import os
from PIL import Image
import gradio as gr
from torchvision import transforms
import easydict
import torch
import numpy as np
import model_build


psp = model_build.build_psp()
stylegan2 = model_build.build_stylegan2()

pretransform = transforms.Compose([
    transforms.Resize((256, 256)),
    transforms.ToTensor(),
    transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])])
    
def pipeline(img):
    img = model_build.img_preprocess(img, pretransform)
    with torch.no_grad():
        _, latent_space = psp(img.float(), randomize_noise=True, resize=False, return_latents=True)
    img = stylegan2(latent_space, noise_mode='none')
    img = Image.fromarray(np.array((img.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(torch.uint8).squeeze(0)[20:-20,:,:]))
    img.save('output.png')
    return 'output.png'
    
examples=[['momoi_out.png',False], ['churuki_out.png', False], ['fgfgfggf.png', False], ['dsfd.png', False]]
description="The male image doesn't work well. 1:1 ratio image recommended (square cropable after uploading). If the background is not monochromatic, it can be mixed with hair color. It takes an average of 5 seconds, but it can take longer if there is a lot of traffic. 남성 이미지에는 잘 작동하지 않음. 1:1비율 권장(업로드 후 정사각형 자르기 가능), 배경이 단색이 아니면 머리색과 섞일 수 있음. 트래픽이 많으면 5초 이상 걸릴 수 있음. Email:krkmfn@gmail.com"
gr.Interface(pipeline, [gr.inputs.Image(type="pil")], gr.outputs.Image(type="file"),description=description,allow_flagging=False,examples=examples,allow_screenshot=False,enable_queue=False).launch()