2020-04-19 22:29:00 +08:00
|
|
|
"""
|
|
|
|
|
.mat files data format
|
2020-04-17 18:34:58 +08:00
|
|
|
imagelabel.mat
|
|
|
|
|
jpg_name 1 2 3 ...
|
|
|
|
|
label 32 12 66 ...
|
|
|
|
|
|
|
|
|
|
setid.mat
|
|
|
|
|
jpg_name(10 records in a class) 24 6 100 65 32 ...
|
|
|
|
|
label 4 ...
|
2020-04-16 14:19:31 +08:00
|
|
|
"""
|
|
|
|
|
"""
|
2020-04-17 18:34:58 +08:00
|
|
|
Usage:
|
2020-04-19 22:29:00 +08:00
|
|
|
python generate_flower_list.py prefix_folder mode
|
|
|
|
|
python generate_flower_list.py jpg train > train_list.txt
|
|
|
|
|
python generate_flower_list.py jpg valid > val_list.txt
|
2020-04-17 18:34:58 +08:00
|
|
|
"""
|
2020-04-19 22:29:00 +08:00
|
|
|
|
|
|
|
|
import scipy.io
|
|
|
|
|
import numpy as np
|
|
|
|
|
import os
|
|
|
|
|
import sys
|
|
|
|
|
|
2020-04-16 14:19:31 +08:00
|
|
|
data_path = sys.argv[1]
|
2020-04-19 22:29:00 +08:00
|
|
|
imagelabels_path = './imagelabels.mat'
|
|
|
|
|
setid_path = './setid.mat'
|
2020-04-16 14:19:31 +08:00
|
|
|
|
|
|
|
|
labels = scipy.io.loadmat(imagelabels_path)
|
|
|
|
|
labels = np.array(labels['labels'][0])
|
|
|
|
|
setid = scipy.io.loadmat(setid_path)
|
|
|
|
|
|
|
|
|
|
d = {}
|
|
|
|
|
d['train'] = np.array(setid['trnid'][0])
|
|
|
|
|
d['valid'] = np.array(setid['valid'][0])
|
2020-04-19 22:29:00 +08:00
|
|
|
d['test'] = np.array(setid['tstid'][0])
|
2020-04-16 14:19:31 +08:00
|
|
|
|
|
|
|
|
for id in d[sys.argv[2]]:
|
2020-04-19 22:29:00 +08:00
|
|
|
message = str(data_path) + "/image_" + str(id).zfill(5) + ".jpg " + str(labels[id - 1] - 1)
|
2020-04-16 14:19:31 +08:00
|
|
|
print(message)
|
