【转载】python+opencv解决方案：保存图像的方法比较之一

https://blog.csdn.net/LiuKejiaHAX/article/details/80711208

学习各种图片读入和保存方法，分析对比其图像的格式

1.cv2打开和保存图片:分彩色和灰度图两种情况

(1)读入指令为cv2.imread('house.jpg')，cv2.imread('house.jpg',cv2.IMREAD_GRAYSCALE)

(2)读入图像为nd.array格式矩阵，注意颜色频道BGR的顺序，

(3)保存指令为cv2.imwrite('imgsavename.*',imgname)。

如果显示图像时做了BGR2RGB，则在保存前应该做RGB2BGR，否则存的图频道颠倒。

2.PIL打开和保存图片：

(1)打开文件指令为Image.open('house.jpg')，Image.open('house.jpg').convert('L')

(2)打开后图像格式为PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=280x200，

dtype为JPEG，mode为RGB；灰度图则分别为None和mode=L；

(3)需要使用nd.array()转换为array格式的矩阵，

(4)保存时再用Image.fromarray()转换回图像<PIL.Image.Image image mode=RGB size=280x200，

dtype为None

(5)保存指令为imgname.save('imgsavename.*')。

3.skimage打开和保存图片:分彩色和灰度图两种情况

(1)读入彩色图像指令为 io.imread('house.jpg')，

读入图片的数据格式为uint8，三通道RGB格式，与cv2同

(2)读入灰度图像指令为io.imread('house.jpg',as_grey=True),

读入图片的数据格式为float，数值在0到1之间

4.plt打开和保存图片:

(1)读入指令为plt.imread()，

(2)保存指令为plt.savefig('imgsavename.*'),且一定在plt.show()之前；

plt.savefig将当前窗口内的内容保存，包括白边(有无参数设置为不保存白边？)。

5.实验结果：

cv2 open and cvtBGR (shape,dtype):(200, 280, 3),uint8

ski open (shape,dtype):(200, 280, 3),uint8

plt open (shape,dtype):(200, 280, 3),uint8

pil open (size ,dtype):(280, 200),JPEG

pil open and pil2arr (shape,dtype):(200, 280, 3),uint8

pil open and arr2pil (size ,dtype):(280, 200),None

cv2 open and save (shape,dtype):(200, 280, 3),uint8

pil open and save (shape,dtype):(200, 280, 3),uint8

ski open and save (shape,dtype):(200, 280, 3),uint8

plt open and save (shape,dtype):(288, 432, 3),uint8

cv2 open gray (shape,dtype):(200, 280),uint8

pil open gray (size ,dtype):(280, 200),None

ski open gray (shape,dtype):(200, 280),float64

cv2 open and savegray(shape,dtype):(200, 280),uint8

pil open and savegray(shape,dtype):(200, 280),uint8

ski open and savegray(shape,dtype):(200, 280),uint8

总结：

(1)读入彩图cv2,plt,ski数据类型为uint8一致，均为三通道uint8（注意cv2是BGR）;

pil读入JPEG格式(mode=RGB)且shape不同，需要转换为ndarray(shape变化)，

保存时再转回图片，格式为None(shape变化)。

(2)读入灰度图仅对比了cv2,ski和pil，三者均不同，cv2为uint8，而ski为float64(0和1之间),

pil的format为None(mode=L),与彩色图同操作。

(3)保存图片，四种方法均为uint8,但是cv2，pil，ski保存原图shape不变

(注意cv2又存成BGR)，而plt保存窗口且shape改变。

'''

1.cv2打开图片，显示后，用cv2存储

'''

import cv2

import matplotlib.pyplot as plt

# cv2读入和保存彩色图

img_cv2BGR = cv2.imread('house.jpg')

img_cv2RGB = cv2.cvtColor(img_cv2BGR,cv2.COLOR_BGR2RGB)

cv2.imwrite('house_cv2write.jpg',img_cv2RGB) # 图像占内存略大于原图

img_cv2write = plt.imread('house_cv2write.jpg')

print(img_cv2BGR.dtype)

print(img_cv2BGR.size)

print(img_cv2BGR.shape)

print(img_cv2BGR)

# cv2读入和保存灰度图

imgray_cv2 = cv2.imread('house.jpg',cv2.IMREAD_GRAYSCALE)

cv2.imwrite('housegray_cv2write.jpg',imgray_cv2)

imgray_cv2write = plt.imread('housegray_cv2write.jpg')

print(imgray_cv2.dtype)

print(imgray_cv2.size)

print(imgray_cv2.shape)

print(imgray_cv2)

