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