python读取图片的几种方式

opencv的像素值在[0,1][0,1]，show的时候转换到[0,255]

import cv2
img = cv2.imread("imgfile")
cv2.imshow("img_win_name", img)
cv2.waitKey(0)  # 无限期等待输入

cv2.imwrite("write_file_name", img)
  
  

  
  

   
   
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注意，opencv打开图片的格式为：

height×width×channelsheight×width×channels

。
分离方法为:

b, g, r = cv2.split(img)
  
  

  
  

   
   
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2. scikit-image包

scikit-image的像素值在[−1,1][−1,1]，show的时候转换到[0,255]

import skimage.io as io
import matplotlib.pyplot as plt

img = io.imread("a.jpg")
io.imshow(img)
plt.show()
  
  

  
  

   
   
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注意skimage读取图片也是height×width×channelsheight×width×channels

3. matplotlib包

matplotlib的像素值在[-1,1]之间，存储的时候转换到[0,255][0,255]，show的时候转换到[0,255]

import matplotlib.pyplot as plt

img = plt.imread("img_name")
plt.imshow(img)
  
  

  
  

   
   
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matplotlib读取图片也是height×widht×channelsheight×widht×channels

4. tifffile包

import tifffile as tiff

# 将图片的像素值放缩到[0,1]之间
def scale_percentile(matrix):
    w, h, d = matrix.shape
    matrix = np.reshape(matrix, [w * h, d]).astype(np.float64)
    # Get 2nd and 98th percentile
    mins = np.percentile(matrix, 1, axis=0)
    maxs = np.percentile(matrix, 99, axis=0) - mins
    matrix = (matrix - mins[None, :]) / maxs[None, :]
    matrix = np.reshape(matrix, [w, h, d])
    matrix = matrix.clip(0, 1)
    return matrix

img = tiff.imread("file_name")
tiff.imshow(scale_percentile(img))
  
  

  
  

   
   
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注意tifffile的图片的读取顺序height×width×channelsheight×width×channels按照波段来获取。