utils.py

import numpy as np
import os
import cv2

def getImages(images,metadata):

	images_list = os.listdir(images)
	img_data = []

	f=open(metadata)
	f.readline()
	for line in f:
		imagefilename = line.strip().split("\t")[1]
		input_img = cv2.imread(os.path.join(images,imagefilename))
		input_img_resize=cv2.resize(input_img,(32,32))
		img_data.append(input_img_resize)
	return img_data


def images_to_sprite(data):
	"""Creates the sprite image along with any necessary padding
	Args:
	data: NxHxW[x3] tensor containing the images.
	Returns:
	data: Properly shaped HxWx3 image with any necessary padding.
	"""
	if len(data.shape) == 3:
		data = np.tile(data[...,np.newaxis], (1,1,1,3))
	data = data.astype(np.float32)
	min = np.min(data.reshape((data.shape[0], -1)), axis=1)
	data = (data.transpose(1,2,3,0) - min).transpose(3,0,1,2)
	max = np.max(data.reshape((data.shape[0], -1)), axis=1)
	data = (data.transpose(1,2,3,0) / max).transpose(3,0,1,2)
	# Inverting the colors seems to look better for MNIST
	#data = 1 - data

	n = int(np.ceil(np.sqrt(data.shape[0])))
	padding = ((0, n ** 2 - data.shape[0]), (0, 0),
			(0, 0)) + ((0, 0),) * (data.ndim - 3)
	data = np.pad(data, padding, mode='constant',
			constant_values=0)
	# Tile the individual thumbnails into an image.
	data = data.reshape((n, n) + data.shape[1:]).transpose((0, 2, 1, 3)
			+ tuple(range(4, data.ndim + 1)))
	data = data.reshape((n * data.shape[1], n * data.shape[3]) + data.shape[4:])
	data = (data * 255).astype(np.uint8)
	return data