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

Limit on the number of detections?? #87

Open
phj1012 opened this issue Dec 20, 2021 · 3 comments
Open

Limit on the number of detections?? #87

phj1012 opened this issue Dec 20, 2021 · 3 comments

Comments

@phj1012
Copy link

phj1012 commented Dec 20, 2021

Is there a limit to the number of detection results?

I wonder if there is a limit to the number of detection results on TextFuseNet.

there are a lot of things that I can't catch even though I increased DETECTIONS_PER_IMAGE and other option In the config/default.py file,

I used the model that is reset 101 backbone as it is.

Is there an output limitation like a network using RPN in the past?

If there are not many objects in the image, I'm very good at catching them, but if there are many objects, I can't catch them.

So I wonder if there is a limit to the number of detection results in the network.

@kczzq
Copy link

kczzq commented Dec 20, 2021

I had the same problem.
Changing parameters does not solve the fundamental problem.
There might be limitations in output due to the network, so try using a different network.
maximum output calc rpn feature shape x anchor size. That's my guess.

@lehoangHUST
Copy link

hello @kczzq, @phj1012 Do you have solve problem??

@ddemilla
Copy link

ddemilla commented Nov 1, 2022

I struggled with this one too. If you have a large number of objects (>50), the confidence scores are likely very low. When running the demo, you can see these detections with --confidence-threshold=0.0 if you also set DETECTIONS_PER_IMAGE to a high number. However, this will lead to a large number of false positives and undesirable detections as well.

I haven't figured out how to get good confidence scores with a large number of detected objects yet (40-100) but you will at least be able to see the additional detections using the above approach.

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

4 participants