blur.py

# Load image pixels
data = np.array(image)

# Half kernel size
a = kernel_size // 2

for x in range(width):
    for y in range(height):
        # min and max are used for edge pixels
        x_start = max(x - a, 0)
        y_start = max(y - a, 0)

        x_end = min(x + a + 1, width)
        y_end = min(y + a + 1, height)

        # Array with all pixels inside square
        square = data[y_start:y_end, x_start:x_end]

        # We take their average
        r_, g_, b_ = square.mean(axis=(0,1))
        
        new_pixel = (int(r_),int(g_), int(b_))
        new_image.putpixel((x, y), new_pixel)