roboflow / roboflow/supervision
feature - calculation of involuntary attention zones
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 50.9k
- Forks
- 4.8k
- Avg merge
- 1d 12h
- Merged PRs (30d)
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Description
Search before asking
- I have searched the Supervision issues and found no similar feature requests.
Description
if you want an idea about how to use this as a new and good feature, then for a forecast, add a direction vector for each car, see the intersections between the vectors, see how the dispersion of the intersections evolves and you will have the areas where drivers tend to steer the car involuntarily.
Use case
These areas can be used to highlight traffic signs or advertisements
Additional
No response
Are you willing to submit a PR?
- Yes I'd like to help by submitting a PR!
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry points. Start by surveying the repository's existing tracking and video-processing APIs, then determine where trajectory data could be extended. Done would require a defined method for car direction vectors, vector intersections, dispersion over time, and the resulting attention zones, with tests or examples for the behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100