batch_size=1,
target="Ascend")
step_size = dataset.get_dataset_size()
img_path = os.path.join(args_opt.output_path, "img_data")
label_path = os.path.join(args_opt.output_path, "label")
os.makedirs(img_path)
os.makedirs(label_path)
for idx, data in enumerate(dataset.create_dict_iterator(output_numpy=True, num_epochs=1)):
img_data = data["image"]
img_label = data["label"]
file_name = "google_cifar10_1_" + str(idx) + ".bin"
img_file_path = os.path.join(img_path, file_name)
img_data.tofile(img_file_path)
label_file_path = os.path.join(label_path, file_name)
img_label.tofile(label_file_path)
print("=" * 20, "export bin files finished", "=" * 20)