| # ODIR-5K preparation for TriPAH | |
| Source: [ODIR-2019 challenge dataset](https://odir2019.grand-challenge.org/dataset/). | |
| The current local prepared artifact contains 3,500 binocular samples with 8 labels. Its 3,500 image references are valid. Images are processed JPEGs formed by concatenating the left and right fundus views. Captions contain age, sex, and bilateral diagnostic keywords. | |
| This folder distributes instructions only. Obtain the original data and confirm the applicable redistribution terms with the source provider. | |
| From the TriPAH code checkout, after installing dependencies: | |
| ```bash | |
| python -m dataset.builders.convert_odir_dataset \ | |
| --root /path/to/ODIR-5K --output dataset/odir | |
| ``` | |
| Expected raw inputs are `data.xlsx` and `Training_Images/` or `Training Images/`. For a different image location, supply `--train-dir /path/to/images`. | |
| The prepared layout requires `caption.txt`, `index.mat`, `label.mat`, `prompt_caption.npz`, and `images/`. Preserve row alignment. The local labels have shape `[3500,8]` and the main float32 prompt embeddings have shape `[3500,77,512]`. | |
| For detailed conversion and training instructions, see [TriPAH's ODIR guide](https://github.com/Medical-Multi-Agent-AI/TriPAH/blob/main/README_ODIR.md). | |