visualize.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jan 15 23:10:10 2019

@author: vijay
"""


import torchvision.utils as vutils
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from IPython.display import HTML
import image_loader as il


def lossvstrain(G_losses, D_losses):
    plt.figure(figsize=(10,5))
    plt.title("Generator and Discriminator Loss During Training")
    plt.plot(G_losses,label="G")
    plt.plot(D_losses,label="D")
    plt.xlabel("iterations")
    plt.ylabel("Loss")
    plt.legend()
    plt.show()

def generatorprogress(img_list):
    fig = plt.figure(figsize=(8,8))
    plt.axis("off")
    ims = [[plt.imshow(np.transpose(i,(1,2,0)), animated=True)] for i in img_list]
    ani = animation.ArtistAnimation(fig, ims, interval=100, repeat_delay=100, blit=True)
    
    HTML(ani.to_jshtml())


def realvfake(device, img_list):
    # Grab a batch of real images from the dataloader
    real_batch = next(iter(il.dataloader))

    # Plot the real images
    plt.figure(figsize=(15,15))
    plt.subplot(1,2,1)
    plt.axis("off")
    plt.title("Real Images")
    plt.imshow(np.transpose(vutils.make_grid(real_batch[0].to(device)[:64], padding=5, normalize=True).cpu(),(1,2,0)))

    # Plot the fake images from the last epoch
    plt.subplot(1,2,2)
    plt.axis("off")
    plt.title("Fake Images")
    plt.imshow(np.transpose(img_list[-1],(1,2,0)))
    plt.show()