I am undertaking a multi-company project to create a UAV prototype for surveillance and security of a restricted area and visual inspection of telecommunications infrastructures. My role in the project is to develop the AI component for intrusion detection and the visual analysis of infrastructures.
I decided to use your NVIDIA Jetson Orin Nano Developer Kit. I was studying/researching possible intrusion detection algorithms when I discovered that you have NanoOWL and PeopleNet. However, I wasn’t sure of the differences between them. Can anyone explain the differences between the two? How could I then train the algorithms? Do you also have software to adapt the code to my project/objectives?
PeopleNet is a model that is specialized in detecting people. If you need to detect people only, it is likely the better choice.
NanoOWL is an “Open-Vocabulary” object detection model, that detects objects based on generic prompts like (“a chair”, “a dog”, “a hat”, etc.). This may be a good starting point if you don’t have a model for your specialized task, or have multiple classes of interest.