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Dockerfile

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+FROM python:3.10-slim
+
+WORKDIR /app
+
+COPY . /app
+
+RUN pip install --no-cache-dir -r requirements.txt
+
+EXPOSE 7860
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI, File, UploadFile
+from ultralytics import YOLO
+from huggingface_hub import hf_hub_download
+import io
+from PIL import Image
+
+app = FastAPI()
+
+# Download your YOLO model from your model repo
+model_path = hf_hub_download("devsdevline/soccer-homography-yolo", "best.pt")
+model = YOLO(model_path)
+
+@app.get("/")
+def root():
+    return {"status": "API running", "model": "soccer-homography-yolo"}
+
+@app.post("/predict")
+async def predict(file: UploadFile = File(...)):
+    # Read uploaded image
+    image = Image.open(io.BytesIO(await file.read())).convert("RGB")
+    results = model(image)
+
+    detections = []
+    for box in results[0].boxes:
+        detections.append({
+            "class_id": int(box.cls[0]),
+            "confidence": float(box.conf[0]),
+            "bbox": box.xyxy[0].tolist()
+        })
+
+    return {"detections": detections}