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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}
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