Open-vocabulary perception on a Jetson Orin: what's your pipeline?
Grounding DINO for boxes followed by SAM 2.1 for masks is a common language-driven pick-and-place front end.
Did you export to TensorRT or stay in PyTorch, and what end-to-end rate did you get?
Referenced repos
Indexed from Hugging Face and linked upstream, not hosted here.
Open-vocabulary detector that draws boxes around objects named in a free-text prompt, without a fixed class list.
Compact variant of Meta's promptable segmentation model that returns object masks from points or boxes and can track them across video frames.
CLIP-based zero-shot detector from Google that localizes objects from text queries or from an example image crop.