step_2_cnns.py

import numpy as np

filter_vals = np.array([
  [-1, -1, 1, 1],
  [-1, -1, 1, 1],
  [-1, -1, 1, 1],
  [-1, -1, 1, 1]
])

print('Filter shape: ', filter_vals.shape)

# Defining the Filters
filter_1 = filter_vals
filter_2 = -filter_1
filter_3 = filter_1.T
filter_4 = -filter_3
filters = np.array([filter_1, filter_2, filter_3, filter_4])

# Check the Filters
fig = plt.figure(figsize=(10, 5))
for i in range(4):
    ax = fig.add_subplot(1, 4, i+1, xticks=[], yticks=[])
    ax.imshow(filters[i], cmap='gray')
    ax.set_title('Filter %s' % str(i+1))
    width, height = filters[i].shape
    for x in range(width):
        for y in range(height):
            ax.annotate(str(filters[i][x][y]), xy=(y,x),
                        color='white' if filters[i][x][y]<0 else 'black')