# convert to numpy array data = img_to_array(img) # expand dimension to one sample samples = expand_dims(data, 0) # create image data augmentation generator datagen = ImageDataGenerator(rotation_range = 40, brightness_range=[0.2, 0.7], width_shift_range = 0.2, height_shift_range = 0.2, zoom_range = 0.2, horizontal_flip = True) # prepare iterator it = datagen.flow(samples, batch_size=1) plt.figure(figsize=(12, 8)) # generate samples and plot for i in range(20): # define subplot pyplot.subplot(4 , 5 , i+1) # generate batch of images batch = it.next() # convert to unsigned integers for viewing image = batch[0].astype('uint8') # plot raw pixel data pyplot.axis('off') # plt.tight_layout(2) pyplot.imshow(image) # show the figure plt.tight_layout(2) fig1 = plt.gcf() plt.show() plt.draw() fig1.savefig('tessstttyyy.png', dpi=100)