app.py

from fastapi import FastAPI, UploadFile, File
from fastapi.middleware.cors import CORSMiddleware
from PIL import Image
from io import BytesIO
import numpy as np
import tensorflow as tf

app = FastAPI()

# CORS config (optional)
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_methods=["*"],
    allow_headers=["*"],
)

@app.post("/predict")
async def predict(file: UploadFile = File(...)):
    contents = await file.read()
    img = Image.open(BytesIO(contents)).convert("RGB")
    img = img.resize((256, 256))  # or whatever your model expects
    arr = np.array(img) / 255.0
    arr = np.expand_dims(arr, 0)
    # prediction = model.predict(arr)
    # result = do_something_with_prediction(prediction)
    return {"success": True}