app.py

from fastapi import FastAPI, File, UploadFile
from fastapi.responses import JSONResponse
from PIL import Image
import io
from ultralytics import YOLO

app = FastAPI()
model = YOLO("best.pt")  # Ensure this file is in your project folder

@app.post("/detect")
async def detect(file: UploadFile = File(...)):
    contents = await file.read()
    image = Image.open(io.BytesIO(contents)).convert("RGB")
    results = model(image)

    detections = []
    for r in results:
        for box in r.boxes:
            cls_id = int(box.cls)
            conf = float(box.conf)
            label = model.names[cls_id]
            x1, y1, x2, y2 = box.xyxy[0]
            detections.append({
                "label": label,
                "confidence": round(conf, 2),
                "box": [
                    round(float(x1), 2),
                    round(float(y1), 2),
                    round(float(x2 - x1), 2),
                    round(float(y2 - y1), 2)
                ]
            })

    return JSONResponse(content={"detections": detections})