convolution implementation for CV

convolution.py

import numpy as np
import cv2, sys, os.path
from itertools import chain
from functools import reduce

kernel = "smooth"
filename = "demo.png"

kernels = {
        "blur"    :   [[5/80,1/8,5/80],
                       [ 1/8,1/4, 1/8],
                       [5/80,1/8,5/80]],
        "topsobel" :  [[  1,   2,   1],
                       [  0,   0,   0],
                       [ -1,  -2,  -1]],
        "rightsobel": [[ -1,   0,   1],
                       [ -2,   0,   2],
                       [ -1,   0,   1]],
        "emboss" :    [[ -2,  -1,   0],
                       [ -1,   1,   1],
                       [  0,   1,   2]],
        "smooth"  :   [[1/9, 1/9, 1/9],
                       [1/9, 1/9, 1/9],
                       [1/9, 1/9, 1/9]],
        "sharpen" :   [[  0,  -1,   0],
                       [ -1,   5,  -1],
                       [  0,  -1,   0]],
        "edgedet" :   [[ -1,  -1,  -1],
                       [ -1,   8,  -1],
                       [ -1,  -1,  -1]],
        "identity":   [[  0,   0,   0],
                       [  0,   1,   0],
                       [  0,   0,   0]]
        }

dot = lambda a, b: sum(i[0] * i[1] for i in zip(a, b))
flatten = lambda it: list(chain.from_iterable(it))
normalize = lambda v: min(max(v, 0), 255)

def conv(image, y, x, kernel):
    K = flatten(kernel)
    kh, kw = len(kernel), len(kernel[0])
    channels = zip(*[image[y + dy][x + dx]
        for dy in range(-(kh // 2), kh // 2 + 1)
        for dx in range(-(kw // 2), kw // 2 + 1)])
    return [dot(channel, K) for channel in  channels]

if __name__ == '__main__':

    if "-h" in sys.argv or "--help" in sys.argv:
        print(sys.argv[0], "[file] [kernel name]\n")
        print("kernels:", ' '.join(kernels.keys())), exit(0)

    if len(sys.argv) > 1: filename = sys.argv[1]
    if len(sys.argv) > 2: kernel = sys.argv[2]
    if kernel not in kernels: print("kernel doesn't exist"), exit(1)
    if not os.path.isfile(filename): print(filename, "doesn't exit"), exit(1)

    img, kernel = cv2.imread(filename), kernels[kernel]
    height, width = len(img), len(img[0])

    kh, kw = len(kernel), len(kernel[0])
    new = np.array([[[normalize(rgb) for rgb in conv(img, y, x, kernel)]
                        for x in range(kw // 2, width - kw // 2)]
                        for y in range(kh // 2, height - kh // 2)],
                        dtype=np.uint8)

    cv2.namedWindow('origin', cv2.WINDOW_NORMAL)
    cv2.namedWindow('conv', cv2.WINDOW_NORMAL)
    cv2.imshow('origin', img), cv2.imshow('conv', new)
    cv2.waitKey(0), cv2.destroyAllWindows()