from __future__ import annotations
from fastapi import FastAPI, File, UploadFile
from fastapi.responses import FileResponse
from fastapi.staticfiles import StaticFiles
import shutil
import torch
import numpy as np

from vtoonify_model import Model

app = FastAPI()
model = Model(device='cuda' if torch.cuda.is_available() else 'cpu')

@app.post("/upload/")
async def process_image(file: UploadFile = File(...)):
    # Save the uploaded image locally
    with open("uploaded_image.jpg", "wb") as buffer:
        shutil.copyfileobj(file.file, buffer)

    # Load the model (assuming 'cartoon1' is always used)
    exstyle, load_info = model.load_model('cartoon1')

    # Process the uploaded image
    top, bottom, left, right = 200, 200, 200, 200  
    aligned_face, _, input_info = model.detect_and_align_image("uploaded_image.jpg", top, bottom, left, right)
    processed_image, message = model.image_toonify(aligned_face, exstyle, style_degree=0.5, style_type='cartoon1')

    # Save the processed image
    with open("result_image.jpg", "wb") as result_buffer:
        result_buffer.write(processed_image)

    # Return the processed image
    return FileResponse("result_image.jpg", media_type="image/jpeg", headers={"Content-Disposition": "attachment; filename=result_image.jpg"})

app.mount("/", StaticFiles(directory="AB", html=True), name="static")

@app.get("/")
def index() -> FileResponse:
    return FileResponse(path="/app/AB/index.html", media_type="text/html")