In [6]:

    

%matplotlib inline

import numpy as np
from scipy.misc import imread, imresize
import matplotlib.pyplot as plt

import rawpy
import imageio

img_list = ['1.pgm', '891539.bmp', 'fR01.raw', 'lenna.tif', 'koala512.jpg', 'array.tif']


    

In [50]:

    

# for test
img = imread(img_list[0])
print(img.shape)
plt.imshow(img)
plt.show()

# img_reshape = img.reshape(img.shape[0]*img.shape[1], 1)
# img_hist = plt.hist(img_reshape, 256)
# plt.show()


    

    




(128, 128)






    

In [93]:

    

# use plt.subplot()

img_list = ['1.pgm', '891539.bmp', 'fR01.raw', 'lenna.tif', 'koala512.jpg', 'array.tif']
subplot_list = [1, 2, 3, 7, 8, 9]

plt.figure(figsize=(20, 20))


for i in range(len(img_list)):
    
    target_img = img_list[i]
    subplot_index = subplot_list[i]
    
    if target_img == 'fR01.raw':
        img = np.fromfile(target_img, 'uint8')
        img = img.reshape(300, 300)
    else:
        img = imread(target_img)
    
    plt.subplot(4, 3, subplot_index)
    plt.title(target_img, fontsize=20)
    plt.imshow(img)
#     plt.show()

    new_shape = 1
    for shape in img.shape:
        new_shape = new_shape * shape

    plt.subplot(4, 3, subplot_index+3)
    plt.title('Histogram of ' + target_img, fontsize=20)
    img_reshape = img.reshape(new_shape, 1)
    img_hist = plt.hist(img_reshape, 256)

plt.tight_layout()    
# plt.show()
plt.savefig('output_by_python.png', dpi=300)


    

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