Great question! I work for a computer vision company (Roboflow) and have seen computer vision used for everything from accident prevention on critical infrastru

Great question! I work for a computer vision company (Roboflow) and have seen computer vision used for everything from accident prevention on critical infrastructure to identifying defects on vehicle parts to detecting trading cards for use in video game applications. Drawing bounding boxes is a common end point for demos, but for businesses using computer vision there is an entire world after that: on device deployment. This can be on devices like an NVIDIA Jetson (a very common choice), to Raspberry Pis to central CUDA GPU servers for processing large volumes of data (maybe connected to cameras over RTSP). Note: There are many models that are faster and perform better than YOLOv5 (i.e. YOLOv8, YOLOv10, PaliGemma). Roboflow Inference that our ML team maintains has various guides on deploying models to the edge: https://inference.roboflow.com/#inference-pipeline https://inference.roboflow.com/#inference-pipeline