Hi OpenCV Zoo maintainers,
URML (urml.dev) is a small, Apache-2.0 language for robot intent: an intent becomes a typed primitive, validated against the robot's declared capabilities and a safety envelope, then dispatched. opencv_zoo collects edge-deployable models for OpenCV DNN, and for the robotics subset of users, a zoo model's output is exactly the kind of perception fact a URML intent conditions on. This is a narrowly-scoped consume-the-estimate note about that robotics slice, not a claim on the whole project.
Nothing here asks the project to adopt, host, or maintain anything. This is a request for comment.
The boundary: for a robot running an opencv_zoo model on-device, the model's output (a detection, a pose, a segmentation) is a fact a typed URML intent conditions on, validated against the robot's capabilities and a safety envelope before dispatch. The zoo stays the model source and OpenCV DNN stays the runtime; URML stays out of perception. What a given zoo model outputs (its classes, keypoints) maps toward the perception side of a URML manifest, so an intent that needs an output the chosen model does not provide can be caught early.
Two real questions: (1) for robots using opencv_zoo models on-device, is "the zoo model produces the estimate, URML consumes it as a fact an intent conditions on" a sensible boundary? (2) Does a zoo model's output schema map cleanly toward the perception side of a URML manifest?
Full write-up: https://github.com/URML-MARS/URML/blob/main/docs/rfcs/0614-opencv-zoo-outreach.md
Thanks for the zoo; edge-deployable models are exactly what a lot of robots run for perception, and a clean line to the intent that uses them seemed worth raising for that subset.
Ido Yahalomi (URML, greenvh@gmail.com)
AI-assisted prose, maintainer-reviewed before posting (see https://github.com/URML-MARS/URML/blob/main/VIBE.md). Human-only correspondence available on request.
Hi OpenCV Zoo maintainers,
URML (urml.dev) is a small, Apache-2.0 language for robot intent: an intent becomes a typed primitive, validated against the robot's declared capabilities and a safety envelope, then dispatched. opencv_zoo collects edge-deployable models for OpenCV DNN, and for the robotics subset of users, a zoo model's output is exactly the kind of perception fact a URML intent conditions on. This is a narrowly-scoped consume-the-estimate note about that robotics slice, not a claim on the whole project.
Nothing here asks the project to adopt, host, or maintain anything. This is a request for comment.
The boundary: for a robot running an opencv_zoo model on-device, the model's output (a detection, a pose, a segmentation) is a fact a typed URML intent conditions on, validated against the robot's capabilities and a safety envelope before dispatch. The zoo stays the model source and OpenCV DNN stays the runtime; URML stays out of perception. What a given zoo model outputs (its classes, keypoints) maps toward the perception side of a URML manifest, so an intent that needs an output the chosen model does not provide can be caught early.
Two real questions: (1) for robots using opencv_zoo models on-device, is "the zoo model produces the estimate, URML consumes it as a fact an intent conditions on" a sensible boundary? (2) Does a zoo model's output schema map cleanly toward the perception side of a URML manifest?
Full write-up: https://github.com/URML-MARS/URML/blob/main/docs/rfcs/0614-opencv-zoo-outreach.md
Thanks for the zoo; edge-deployable models are exactly what a lot of robots run for perception, and a clean line to the intent that uses them seemed worth raising for that subset.
Ido Yahalomi (URML, greenvh@gmail.com)
AI-assisted prose, maintainer-reviewed before posting (see https://github.com/URML-MARS/URML/blob/main/VIBE.md). Human-only correspondence available on request.