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# ------------------------------------------------------------------------------
# Util functions to visualize images.
# ------------------------------------------------------------------------------
import numpy as np
import cv2 as cv
from PIL import Image
def split(x):
assert type(x) == int
t = int(np.floor(np.sqrt(x)))
for a in range(t, 0, -1):
if x % a == 0:
return a, x / a
def grid_transform(x):
n, c, h, w = x.shape
a, b = split(n)
x = np.transpose(x, [0, 2, 3, 1])
x = np.reshape(x, [int(a), int(b), int(h), int(w), int(c)])
x = np.transpose(x, [0, 2, 1, 3, 4])
x = np.reshape(x, [int(a * h), int(b * w), int(c)])
if x.shape[2] == 1:
x = np.squeeze(x, axis=2)
return x
def seq_transform(x):
n, c, h, w = x.shape
x = np.transpose(x, [2, 0, 3, 1])
x = np.reshape(x, [h, n * w, c])
return x
# Converts image pixels from range [-1, 1] to [0, 255].
def data2img(data):
rescaled = np.divide(data + 1.0, 2.0) * 255.
rescaled = np.clip(rescaled, 0, 255)
return np.rint(rescaled).astype('uint8')
def data2pil(data):
return Image.fromarray(data2img(data), mode='RGB')
def interleave(a, b):
res = np.empty([a.shape[0] + b.shape[0]] + list(a.shape[1:]), dtype=a.dtype)
res[0::2] = a
res[1::2] = b
return res
def save_image(filepath, img):
pilimg = Image.fromarray(img)
pilimg.save(filepath)
def imread(filename):
img = cv.imread(filename, cv.IMREAD_UNCHANGED)
if img is not None:
if len(img.shape) > 2:
img = img[...,::-1]
return img
def imconvert_float32(im):
im = np.float32(im)
im = (im / 255) * 2.0 - 1
return im
def load_image(opt_fp_in, opt_dims=128):
target_im = imread(opt_fp_in)
w = target_im.shape[1]
h = target_im.shape[0]
if w <= h:
scale = opt_dims / w
else:
scale = opt_dims / h
target_im = cv.resize(target_im,(0,0), fx=scale, fy=scale)
w = target_im.shape[1]
h = target_im.shape[0]
x0 = 0
x1 = opt_dims
y0 = 0
y1 = opt_dims
if w > opt_dims:
x0 += int((w - opt_dims) / 2)
x1 += x0
if h > opt_dims:
y0 += int((h - opt_dims) / 2)
y1 += y0
phi_target = imconvert_float32(target_im)
phi_target = phi_target[y0:y1,x0:x1]
if phi_target.shape[2] == 4:
phi_target = phi_target[:,:,1:4]
b = np.dsplit(phi_target, 3)
phi_target = np.stack(b).reshape((3,opt_dims, opt_dims))
#print(phi_target.shape)
#phi_target = np.expand_dims(phi_target, 0)
#phi_target = np.reshape(3, opt_dims, opt_dims)
return phi_target
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