Python OpenCV像素操作
Python OpenCV像素操作
OpenCV学堂
发布于 2018-04-04 11:19:38
发布于 2018-04-04 11:19:38
Python OpenCV像素操作
环境声明 ： Python3.6 + OpenCV3.3 + PyCharm IDE
首先要引入OpenCV和Numpy支持，添加代码如下：
import cv2 as cv;
import numpy as np;读写像素
对RGB图像来说，在Python中第一个维度表示高度、第二个维度表示宽度、第三个维度是通道数目，可以通过下面的代码获取图像三个维度的大小
print(image.shape)
print(image.size)
print(image.dtype)循环读取图像方法一：
直接从图像中读取，缺点是每次都需要访问imread之后的Mat对象，进行native操作，速度是个问题， 代码实现如下：
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)循环读取图像方法二：
首先通过Numpy把像素数据读到内存中，在内存中进行高效循环访问每个像素，修改之后，在赋值回去即可，代码如下：
# 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语言中完成图像的属性读取、像素读取与操作、实现了图像的颜色取反、亮度提升、灰度化、梯度化、操作。首先看一下效果：
完整的Python代码实现如下：
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()本文参与 腾讯云自媒体分享计划，分享自微信公众号。
原始发表：2017-10-09，如有侵权请联系 cloudcommunity@tencent.com 删除
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