使用tensorflow将图片灰度化以及遇到的坑解决

import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
from keras_preprocessing.image import load_img,img_to_array
%matplotlib inline
 
 
image_name = 'cat1.jpg'
image = load_img(image_name)
#将图片转换为数组
image = img_to_array(image)
#转为黑白
image = tf.image.rgb_to_grayscale(image)
image = tf.squeeze(image,2)
plt.imshow(image)

#坑一、不将image转换为数组，直接用rgb_to_grayscale方法，将图片转为灰度图片
image_name = 'cat1.jpg'
image = load_img(image_name)
#转为黑白
image = tf.image.rgb_to_grayscale(image)

#坑二：最后图片无法显示
image_name = 'cat1.jpg'
image = load_img(image_name)
#将图片转换为数组
image = img_to_array(image)
#转为黑白
image = tf.image.rgb_to_grayscale(image)
plt.imshow(image)

image_name = 'cat1.jpg'
image = load_img(image_name)
plt.imshow(image)
#将图片转换为数组
image = img_to_array(image)
image = image.astype(dtype='uint8')
#转为黑白
image = tf.image.rgb_to_grayscale(image)
#降维
image = tf.squeeze(image,2)
plt.imshow(image)