First commit

Dockerfile

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+FROM python:3.11-slim
+
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y \
+    libgl1 \
+    libglib2.0-0 \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI, UploadFile, File
+from PIL import Image
+from ultralytics import YOLO
+import io
+
+app = FastAPI()
+
+# Loading model
+model = YOLO("best.pt")
+print("Model classes :", model.names)
+
+# Health check
+@app.get("/")
+def home():
+    return {"status": "ok", "classes": model.names}
+
+@app.post("/predict")
+def predict(file: UploadFile = File(...)):
+    image = Image.open(io.BytesIO(file.file.read())).convert("RGB")
+
+    results = model.predict(image)[0]
+
+    detections = []
+    # For each bounding box, 3 pieces of information are extracted
+    for box in results.boxes:
+        detections.append({
+            # converte 0 and 1 into fire or smoke
+            "classe": model.names[int(box.cls)],
+            # confidence score
+            "confidence": float(box.conf),
+            # bbox coordinates
+            "bbox": box.xyxy[0].tolist(),
+        })
+
+    return {"detections": detections}

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:148ea5e757aabe4043582981eb24a1f6ed02d4ed3b8379c8a1bd876646e1476c
+size 40480492

requirements.txt

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+fastapi
+uvicorn[standard]
+ultralytics   # package which contains Yolo
+python-multipart  # allows Fast AFPI to receive uploaded files
+pillow  # For manipulate images