'''2.PIL保存'''

from PIL import Image

import numpy as np

# 用PIL读入和保存彩色图，并进行格式转换以用于不同目的

img_pil = Image.open('house.jpg') # img类，JPEG格式，mode=RGB

img_pil2arr = np.array(img_pil) # 转成ndarray

img_arr2pil = Image.fromarray(img_pil2arr) # 矩阵再转为图像

img_arr2pil.save('house_pilsave.jpg') # PIL保存图像

img_pilsave = plt.imread('house_pilsave.jpg')

print(img_pil.format) # JPEG; 'Image' object has no attribute 'shape' and 'dtype'

print(img_pil.size) # (280, 200)

print(img_pil) # <PIL.JpegImagePlugin.JpegImageFile image mode=RGB...

print(img_arr2pil.format)

print(img_arr2pil.size)

print(img_arr2pil)

# 用PIL读入和保存灰度图

imgray_pil = Image.open('house.jpg').convert('L') # L为灰度图，RGB为真彩色,RGBA为加了透明频道

imgray_pil.save('house_gray_pilsave.jpg')

print(imgray_pil.format) # None;format为None，mode为L，注意与彩色图不同

print(imgray_pil.size) # (280, 200)

print(imgray_pil) # <PIL.Image.Image image mode=L size=280x200 at...

imgray_pilsave = plt.imread('house_gray_pilsave.jpg')

'''

3.skimage保存:分彩色和灰度图两种情况

'''

from skimage import io

# ski读入彩色图

img_ski = io.imread('house.jpg')

io.imshow(img_ski) # io.imshow显示图像

io.imsave('house_skisave.jpg',img_ski) # io.save保存图像

img_skisave = plt.imread('house_skisave.jpg') # plt读入图像

print(img_ski.dtype)

print(img_ski.size)

print(img_ski.shape)

print(img_ski)

# ski读入灰度图

imgray_ski = io.imread('house.jpg',as_grey=True)

print(imgray_ski.dtype)

print(imgray_ski.size)

print(imgray_ski.shape)

print(imgray_ski)

io.imsave('house_gray_ski.jpg',imgray_ski)

imgray_skisave = plt.imread('house_gray_ski.jpg')

'''

4.plt.save:将当前窗口内的内容保存，包括白边

'''

import matplotlib.pyplot as plt

fig = plt.figure('house')

img_plt = plt.imread('house.jpg')

plt.imshow(img_plt)

plt.savefig('house_pltsave.jpg') # 一定在plt.show()之前

plt.show()

img_pltsave = plt.imread('house_pltsave.jpg')

'''

打印图片格式

'''

# 分类显示：方法结果对比

print("cv2 open and cvtBGR (shape,dtype):{},{}".format(img_cv2RGB.shape,img_cv2RGB.dtype))

print("cv2 open and save (shape,dtype):{},{}".format(img_cv2write.shape,img_cv2write.dtype))

print("cv2 open gray (shape,dtype):{},{}".format(imgray_cv2.shape,imgray_cv2.dtype))

print("cv2 open and savegray(shape,dtype):{},{}".format(imgray_cv2write.shape,imgray_cv2write.dtype))

print("pil open gray (size ,dtype):{},{}".format(imgray_pil.size,imgray_pil.format))

print("pil open and savegray(shape,dtype):{},{}".format(imgray_pilsave.shape,imgray_pilsave.dtype))

print("pil open (size ,dtype):{},{}".format(img_pil.size,img_pil.format))

print("pil open and pil2arr (shape,dtype):{},{}".format(img_pil2arr.shape,img_pil2arr.dtype))

print("pil open and arr2pil (size ,dtype):{},{}".format(img_arr2pil.size,img_arr2pil.format))

print("pil open and save (shape,dtype):{},{}".format(img_pilsave.shape,img_pilsave.dtype))

print("ski open (shape,dtype):{},{}".format(img_ski.shape,img_ski.dtype))

print("ski open and save (shape,dtype):{},{}".format(img_skisave.shape,img_skisave.dtype))

print("ski open gray (shape,dtype):{},{}".format(imgray_ski.shape,imgray_ski.dtype))

print("ski open and savegray(shape,dtype):{},{}".format(imgray_skisave.shape,imgray_skisave.dtype))

print("plt open (shape,dtype):{},{}".format(img_plt.shape,img_plt.dtype))

print("plt open and save (shape,dtype):{},{}".format(img_pltsave.shape,img_pltsave.dtype))

# 分类显示：相同操作结果对比