import os
from PIL import Image
import torch
import gradio as gr
os.system("pip install gradio==2.5.3")
import torch
torch.backends.cudnn.benchmark = True
from torchvision import transforms, utils
from util import *
from PIL import Image
import math
import random
import numpy as np
from torch import nn, autograd, optim
from torch.nn import functional as F
from tqdm import tqdm
import lpips
from model import *
from e4e_projection import projection as e4e_projection
from copy import deepcopy
import imageio
os.makedirs('inversion_codes', exist_ok=True)
os.makedirs('style_images', exist_ok=True)
os.makedirs('style_images_aligned', exist_ok=True)
os.makedirs('models', exist_ok=True)
os.system("wget http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2")
os.system("bzip2 -dk shape_predictor_68_face_landmarks.dat.bz2")
os.system("mv shape_predictor_68_face_landmarks.dat models/dlibshape_predictor_68_face_landmarks.dat")
device = 'cpu'
os.system("gdown https://drive.google.com/uc?id=1_cTsjqzD_X9DK3t3IZE53huKgnzj_btZ")
latent_dim = 512
original_generator = Generator(1024, latent_dim, 8, 2).to(device)
ckpt = torch.load('stylegan2-ffhq-config-f.pt', map_location=lambda storage, loc: storage)
original_generator.load_state_dict(ckpt["g_ema"], strict=False)
mean_latent = original_generator.mean_latent(10000)
generatorjojo = deepcopy(original_generator)
generatordisney = deepcopy(original_generator)
generatorjinx = deepcopy(original_generator)
generatorcaitlyn = deepcopy(original_generator)
generatoryasuho = deepcopy(original_generator)
generatorarcanemulti = deepcopy(original_generator)
generatorart = deepcopy(original_generator)
generatorspider = deepcopy(original_generator)
transform = transforms.Compose(
[
transforms.Resize((1024, 1024)),
transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),
]
)
os.system("gdown https://drive.google.com/uc?id=1jtCg8HQ6RlTmLdnbT2PfW1FJ2AYkWqsK")
os.system("cp e4e_ffhq_encode.pt models/e4e_ffhq_encode.pt")
os.system("gdown https://drive.google.com/uc?id=1ZRwYLRytCEKi__eT2Zxv1IlV6BGVQ_K2")
ckptjojo = torch.load('jojo_preserve_color.pt', map_location=lambda storage, loc: storage)
generatorjojo.load_state_dict(ckptjojo["g"], strict=False)
os.system("gdown https://drive.google.com/uc?id=1Bnh02DjfvN_Wm8c4JdOiNV4q9J7Z_tsi")
ckptdisney = torch.load('disney_preserve_color.pt', map_location=lambda storage, loc: storage)
generatordisney.load_state_dict(ckptdisney["g"], strict=False)
os.system("gdown https://drive.google.com/uc?id=1jElwHxaYPod5Itdy18izJk49K1nl4ney")
ckptjinx = torch.load('arcane_jinx_preserve_color.pt', map_location=lambda storage, loc: storage)
generatorjinx.load_state_dict(ckptjinx["g"], strict=False)
os.system("gdown https://drive.google.com/uc?id=1cUTyjU-q98P75a8THCaO545RTwpVV-aH")
ckptcaitlyn = torch.load('arcane_caitlyn_preserve_color.pt', map_location=lambda storage, loc: storage)
generatorcaitlyn.load_state_dict(ckptcaitlyn["g"], strict=False)
os.system("gdown https://drive.google.com/uc?id=1SKBu1h0iRNyeKBnya_3BBmLr4pkPeg_L")
ckptyasuho = torch.load('jojo_yasuho_preserve_color.pt', map_location=lambda storage, loc: storage)
generatoryasuho.load_state_dict(ckptyasuho["g"], strict=False)
os.system("gdown https://drive.google.com/uc?id=1enJgrC08NpWpx2XGBmLt1laimjpGCyfl")
ckptarcanemulti = torch.load('arcane_multi_preserve_color.pt', map_location=lambda storage, loc: storage)
generatorarcanemulti.load_state_dict(ckptarcanemulti["g"], strict=False)
os.system("gdown https://drive.google.com/uc?id=1a0QDEHwXQ6hE_FcYEyNMuv5r5UnRQLKT")
ckptart = torch.load('art.pt', map_location=lambda storage, loc: storage)
generatorart.load_state_dict(ckptart["g"], strict=False)
os.system("wget https://huggingface.co/akhaliq/jojo-gan-spiderverse/blob/main/spiderverse-checkpoint-3-face-500iters.pt")
ckptspider = torch.load('spiderverse-checkpoint-3-face-500iters.pt', map_location=lambda storage, loc: storage)
generatorspider.load_state_dict(ckptspider["g"], strict=False)
def inference(img, model):
aligned_face = align_face(img)
my_w = e4e_projection(aligned_face, "test.pt", device).unsqueeze(0)
if model == 'JoJo':
with torch.no_grad():
my_sample = generatorjojo(my_w, input_is_latent=True)
elif model == 'Disney':
with torch.no_grad():
my_sample = generatordisney(my_w, input_is_latent=True)
elif model == 'Jinx':
with torch.no_grad():
my_sample = generatorjinx(my_w, input_is_latent=True)
elif model == 'Caitlyn':
with torch.no_grad():
my_sample = generatorcaitlyn(my_w, input_is_latent=True)
elif model == 'Yasuho':
with torch.no_grad():
my_sample = generatoryasuho(my_w, input_is_latent=True)
elif model == 'Arcane Multi':
with torch.no_grad():
my_sample = generatorarcanemulti(my_w, input_is_latent=True)
elif model == 'Art':
with torch.no_grad():
my_sample = generatorart(my_w, input_is_latent=True)
else:
with torch.no_grad():
my_sample = generatorspider(my_w, input_is_latent=True)
npimage = my_sample[0].permute(1, 2, 0).detach().numpy()
imageio.imwrite('filename.jpeg', npimage)
return 'filename.jpeg'
title = "JoJoGAN"
description = "Gradio Demo for JoJoGAN: One Shot Face Stylization. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
article = "JoJoGAN: One Shot Face Stylization| Github Repo Pytorch
samples from repo: 
"
examples=[['iu.jpeg','Jinx']]
gr.Interface(inference, [gr.inputs.Image(type="filepath"),gr.inputs.Dropdown(choices=['JoJo', 'Disney','Jinx','Caitlyn','Yasuho','Arcane Multi','Art'], type="value", default='JoJo', label="Model")], gr.outputs.Image(type="file"),title=title,description=description,article=article,enable_queue=True,allow_flagging=False,examples=examples).launch()