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#!/usr/bin/env python
r"""Create a list containing image names and their corresponding class indices
for ImageNet validation data.
The directory structure of the original ImageNet validation data set is
expected to be:
data_dir/ILSVRC2012_val_00000001.JPEG
data_dir/ILSVRC2012_val_00000002.JPEG
...
date_dir/ILSVRC2012_val_00050000.JPEG
This script generate a list like:
ILSVRC2012_val_00000001.JPEG 65
ILSVRC2012_val_00000002.JPEG 970
...
ILSVRC2012_val_00050000.JPEG 355
Usage:
Download https://github.com/tensorflow/models/blob/master/research/slim/datasets/imagenet_2012_validation_synset_labels.txt and then,
./create_image_labels.py imagenet_2012_validation_synset_labels.txt
"""
import sys
if __name__ == '__main__':
if len(sys.argv) < 2:
print('Usage: ./create_image_labels.py <labels file>')
sys.exit(-1)
labels_file = sys.argv[1]
labels = [l.strip() for l in open(labels_file).readlines()]
sorted_labels = sorted(labels)
class_idx = 0
label_to_class_idx = {}
for label in sorted_labels:
if label not in label_to_class_idx:
label_to_class_idx[label] = class_idx
class_idx += 1
image_list_file = 'val.txt'
with open(image_list_file, 'w') as f:
for i, label in enumerate(labels):
image_name = 'ILSVRC2012_val_000%.5d.JPEG' % (i + 1)
f.write(f'{image_name} {label_to_class_idx[label]}\n')
print(f'Output image list file: {image_list_file}')
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