Python Deep Learning Projects

Plotting the training – part 1

During each epoch, the following function plots 9 generated images. For comparison, it will also plot the corresponding 9 original target images and 9 noised input images. We need to use the upscale function we've defined when plotting to make sure the images are scaled to range between 0 and 255, so that you do not encounter issues when plotting:

def generated_images_plot(original, noised_data, generator):        print('NOISED')    for i in range(9):        plt.subplot(331 + i)        plt.axis('off')        plt.imshow(upscale(np.squeeze(noised_data[i])), cmap='gray') # upscale for plotting    plt.show()        print('GENERATED')    for i in range(9):        pred = generator.predict(noised_data[i:i+1], verbose=0)        plt.subplot(331 + i)        plt.axis('off') plt.imshow(upscale(np.squeeze(pred[0])), ...