python - 棕褐色效果opencv python中的错误

Question

我正在尝试创建一个滤镜，为所有图片创建棕褐色外观。但是我在过滤后的图像中发现了一些蓝色和青色的 Blob 。我认为它可能溢出了，但我试图解释这一点，但它并没有给我想要的影响。我不确定怎么了。原始链接位于https://www.dropbox.com/s/pd0esc8tef3smae/Lampard.jpg。修改后变为https://www.dropbox.com/s/f9n9lrhoi1qqs53/Lampard_blue.jpg

def filter3(path, cv2):
cv2.destroyAllWindows()
cv2.namedWindow("Filter 3")
img = cv2.imread(path, cv2.IMREAD_UNCHANGED) 
newImg = img
(i,j,k) = img.shape
for x in xrange(i):
    for y in xrange(j):
        b = img[x,y,0]
        g = img[x,y,1]
        r = img[x,y,2]
        if(k == 4):
            newImg[x,y,0] = np.uint16(b * 0.272 + g * 0.534 + r * 0.131)
            newImg[x,y,1] = np.uint8(b * .349 + g * 0.686 + r * 0.168)
            newImg[x,y,2] = np.uint8(b * 0.393 + g * 0.769 + r * 0.189)
            # newB = np.uint16(b * 0.272 + g * 0.534 + r * 0.131)
            # newG = np.uint16(b * .349 + g * 0.686 + r * 0.168)
            # newR = np.uint16(b * 0.393 + g * 0.769 + r * 0.189)
            # if(newB > 255):
            #   newImg[x,y,0] = np.uint8(255)
            # else: 
            #   newImg[x,y,0] = np.uint8(newB)
            # if(newG > 255):
            #   newImg[x,y,1] = np.uint8(255) 
            # else: 
            #   newImg[x,y,1] = np.uint8(newB)
            # if(newR > 255):
            #   newImg[x,y,2] = np.uint8(255) 
            # else: 
            #   newImg[x,y,2] = np.uint8(newB)

            newImg[x,y,3] = img[x,y,3]
        else:
            newImg[x,y,0] = np.uint16(b * 0.272 + g * 0.534 + r * 0.131)
            newImg[x,y,1] = np.uint8(b * .349 + g * 0.686 + r * 0.168)
            newImg[x,y,2] = np.uint8(b * 0.393 + g * 0.769 + r * 0.189)
            # if(newB > 255):
            #   newImg[x,y,0] = np.uint8(0)
            # else: 
            #   newImg[x,y,0] = np.uint8(newB)
cv2.imshow("Filter 3", newImg)
return newImg

Answer 1

在我看来，问题出在类型上。 Python 认为在操作后你想要整数。每个 channel 有 8 位。计算后你将获得值 256 (100000001) python 将只读取前 8 位 (00000001)。因此，您的形象有点奇怪。在我的例子中，这段代码有效:

import cv2
import numpy as np
from matplotlib import pyplot as plt

img = cv2.imread('lena.jpg')
newImage = cv2.imread('lena.jpg')
i, j, k = img.shape
for x in xrange(i):
    for y in xrange(j):
    R = img[x,y,2] * 0.393 + img[x,y,1] * 0.769 + img[x,y,0] * 0.189
    G = img[x,y,2] * 0.349 + img[x,y,1] * 0.686 + img[x,y,0] * 0.168
    B = img[x,y,2] * 0.272 + img[x,y,1] * 0.534 + img[x,y,0] * 0.131
    if R > 255:
        newImage[x,y,2] = 255
    else:
        newImage[x,y,2] = R
    if G > 255:
        newImage[x,y,1] = 255
    else:
        newImage[x,y,1] = G
    if B > 255:
        newImage[x,y,0] = 255
    else:
        newImage[x,y,0] = B

cv2.imshow('image',newImage)
cv2.waitKey(0)
cv2.destroyAllWindows()

也许这不是很好的代码，但我对 Python 不熟悉。