import cv2
import numpy as np
# 使用numpy方式创建一个二维数组
img = np.ones((100,100))
# 转换成int8类型
img = np.int8(img)
# 颜色空间转换，单通道转换成多通道， 可选可不选
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
cv2.imwrite("demo.jpg", img)

import numpy as np
import cv2
from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img
from PIL import Image
import skimage.io as io
import matplotlib.pyplot as plt
import matplotlib.image as mpig 
 
'''
方式：   返回类型
OpenCV   np.ndarray
PIL    PIL.JpegImagePlugin.JpegImageFile
keras.preprocessing.image PIL.JpegImagePlugin.JpegImageFile
Skimage.io   np.ndarray
matplotlib.pyplot  np.ndarray
matplotlib.image  np.ndarray
'''
 
imagePath="E:/DataSet/test1/trainSet/bus/300.jpg" 
 
'''
方式一：使用OpenCV
'''
img1=cv2.imread(imagePath)
print("img1:",img1.shape)
print("img1:",type(img1))
print("-"*10)
 
'''
方式二：使用PIL
'''
img2=Image.open(imagePath)
print("img2:",img2)
print("img2:",type(img2))
#转换成np.ndarray格式
img2=np.array(img2)
print("img2:",img2.shape)
print("img2:",type(img2))
print("-"*10) 
 
'''
方式三：使用keras.preprocessing.image
'''
img3=load_img(imagePath)
print("img3:",img3)
print("img3:",type(img3))
#转换成np.ndarray格式,使用np.array(),或者使用keras里的img_to_array()
#使用np.array()
#img3=np.array(img2)
#使用keras里的img_to_array()
img3=img_to_array(img3)
print("img3:",img3.shape)
print("img3:",type(img3))
print("-"*10) 
 
'''
方式四：使用Skimage.io
'''
img4=io.imread(imagePath)
print("img4:",img4.shape)
print("img4:",type(img4))
print("-"*10) 
 
'''
方式五：使用matplotlib.pyplot
'''
img5=plt.imread(imagePath)
print("img5:",img5.shape)
print("img5:",type(img5))
print("-"*10) 
 
'''
方式六：使用matplotlib.image
'''
img6=mpig.imread(imagePath)
print("img6:",img6.shape)
print("img6:",type(img6))
print("-"*10)

Using TensorFlow backend.
img1: (256, 384, 3)
img1: <class 'numpy.ndarray'>
----------
img2: <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=384x256 at 0x249608A8C50>
img2: <class 'PIL.JpegImagePlugin.JpegImageFile'>
img2: (256, 384, 3)
img2: <class 'numpy.ndarray'>
----------
img3: <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=384x256 at 0x2496B5A23C8>
img3: <class 'PIL.JpegImagePlugin.JpegImageFile'>
img3: (256, 384, 3)
img3: <class 'numpy.ndarray'>
----------
img4: (256, 384, 3)
img4: <class 'numpy.ndarray'>
----------
img5: (256, 384, 3)
img5: <class 'numpy.ndarray'>
----------
img6: (256, 384, 3)
img6: <class 'numpy.ndarray'>
----------