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

Inconsistent ID Assignment During Training on Custom Driving Dataset #69

Open
back2zack opened this issue Jun 5, 2024 · 2 comments
Open

Comments

@back2zack
Copy link

back2zack commented Jun 5, 2024

Description:
I'm encountering issues with the MOTRV2 model while training it on a custom dataset of driving sequences . The model detects objects in the frames correctly, but the ID assignment is highly inconsistent. Objects often get new IDs in consecutive frames, and multiple IDS are sometimes assigned to the same Object.

Dataset Details:

  • The dataset consists of sequences with approximately 100 frames each.
  • Each sequence captures various driving scenes .
  • Attempted to overfit on a single sequence with 150 frames.

Data Preparation:
I used the same data augmentation techniques and data structure as those used for the DanceTrack dataset.

Training Parameters:

--meta_arch motr --dataset_file e2e_dspace --epoch 60 --with_box_refine --lr_drop 4 --lr 2e-4 --lr_backbone 2e-5 --batch_size 1 --sample_mode random_interval --sample_interval 4 --sampler_lengths 10 --merger_dropout 0 --dropout 0 --random_drop 0.1 --fp_ratio 0.3 --query_interaction_layer QIMv2 --query_denoise 0.05 --num_queries 10

Observed Behavior:

  • Objects detected in frames are frequently assigned new IDs.
  • Multiple IDs are sometimes given to the same Object.
  • Although the loss function is decreasing, the ID assignment remains inconsistent.

image
image
image

I assume that the inaccuracy in detections is due to the fact that the system was only trained on a small sequence, but there is no correct assignment of an ID during the entire sequence.

@Shawnnnnn
Copy link

what is your score threshold when inference? when I set it to 0.5, it will get probably OK results.

@back2zack
Copy link
Author

@Shawnnnnn are you also working with automotive dataset ? how are your results looking ?

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