OpenCV图像处理

import cv2 as cv
# 读取图片
img = cv.imread('../Resources/Photos/park.jpg')
cv.imshow('Park', img)

# 灰度化
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow('Gray', gray)

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# -*- coding: utf-8 -*-
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from PIL import Image
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from pylab import *
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#读取图片,灰度化，并转为数组
im = array(Image.open("Resources/Photos/park.jpg").convert('L'))
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im2 = 255 - im                  # 对图像进行反相处理
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im3 = (100.0/255) * im + 100    # 将图像像素值变换到 100...200 区间
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im4 = 255.0 * (im/255.0)**2     # 对图像像素值求平方后得到的图像(二次函数变换，使较暗的像素值变得更小)
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#2x2显示结果 使用第一个显示原灰度图
#subplot(221)
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title('gray')
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gray()
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imshow(im)
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show()

import cv2 as cv
import matplotlib.pyplot as plt
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img = cv.imread('../Resources/Photos/park.jpg')
cv.imshow('Park', img)

# BGR to HSV
hsv = cv.cvtColor(img, cv.COLOR_BGR2HSV)
cv.imshow('HSV', hsv)

# BGR to L*a*b
lab = cv.cvtColor(img, cv.COLOR_BGR2LAB)
cv.imshow('LAB', lab)

# BGR to RGB
rgb = cv.cvtColor(img, cv.COLOR_BGR2RGB)
cv.imshow('RGB', rgb)

# HSV to BGR
lab_bgr = cv.cvtColor(lab, cv.COLOR_LAB2BGR)
cv.imshow('LAB --> BGR', lab_bgr)