OpenCV：画像特殊効果処理（2）

1.救済効果

计算公式： 隣接するピクセルのピクセル値と定数値の差

import cv2
import numpy as np
img = cv2.imread('img.jpg', 1)
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
cv2.imshow('gray', gray)
dat = np.zeros((img.shape[0], img.shape[1], 1), np.uint8)
for i in range(img.shape[0]):
    for j in range(img.shape[1] - 1):
        newP = int(gray[i, j]) - int(gray[i, j + 1]) + 200
        if newP > 255:
            newP = 255
        if newP < 0:
            newP = 0
        dat[i, j] = newP
cv2.imshow('dat', dat)
cv2.waitKey(0)

2.カラーマッピング

青いピクセルと緑のピクセルを強調する

import cv2
import numpy as np
img = cv2.imread('img.jpg', 1)
cv2.imshow('img', img)
dat = np.zeros(img.shape, np.uint8)
for i in range(img.shape[0]):
    for j in range(img.shape[1]):
        (b, g, r) = img[i, j]
        b = b * 1.5
        g = g * 1.5
        if b > 255:
            b = 255
        if g > 255:
            g = 255
        dat[i, j] = (b, g, r)
cv2.imshow('dat', dat)
cv2.waitKey(0)

3.油絵特殊効果

基本的な手順：

1.转化为灰色图像
2.划分为若干个小方块，统计小方块中的灰度值
3.将灰度值划分为几个等级，如0-255划分为四个等级，每个等级的大小为64
4.找到每个方块中灰度等级最多的像素，并求均值
5.用该均值替代原来的像素值得到油画效果

以下は、小さな正方形の8*8油絵効果の実現です

import cv2
import numpy as np
img = cv2.imread('img4.png', 1)
cv2.imshow('img', img)
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
dat = np.zeros(img.shape, np.uint8)
for i in range(4, img.shape[0] - 4):
    for j in range(4, img.shape[1] - 4):
        array1 = np.zeros(8, np.uint8)
        for m in range(-4, 4):
            for n in range(-4, 4):
                array1[int(gray[i + m, j + n] / 32)] += 1
        countMax = array1[0]
        l = 0
        for k in range(8):
            if countMax < array1[k]:
                countMax = array1[k]
                l = k
        sum_b, sum_g, sum_r,cnt = 0,0,0,0
        for m in range(-4, 4):
            for n in range(-4, 4):
                if int(gray[i + m, j + n] / 32) == l:
                    (b,g,r) = img[i + m, j + m]
                    sum_b += b
                    sum_g += g
                    sum_r += r
                    cnt += 1
        dat[i, j] = (sum_b // cnt, sum_g // cnt, sum_r // cnt)
cv2.imshow('dat', dat)
cv2.waitKey(0)