mirror of https://github.com/alibaba/EasyCV.git
39 lines
1.2 KiB
Python
39 lines
1.2 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
|
|
'''
|
|
SimCLR provides list files for semi-supervised benchmarks:
|
|
https://github.com/google-research/simclr/tree/master/imagenet_subsets/
|
|
This script convert the list files into the required format in EasyCV.
|
|
'''
|
|
import argparse
|
|
|
|
parser = argparse.ArgumentParser(
|
|
description='Convert ImageNet subset lists provided by simclr.')
|
|
parser.add_argument('input', help='Input list file.')
|
|
parser.add_argument('output', help='Output list file.')
|
|
args = parser.parse_args()
|
|
|
|
# create dict
|
|
with open('data/imagenet/meta/train_labeled.txt', 'r') as f:
|
|
lines = f.readlines()
|
|
keys = [l.split('/')[0] for l in lines]
|
|
labels = [l.strip().split()[1] for l in lines]
|
|
mapping = {}
|
|
for k, l in zip(keys, labels):
|
|
if k not in mapping:
|
|
mapping[k] = l
|
|
else:
|
|
assert mapping[k] == l
|
|
|
|
# convert
|
|
with open(args.input, 'r') as f:
|
|
lines = f.readlines()
|
|
fns = [l.strip() for l in lines]
|
|
sample_keys = [l.split('_')[0] for l in lines]
|
|
sample_labels = [mapping[k] for k in sample_keys]
|
|
output_lines = [
|
|
'{}/{} {}\n'.format(k, fn, l)
|
|
for k, fn, l in zip(sample_keys, fns, sample_labels)
|
|
]
|
|
with open(args.output, 'w') as f:
|
|
f.writelines(output_lines)
|