Image Classification - Image Augmentation Methods

Common Image Enhancement Methods

tf.image for image enhancement

Offline implementation

import tensorflow as tf
import matplotlib.pyplot as plt
import numpy as np

cat=plt.imread('./cat.jpg')
plt.imshow(cat)

flip and crop

#左右翻转
cat1=tf.image.random_flip_left_right(cat)
plt.imshow(cat1)

#上下翻转
cat2=tf.image.random_flip_up_down(cat)
plt.imshow(cat2)

#裁切
cat3=tf.image.random_crop(cat,(200,200,3))
plt.imshow(cat3)

color change

#亮度调整
cat4=tf.image.random_brightness(cat,0.5)
plt.imshow(cat4)

#颜色色调
cat5=tf.image.random_hue(cat,0.5)
plt.imshow(cat5)

Use ImageDataGenerator (for image enhancement)

Realize online

for x,y in datagen.flow(x_train,y_train,batch_size=9):
    plt.figure(figsize=(8,8))
    for i in range(0,9):
        plt.subplot(330+1+i)
        plt.imshow(x[i].reshape(28,28),cmap='gray')
        plt.title(y[i])
    plt.show()
    break