Convert image by CNN weights

viz_filter.py

import numpy as np
from scipy.ndimage import convolve
import tensorflow as tf
from tensorflow import pywrap_tensorflow
from PIL import Image
from matplotlib import pyplot as plt

plt.axis('off')
img = Image.open('009_0001.jpg')
plt.imshow(img)
plt.show()

checkpoint = pywrap_tensorflow.NewCheckpointReader('inception-v3/model.ckpt-157585')
conv0 = checkpoint.get_tensor('conv0/weights')
conv0 = conv0.transpose((3, 2, 0, 1)) # transpose kernel [H, W, In, Out] to [Out, In, H, W]
images = []
for i in range(32):
    _kernel = conv0[i]
    print(i)

    img1 = np.asarray(img)
    img1 = img1.transpose((2, 0, 1)) # transpose image [H, W, C] to [C, H, W]
    imgR = convolve(img1[0], _kernel[0], mode='constant')
    imgG = convolve(img1[1], _kernel[1], mode='constant')
    imgB = convolve(img1[2], _kernel[2], mode='constant')
    img1 = np.asarray(imgR + imgG + imgB)
    images.append(img1)
    plt.axis('off')
    plt.imshow(img1, cmap='gray')
    plt.show()
    
for i in range(11):
    for j in range(11):
        if i != j:
            img1 = (images[i] + images[j]) / 2.0
            print("%d + %d" % (i, j))
            plt.axis('off')
            plt.imshow(img1, cmap='gray')
            plt.show()