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convert_iiit5k.py 2.11 KB
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zhaoting 提交于 2年前 . move official models
# Copyright 2020-21 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.
# ============================================================================
import argparse
from scipy import io
###############################################
# load testdata
# testdata.mat structure
# test[:][0] : image name
# test[:][1] : label
# test[:][2] : 50 lexicon
# test[:][3] : 1000 lexicon
##############################################
def init_args():
parser = argparse.ArgumentParser('')
parser.add_argument('-m', '--mat_file', type=str, default='testdata.mat',
help='Directory where character dictionaries for the dataset were stored')
parser.add_argument('-o', '--output_dir', type=str, default='./processed',
help='Directory where ord map dictionaries for the dataset were stored')
parser.add_argument('-a', '--output_annotation', type=str, default='./annotation.txt',
help='Directory where ord map dictionaries for the dataset were stored')
return parser.parse_args()
def mat_to_list(mat_file):
ann_ori = io.loadmat(mat_file)
testdata = ann_ori['testdata'][0]
ann_output = []
for elem in testdata:
img_name = elem[0]
label = elem[1]
ann = img_name[0] + ',' + label[0]
ann_output.append(ann)
return ann_output
def convert():
args = init_args()
ann_list = mat_to_list(args.mat_file)
ann_file = args.output_annotation
with open(ann_file, 'w') as f:
for line in ann_list:
txt = line + '\n'
f.write(txt)
if __name__ == "__main__":
convert()
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