TorchServe Deployment for Real-time Inference

Configure and prepare your trained hazard detection model for deployment using `TorchServe`. Create a model archive (.mar file) and any necessary custom handlers to ensure efficient, low-latency inference. Your `TorchServe` deployment should be capable of accepting incoming sensor data (e.g., fused terrain maps or raw sensor frames) and outputting hazard detections or a processed hazard map in real-time. Provide instructions or a Dockerfile for setting up the TorchServe environment.