Python opencv图像基本操作学习之灰度图转换

import cv2  # opencv读取的格式是BGR
import matplotlib.pyplot as plt
import numpy as np
# 读取图片；括号里面填写好路径就行！！
img = cv2.imread("./123.jpg")
 
print(img)
# 图像显示在窗口上面
# cv2.imshow("image", img)
# # 参数代表关闭图片后程序关闭的时间，数字越大时间越久
# cv2.waitKey(0)
# # 窗口关闭
# cv2.destroyAllWindows()
# shape方法：shape返回的是图像的行数，列数，色彩通道数
print(img.shape)
# (1440, 1080, 3)
 
 
# 改为灰色,图片转换为灰度图
img = cv2.imread("./123.jpg", cv2.IMREAD_GRAYSCALE)
print("*" * 100)
print(img)
print(img.shape)
# (1440, 1080)
cv2.imshow("image", img)
# 参数代表等待时间
cv2.waitKey(0)
# 窗口关闭
cv2.destroyAllWindows()
 
 
# 保存改变
cv2.imwrite("123.jpg", img)
 
 
# 查看图片类型
sd = type(img)
print(sd)
# 查看图片的总像素
img.size
print(img.size)
# 查看存储类型
img.dtype
print(img.dtype)
 

# 读取图片；括号里面填写好路径就行！！我这里当先目录下我导入的图片
img = cv2.imread("./123.jpg")

# 图像显示在窗口上面
 cv2.imshow("image", img)
 # 参数代表关闭图片后程序关闭的时间，数字越大时间越久
 cv2.waitKey(0)
# 窗口关闭
 cv2.destroyAllWindows()

img = cv2.imread("./123.jpg")
 
print(img)

# 改为灰色,图片转换为灰度图
img = cv2.imread("./123.jpg", cv2.IMREAD_GRAYSCALE)

cv2.imshow("image", img)
 # 参数代表关闭图片后程序关闭的时间，数字越大时间越久
cv2.waitKey(0)
# 窗口关闭
cv2.destroyAllWindows()

# 保存函数
cv2.imwrite("123.jpg", img)

# 查看图片类型
sd = type(img)
print(sd)
# 查看图片的总像素
img.size
print(img.size)
# 查看存储类型
img.dtype
print(img.dtype)

import cv2
import numpy as np

if __name__ == "__main__":
    img_path = "timg.jpg"
    img = cv2.imread(img_path)
    #获取图片的宽和高
    width,height = img.shape[:2][::-1]
    #将图片缩小便于显示观看
    img_resize = cv2.resize(img,
    (int(width*0.5),int(height*0.5)),interpolation=cv2.INTER_CUBIC)
    cv2.imshow("img",img_resize)
    print("img_reisze shape:{}".format(np.shape(img_resize)))

    #将图片转为灰度图
    img_gray = cv2.cvtColor(img_resize,cv2.COLOR_RGB2GRAY)
    cv2.imshow("img_gray",img_gray)
    print("img_gray shape:{}".format(np.shape(img_gray)))
    cv2.waitKey()

import cv2
import numpy as np

if __name__ == "__main__":
    img_path = "timg.jpg"
    img = cv2.imread(img_path)
    #获取图片的宽和高
    width,height = img.shape[:2][::-1]
    #将图片缩小便于显示观看
    img_resize = cv2.resize(img,
    (int(width*0.5),int(height*0.5)),interpolation=cv2.INTER_CUBIC)
    cv2.imshow("img",img_resize)
    print("img_reisze shape:{}".format(np.shape(img_resize)))

    #读取灰度图
    img_gray = cv2.imread(img_path,cv2.IMREAD_GRAYSCALE)
    #将图片缩小便于显示观看
    img_gray = cv2.resize(img_gray,
    (int(width*0.5),int(height*0.5)),interpolation=cv2.INTER_CUBIC)
    cv2.imshow("img_gray",img_gray)
    print("img_gray shape:{}".format(np.shape(img_gray)))
    cv2.waitKey()