forked from yaoyao-liu/social-relation-tensorflow
/
utils.py
58 lines (48 loc) · 1.43 KB
/
utils.py
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import numpy as np
import scipy.misc as scm
import os
import tensorflow as tf
def get_img_list(img_list_dir):
img_dir_list = []
img_label_list = {}
path = os.path.join(img_list_dir)
file = open(path,'r')
count = 0
for line in file:
row = line.split('\n')[0].split()
img_dir = row.pop(0)
img_label = row.pop(0)
#img_dir_list[count] = img_dir
img_dir_list.append(img_dir)
img_label_list[img_dir] = img_label
count += 1
file.close()
return img_label_list, img_dir_list
def load_img(data_list, image_size):
img = [get_img(img_path, image_size) for img_path in data_list]
img = np.array(img)
return img
def process_list(dir_list, num_list):
output_list=[]
for i in range(len(num_list)):
output_list.append(dir_list[num_list[i]])
return output_list
def get_img(img_path, data_size):
img = scm.imread(img_path)
#img = img[61:189,61:189,:]
img_resize = scm.imresize(img,[data_size,data_size,3])
#img_resize = img_resize/127.5 - 1.
return img_resize
def preprocess_label(label, cls_num):
label_out = []
tmp = []
for i in range(len(label)):
this_label = int(label[i]) - 1
for j in range(cls_num):
if j == this_label:
tmp.append(1.)
else:
tmp.append(0.)
label_out.append(tmp)
tmp = []
return label_out