第二天openc的内容：图片的缩放、旋转、格式转换

1.图像类型转换：

　　1.gray（灰度）————bgr（彩色）

import cv2
img=cv2.imread('D:\cc1\lena256.bmp',cv2.IMREAD_UNCHANGED)
img1=cv2.cvtColor(img,cv2.COLOR_GRAY2BGR)
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey()
cv2.destroyAllWindows()

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　　2.bgr（彩色）------------gray（灰度）

import cv2
img=cv2.imread('D:\cc1\lena.bmp',cv2.IMREAD_UNCHANGED)
img1=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey()
cv2.destroyAllWindows()

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　　3.BGR---------RGB

import cv2
img=cv2.imread('D:\cc1\lenacolor.png',cv2.IMREAD_UNCHANGED)
img1=cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey()
cv2.destroyAllWindows()

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2.图像的大小：

　　1.使用图像的行数和列数进行缩放：

import cv2
img=cv2.imread('D:\cc1\lenacolor.png',cv2.IMREAD_UNCHANGED)
img1=cv2.resize(img,(111,222))# 显示列在是行
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey()
cv2.destroyAllWindows()

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　　2.使用行数和列数的比列进行缩放：

import cv2
img=cv2.imread('D:\cc1\lenacolor.png',cv2.IMREAD_UNCHANGED)
rows,cols=img.shape[:2]
c1=(int(cols*0.5),int(rows*1.2))
print(c1)
img1=cv2.resize(img,(c1))# 显示列在是行
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey()
cv2.destroyAllWindows()

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　　3.使用fx和fy进行缩放：

import cv2
img=cv2.imread('D:\cc1\lenacolor.png',cv2.IMREAD_UNCHANGED)
img1=cv2.resize(img,None,fx=1,fy=0.4)
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey()
cv2.destroyAllWindows()

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3图像的反转：

　　1.绕x轴反转：

import cv2
img=cv2.imread('D:\cc1\lenacolor.png',cv2.IMREAD_UNCHANGED)
img1=cv2.flip(img,0)
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey()
cv2.destroyAllWindows()

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　　2.绕y周反转

import cv2
img=cv2.imread('D:\cc1\lenacolor.png',cv2.IMREAD_UNCHANGED)
img1=cv2.flip(img,1)
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey()
cv2.destroyAllWindows()

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　　3.绕对称轴旋转：

import cv2
img=cv2.imread('D:\cc1\lenacolor.png',cv2.IMREAD_UNCHANGED)
img1=cv2.flip(img,-5)
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey()
cv2.destroyAllWindows()

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4.图像的阈值化：

　　1.二进制阈值化：设定一个阈值，如果大于这个值，则将这个值设定为maxvalue，否则设为0

import cv2
img=cv2.imread('D:\cc1\lenacolor.png',cv2.IMREAD_UNCHANGED)
R,img1=cv2.threshold(img,123,255,cv2.THRESH_BINARY)
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey(-5)
cv2.destroyAllWindows()

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　　2.反二进制阈值化：设定一个阈值，如果小于这个值，则将这个值设定为maxvalue，否则设为0

import cv2
img=cv2.imread('D:\cc1\lena256.bmp',cv2.IMREAD_UNCHANGED)
R,img1=cv2.threshold(img,123,255,cv2.THRESH_BINARY_INV)
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey(-5)
cv2.destroyAllWindows()

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　　3.截断阈值化：设定一个阈值，如果大于于这个值，则将这个值设定为maxvalue，否则值保持不变

import cv2
img=cv2.imread('D:\cc1\lena256.bmp',cv2.IMREAD_UNCHANGED)
R,img1=cv2.threshold(img,123,255,cv2.THRESH_TRUNC)
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey(-5)
cv2.destroyAllWindows()

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　　4.阈值化为0：设定一个阈值，如果大于于这个值，则将这个值设定为0，否则值保持不变

import cv2
img=cv2.imread('D:\cc1\lena256.bmp',cv2.IMREAD_UNCHANGED)
R,img1=cv2.threshold(img,123,255,cv2.THRESH_TOZERO)
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey(-5)
cv2.destroyAllWindows()

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　　5.反阈值化为0：设定一个阈值，如果小于于这个值，则将这个值设定为0，否则值保持不变

import cv2
img=cv2.imread('D:\cc1\lena256.bmp',cv2.IMREAD_UNCHANGED)
R,img1=cv2.threshold(img,123,255,cv2.THRESH_TOZERO_INV)
cv2.imshow('old',img)
cv2.imshow('new',img1)
print(img.shape)
print(img1.shape)
cv2.waitKey(-5)
cv2.destroyAllWindows()

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