feat: init fastapi

app.py

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+from fastapi import FastAPI, UploadFile, status
+from fastapi.responses import StreamingResponse, JSONResponse
+from ultralytics import YOLO
+import cv2
+import numpy as np
+from io import BytesIO
+from fastapi.middleware.cors import CORSMiddleware
+app = FastAPI()
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["POST"],
+    allow_headers=["content-type", "accept"],
+)
+
+model = YOLO("best.pt")
+
+@app.post("/inference")
+async def inference(file: UploadFile):
+    if file.content_type != "image/jpeg" and file.content_type != "image/png" and file.content_type != "image/jpg":
+        return JSONResponse(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            content={"error": "Invalid file format"}
+        )
+    image_bytes = await file.read()
+    img = np.frombuffer(image_bytes, dtype=np.uint8)
+    img = cv2.imdecode(img, cv2.IMREAD_COLOR)
+    results = model.predict(source=img, conf=0.5)
+    for r in results: 
+        boxes = r.boxes
+    for box in boxes: 
+        x1, y1, x2, y2 = box.xyxy[0]
+        x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)
+    
+        cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 255), 2)
+
+        label = box.cls[0].item()  
+        label_name = model.names[label]  
+        (text_width, text_height), baseline = cv2.getTextSize(label_name, cv2.FONT_HERSHEY_SIMPLEX, 0.9, 2)
+        cv2.rectangle(img, (x1, y1 - text_height - baseline - 5), (x1 + text_width, y1), (255, 0, 255), -1)
+        cv2.putText(img, label_name, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 0), 2)
+    
+    resp_img_bytes = cv2.imencode('.jpg', img)[1].tobytes()
+    resp_filename = f"inferenced_{file.filename}" if file.filename else "inferenced_image.jpg"
+    return StreamingResponse(BytesIO(resp_img_bytes), media_type="image/jpg", headers={"Content-Disposition": f"attachment; filename={resp_filename}"})

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9e3e7ca8fa30f286ae485a1b568de3c68d71ea3113b54fb20caecdd9e42377ba
+size 22504803

dockerfile

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+FROM python:3.10-slim
+
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+WORKDIR /app
+
+COPY --chown=user . .
+RUN pip install --no-cache-dir -r requirements.txt
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

requirements.txt

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+fastapi==0.116.1
+numpy==2.2.6
+opencv-python==4.12.0.88
+python-multipart==0.0.20
+ultralytics==8.3.193
+ultralytics-thop==2.0.17
+uvicorn==0.35.0