In [40]:

    

# Convert the photos to 256x256 so that our algorithm can handle them.
%matplotlib inline

import glob
from PIL import Image
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import skimage 
import numpy as np
from mpl_toolkits.axes_grid import AxesGrid

IMAGE_SIZE = 256


filenames = glob.glob('../../datasets/paper_examples/greyscale_full/*.jpg')
filenames.sort()

# Resize and convert to RGB
resized_images = [skimage.color.gray2rgb(skimage.transform.resize(skimage.io.imread(filename, as_grey=True),(IMAGE_SIZE,IMAGE_SIZE))) for filename in filenames]

# Display the images
fig = plt.figure()
grid = AxesGrid(fig,
                rect=(1, 1,0),
                nrows_ncols=(1, 5),
                axes_pad=0.1)

for i, frame in enumerate(resized_images):
    grid[i].imshow(frame, cmap=plt.cm.gray)
    grid[i].set_xlabel('Image %s' % i)
    grid[i].set_xticks([])
    grid[i].set_yticks([])

plt.show()


    

In [41]:

    

# save the resized images
for i, frame in enumerate(resized_images):
    skimage.io.imsave('../../datasets/paper_examples/greyscale_256/{}.jpg'.format(i+1), frame)


    

In [42]:

    

# convert the ground truth images to 256 also

filenames = glob.glob('../../datasets/paper_examples/ref_colorized_full/*.png')
filenames.sort()

# Resize and convert to RGB
resized_images = [skimage.transform.resize(skimage.io.imread(filename),(IMAGE_SIZE,IMAGE_SIZE)) for filename in filenames]

# Display the images
fig = plt.figure()
grid = AxesGrid(fig,
                rect=(1, 1,0),
                nrows_ncols=(1, 5),
                axes_pad=0.1)

for i, frame in enumerate(resized_images):
    grid[i].imshow(frame, cmap=plt.cm.gray)
    grid[i].set_xlabel('Image %s' % i)
    grid[i].set_xticks([])
    grid[i].set_yticks([])

plt.show()


    

In [43]:

    

# save the resized images
for i, frame in enumerate(resized_images):
    skimage.io.imsave('../../datasets/paper_examples/ref_colorized_256/{}.jpg'.format(i+1), frame)


    

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