Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Add COCO mAP #139

Open
songyuc opened this issue Mar 30, 2023 · 1 comment
Open

Add COCO mAP #139

songyuc opened this issue Mar 30, 2023 · 1 comment

Comments

@songyuc
Copy link

songyuc commented Mar 30, 2023

🚀 The feature

COCO mAP

COCO mAP (mean average precision) is a widely used evaluation metric for object detection models, especially for the COCO dataset. Unlike the PASCAL VOC evaluation, which has a single IoU (Intersection over Union) threshold for assessing the detection model, the COCO mAP evaluator averages the mAP of 80 classes over 10 IoU thresholds from 0.5 to 0.95 with a step size of 0.05 (AP@[0.5:0.05:0.95]). This is to avoid the bias that a single threshold may induce in the evaluation metric and to provide a more complete analysis of the detection model.

Motivation, pitch

COCO mAP has an official API, which lacks maintenance and has been outdated.

Alternatives

No response

Additional context

No response

@bobakfb
Copy link
Contributor

bobakfb commented Mar 30, 2023

Hey @songyuc, thanks for this feature request! Are you proposing to work on this yourself or did you want to leave it up for someone else to grab?

Can you explain how COCO mAP works? Do you need to have COCO on your device already or does it download part of it to run?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants