from keras.preprocessing.image import ImageDataGenerator from
keras.preprocessingimport image import matplotlib.pyplot as plt import numpy as
npimport pylab img_generator = ImageDataGenerator( rotation_range = 90,
width_shift_range= 0.2, height_shift_range = 0.2, zoom_range = 0.3 ) # Import and display pictures
img_path= 'G:\\100000.jpg' img = image.load_img(img_path) print(type(img)) #
plt.imshow(img)# pylab.show() #img.show() # Convert picture to array x = image.img_to_array(img)
# Expand a dimension x = np.expand_dims(x, axis=0) # Generate pictures gen = img_generator.flow(x,
batch_size=2) # Show generated pictures plt.figure() for i in range(1): for j in range(1):
x_batch= next(gen) print(type(x_batch),x_batch.shape) idx = (1*i) + j
plt.subplot(1, 1, idx+1) plt.imshow(x_batch[0]/255) pylab.show()