Official code repository for A Simple Long-Tailed Rocognition Baseline via Vision-Language Model.

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Deep Learning BALLAD
Overview

BALLAD

This is the official code repository for A Simple Long-Tailed Rocognition Baseline via Vision-Language Model.

image

Requirements

  • Python3
  • Pytorch(1.7.1 recommended)
  • yaml
  • other necessary packages

Datasets

  • ImageNet_LT
  • Places_LT

Download the ImageNet_2014 and Places_365.

Modify the data_root in main.py to refer to your own dataset path.

Training

Phase A

python main.py --cfg ./config/ImageNet_LT/clip_A_rn50.yaml

Phase B

python main.py --cfg ./config/ImageNet_LT/clip_B_rn50.yaml

Testing

python main.py --cfg ./config/ImageNet_LT/test.yaml --test

Acknowledgments

The codes is based on https://github.com/zhmiao/OpenLongTailRecognition-OLTR and motivated by https://github.com/facebookresearch/classifier-balancing.

Comments
  • Approximate Training Time

    Approximate Training Time

    Hi. May I ask how long does it take to train the model with setting "ResNet50×16" on ImageNet-LT using an 8xA100 or 8xV100 server?

    I would appreciate it a lot if you could provide me an approximate training time.

    opened by sandylaker 2
  • Question about the paper.

    Question about the paper.

    Hi @TeleeMa , thanks for your inspiring work in applying the vision-language model to long-tailed recognition. And I have some questions about the precision of the zero-shot CLIP on the Imagenet-LT test split. In the paper, you point out the results are balanced on many-shots (59.4%), medium-shots (57.5%), and low-shots (57.6%) subsets and the overall performance (58.2%). And the performance of the original CLIP on the Imagenet are 73.3%: image So I wonder if there is any difference in settings between BALLAD and CLIP? Looking forward to your reply and thanks in advance~

    opened by waveboo 1
  • Training Config of PlacesLT

    Training Config of PlacesLT

    Hello,

    Great work! Thanks a lot for sharing the codes!

    I can find the config of training on ImageNetLT, but the configs of training on PlaceLT and CIFAR10 are missing. Also, I cannot find the details of training hyperparameters in the original paper.

    Could you please share the config files for PlaceLT and CIFAR10? Or you can simply tell me the details of hyperparameters here, please. Thanks for your help!

    opened by chrisyxue 0
  • Releasing the pre-trained models

    Releasing the pre-trained models

    Thank you for your awesome work, it's very inspiring.

    I just wonder if you have any plan of releasing the checkpoint of your model? It would be nice to have them so we don't need to re-run the experiments. :)

    opened by Duconnor 0
  • The version of CIFAR

    The version of CIFAR

    Thanks for your great work! I have a slight problem, will you release the version of CIFAR? The small dataset will be more helpful and feasible for us to train the model. Thank you!

    opened by madoka109 0
Owner
peng gao
Young Scientist at Shanghai AI Lab
peng gao
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