Python OpenCV像素操作

重磅干貨，第一時(shí)間送達(dá)

本文轉(zhuǎn)自：opencv學(xué)堂

環(huán)境聲明 ： Python3.6 + OpenCV3.3 + PyCharm IDE

import cv2 as cv;
import numpy as np;

對RGB圖像來說，在Python中第一個(gè)維度表示高度、第二個(gè)維度表示寬度、第三個(gè)維度是通道數(shù)目，可以通過下面的代碼獲取圖像三個(gè)維度的大小

print(image.shape)
print(image.size)
print(image.dtype)

直接從圖像中讀取，缺點(diǎn)是每次都需要訪問imread之后的Mat對象，進(jìn)行native操作，速度是個(gè)問題， 代碼實(shí)現(xiàn)如下：

height = image.shape[0]
width = image.shape[1]
channels = image.shape[2]
print(image.shape)
for row in range(height):
    for col in range(width):
        for c in range(channels):
            level = image[row, col, c]
            pv = level + 30
            image[row, col, c] = (255 if pv>255 else pv)

首先通過Numpy把像素?cái)?shù)據(jù)讀到內(nèi)存中，在內(nèi)存中進(jìn)行高效循環(huán)訪問每個(gè)像素，修改之后，在賦值回去即可，代碼如下：

# read once
pixel_data = np.array(image, dtype = np.uint8);
# loop pixel by pixel
for row in range(height):
    for col in range(width):
        for c in range(channels):
            level = pixel_data[row, col, c]
            pixel_data[row, col, c] = 255 - level
# write once
image[ : : ] = pixel_data

案例演示 在Python語言中完成圖像的屬性讀取、像素讀取與操作、實(shí)現(xiàn)了圖像的顏色取反、亮度提升、灰度化、梯度化、操作。首先看一下效果：

完整的Python代碼實(shí)現(xiàn)如下：

import cv2 as cv;
import numpy as np;
def inverse(image):
    print("read and write pixel by pixel")
    print(image.shape)
    print(image.size)
    print(image.dtype)
    height = image.shape[0]
    width = image.shape[1]
    channels = image.shape[2]
    # read once
    pixel_data = np.array(image, dtype = np.uint8);
    # loop pixel by pixel
    for row in range(height):
        for col in range(width):
            for c in range(channels):
                level = pixel_data[row, col, c]
                pixel_data[row, col, c] = 255 - level
    # write once
    image[ : : ] = pixel_data
    cv.imshow("inverse image", image)
def brightness(image):
    print("read and write pixel by pixel")
    height = image.shape[0]
    width = image.shape[1]
    channels = image.shape[2]
    print(image.shape)
    for row in range(height):
        for col in range(width):
            for c in range(channels):
                level = image[row, col, c]
                pv = level + 30
                image[row, col, c] = (255 if pv>255 else pv)
    cv.imshow("inverse image", image);
def to_gray(image):
    print("RGB to Gray Image")
    height = image.shape[0]
    width = image.shape[1]
    channels = image.shape[2]
    print("channels : ", channels);
    print(image.shape)
    for row in range(height):
        for col in range(width):
            blue = image[row, col, 0]
            green = image[row, col, 1];
            red = image[row, col, 2]
            gray = (0.2989*red + 0.5870*green + 0.1140*blue);
            image[row, col, 0] = gray;
            image[row, col, 1] = gray;
            image[row, col, 2] = gray;
    cv.imshow("gray image", image)
def gradient_image(image):
    gx = cv.Sobel(image, cv.CV_32F, 1, 0)
    gy = cv.Sobel(image, cv.CV_32F, 0, 1)
    dst = cv.addWeighted(gx, 0.5, gy, 0.5, 50)
    sobel_abs = np.absolute(dst)
    sobel_8u = np.uint8(sobel_abs)
    cv.imshow("gradient image", sobel_8u)
def clam(pv):
    if pv > 255:
        return 255
    if pv < 0:
        return 0;
    return pv;
print("Image Pixel Operation Demo")
src = cv.imread("D:/vcprojects/images/demo.png")
cv.namedWindow("input image", cv.WINDOW_AUTOSIZE)
cv.imshow("input image", src)
gradient_image(src)
cv.waitKey(0)
cv.destroyAllWindows()