Imageomics HDR Anomaly Challenge Sample

This repository contains sample training code and submissions for the 2024 HDR Anomaly Challenge: Hybrid Butterfly Detection. It is designed to give participants a reference for both working on the challenge, and also the expected publication of their submissions following the challenge (i.e., how to open-source your submission).

Repository Structure

For your repository, you will want to complete the structure information below and add other files (e.g., training code):

submission
  <model weights>
  model.py
  requirements.txt

We also recommend that you include a CITATION.cff for your work.

Note: If you have requirements not included in the whitelist, please check the issues on the challenge GitHub to see if someone else has requested it before making your own issue.

Structure of this Repository

HDR-anomaly-challenge-sample
│
├── BioCLIP_code_submission
│   ├── clf.pkl
│   ├── metadata
│   ├── model.py
│   └── requirements.txt
│
├── BioCLIP_train
│   ├── classifier.py
│   ├── data_utils.py
│   ├── dataset.py
│   ├── evaluation.py
│   ├── model_utils.py
│   └── training.py
│
├── DINO_SGD_code_submission
│   ├── clf.pkl
│   ├── metadata
│   ├── model.py
│   └── requirements.txt
│
└── DINO_train
    ├── classifier.py
    ├── data_utils.py
    ├── dataset.py
    ├── evaluation.py
    ├── model_utils.py
    └── training.py

References

List any sources used in developing your model (e.g., baseline model that was fine-tuned).

training data references