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| from fastapi import FastAPI, File, UploadFile,Form | |
| from fastapi.responses import FileResponse, StreamingResponse | |
| from fastapi.staticfiles import StaticFiles | |
| from fastapi import FastAPI, File, UploadFile | |
| from pydantic import BaseModel | |
| import numpy as np | |
| import cv2 | |
| import torch | |
| from vtoonify_model import Model | |
| import shutil | |
| import os | |
| app = FastAPI() | |
| model = Model(device='cuda' if torch.cuda.is_available() else 'cpu') | |
| async def upload_image(file: UploadFile = File(...), top: int = Form(...), bottom: int = Form(...), left: int = Form(...), right: int = Form(...)): | |
| try: | |
| with open("temp.jpg", "wb") as buffer: | |
| shutil.copyfileobj(file.file, buffer) | |
| # Perform image processing using the model | |
| result_image, _, _ = model.detect_and_align_image("temp.jpg", top, bottom, left, right) | |
| # Save the result image temporarily | |
| result_path = "result.jpg" | |
| cv2.imwrite(result_path, result_image) | |
| # Return the result image | |
| with open(result_path, "rb") as result_buffer: | |
| result_image_bytes = result_buffer.read() | |
| # Remove temporary files | |
| os.remove("temp.jpg") | |
| os.remove(result_path) | |
| return {"result_image": result_image_bytes} | |
| except Exception as e: | |
| return {"error": str(e)} | |
| app.mount("/", StaticFiles(directory="AB", html=True), name="static") | |
| def index() -> FileResponse: | |
| return FileResponse(path="/app/AB/index.html", media_type="text/html") | |