opencv python接口 像素访问例程

opencv2.3.1 python 2.7

import cv2.cv
from decimal import *
from math import ceil

wnd_name = "CV";
cv2.namedWindow(wnd_name);
img = cv2.imread("a.jpg");
cv2.imshow(wnd_name,img);
key = cv2.waitKey(-1);

mB = img[0:img.shape[0], 0:img.shape[1], 0] / 255.0;
mG = img[0:img.shape[0], 0:img.shape[1], 1] / 255.0;
mR = img[0:img.shape[0], 0:img.shape[1], 2] / 255.0;
mY = 65.481 * mR + 128.553 * mG + 24.966 * mB + 16;
#round to int

mY = mY + 0.5;
mY = mY.astype(int);

for row in range(img.shape[0] - 1) :
    for col inrange(img.shape[1] - 1) :
   if mY[row,col] > 255: 
   mY[row,col] = 255;
img[:,:,0] = mY;
img[:,:,1] = mY;
img[:,:,2] = mY;
#
#for row in range(img.shape[0]) :
#    for col inrange(img.shape[1]) :
#       B = img[row,col,0];
#       G = img[row,col,1];
#       R = img[row,col,2];
#       B = B / 255.0;
#       G = G / 255.0;
#       R = R / 255.0;
#       Y = 65.481 * R + 128.553 * G + 24.966 * B +16;
#       Y = int(ceil(Y));
#       if Y > 255 :
#           Y =255;
#       if Y < 0 :
#           Y =0;
#       img[row,col,0] = Y;
#       img[row,col,1] = Y;
#       img[row,col,2] = Y;
#
cv2.imshow(wnd_name,img);
key = cv2.waitKey(-1);

while key == 'q' :
    key =cv2.waitKey(1);
cv2.destroyAllWindows();
cv2.imwrite("result.jpg", img);

最后, python逐像素访问效率很低,最好使用矩阵运算