import gradio as gr
import numpy as np
import torch
from torch import nn
import imageio
import cv2


class Generator(nn.Module):
    # Refer to the link below for explanations about nc, nz, and ngf
    # https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html#inputs
    def __init__(self, nc=4, nz=100, ngf=64):
        super(Generator, self).__init__()
        self.network = nn.Sequential(
            nn.ConvTranspose2d(nz, ngf * 4, 3, 1, 0, bias=False),
            nn.BatchNorm2d(ngf * 4),
            nn.ReLU(True),
            nn.ConvTranspose2d(ngf * 4, ngf * 2, 3, 2, 1, bias=False),
            nn.BatchNorm2d(ngf * 2),
            nn.ReLU(True),
            nn.ConvTranspose2d(ngf * 2, ngf, 4, 2, 0, bias=False),
            nn.BatchNorm2d(ngf),
            nn.ReLU(True),
            nn.ConvTranspose2d(ngf, nc, 4, 2, 1, bias=False),
            nn.Tanh(),
        )

    def forward(self, input):
        output = self.network(input)
        return output


def display_gif(file_name, save_name):
    images = []

    for frame in range(8):
        frame_name = '%d' % (frame)
        image_filename = file_name + frame_name + '.png'
        images.append(imageio.imread(image_filename))

    gif_filename = 'avatar_source.gif'
    return imageio.mimsave(gif_filename, images)


def display_gif_pad(file_name, save_name):
    images = []

    for frame in range(8):
        frame_name = '%d' % (frame)
        image_filename = file_name + frame_name + '.png'
        image = imageio.imread(image_filename)
        image = image[:, :, :3]
        image_pad = cv2.copyMakeBorder(image, 0, 0, 125, 125, cv2.BORDER_CONSTANT, value=0)
        images.append(image_pad)

    return imageio.mimsave(save_name, images)
    

def display_image(file_name):

    image_filename = file_name + '0' + '.png'
    print(image_filename)
    image = imageio.imread(image_filename)
    imageio.imwrite('image.png', image)
    

def run(domain_source, action_source, hair_source, top_source, bottom_source, domain_target, action_target, hair_target, top_target, bottom_target):

    # == Source Avatar ==
    # body
    body_source = '0'
    
    # hair
    if hair_source == "green": hair_source = '0'
    elif hair_source == "yellow": hair_source = '2'
    elif hair_source == "rose": hair_source = '4'
    elif hair_source == "red": hair_source = '7'
    elif hair_source == "wine": hair_source = '8'
    
    # top
    if top_source == "brown": top_source = '0'
    elif top_source == "blue": top_source = '1'
    elif top_source == "white": top_source = '2'
    
    # bottom
    if bottom_source == "white": bottom_source = '0'
    elif bottom_source == "golden": bottom_source = '1'
    elif bottom_source == "red": bottom_source = '2'
    elif bottom_source == "silver": bottom_source = '3'
    
    file_name_source = './Sprite/frames/domain_1/' + action_source + '/'
    file_name_source = file_name_source + 'front' + '_' + str(body_source) + str(bottom_source) + str(top_source) + str(hair_source) + '_'
    
    gif = display_gif_pad(file_name_source, 'avatar_source.gif')
    
    # == Target Avatar ==
    # body
    body_target = '1'
    
    # hair
    if hair_target == "violet": hair_target = '1'
    elif hair_target == "silver": hair_target = '3'
    elif hair_target == "purple": hair_target = '5'
    elif hair_target == "grey": hair_target = '6'
    elif hair_target == "golden": hair_target = '9'
    
    # top
    if top_target == "grey": top_target = '3'
    elif top_target == "khaki": top_target = '4'
    elif top_target == "linen": top_target = '5'
    elif top_target == "ocre": top_target = '6'
    
    # bottom
    if bottom_target == "denim": bottom_target = '4'
    elif bottom_target == "olive": bottom_target = '5'
    elif bottom_target == "brown": bottom_target = '6'
    
    file_name_target = './Sprite/frames/domain_2/' + action_target + '/'
    file_name_target = file_name_target + 'front' + '_' + str(body_target) + str(bottom_target) + str(top_target) + str(hair_target) + '_'
    
    gif_target = display_gif_pad(file_name_target, 'avatar_target.gif')
    
    return 'demo.gif'


gr.Interface(
    run,
    inputs=[
        gr.Textbox(value="Source Avatar - Human", interactive=False),
        gr.Radio(choices=["slash", "spellcard", "walk"], value="slash"),
        gr.Radio(choices=["green", "yellow", "rose", "red", "wine"], value="green"),
        gr.Radio(choices=["brown", "blue", "white"], value="brown"),
        gr.Radio(choices=["white", "golden", "red", "silver"], value="white"),
        gr.Textbox(value="Target Avatar - Alien", interactive=False),
        gr.Radio(choices=["slash", "spellcard", "walk"], value="walk"),
        gr.Radio(choices=["violet", "silver", "purple", "grey", "golden"], value="golden"),
        gr.Radio(choices=["grey", "khaki", "linen", "ocre"], value="ocre"),
        gr.Radio(choices=["denim", "olive", "brown"], value="brown"),
    ],
    outputs=[
        gr.components.Image(type="file", label="Domain Disentanglement"),
    ],
    live=True,
    title="TransferVAE for Unsupervised Video Domain Adaptation",
).launch()