Filter out persons with all NaN keypoints during personAssication#210
Merged
davidpagnon merged 1 commit intoperfanalytics:mainfrom Jan 10, 2026
Conversation
Update person_combinations() to exclude entries with all NaN pose_keypoints_2d, preventing unnecessary combinations.
Collaborator
|
The single-person mode will be removed soon (you will be asked whether you want 1, 2, more, or all detected people), but in the meantime, this looks good to me! |
Contributor
Author
|
Great improvement for usability. |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
In some cases, poseEstimation returns entries with only NaN values in the output file. This causes unnecessary and time-consuming calculations in personAssociation when generating and testing all possible person combinations.
This PR updates the person_combinations() function to exclude entries where all pose_keypoints_2d are NaN, by adding a check to filter out persons (with all NaN keypoints) before processing.