A Library to Fine-Tune Vision-Language-Brain Models for the CNeuroMod Phantom project
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── README.md <- The top-level README for developers using this project.
├── data <- Where CNeuroMod datasets are installed (e.g., stimuli, fmriprep BOLD data)
├── docs <- A default Sphinx project; see sphinx-doc.org for details
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├── models <- Cache directory to save pre-trained model params
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├── config <- .yaml config files to define params using hydra
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├── requirements_*.txt <- The requirements file for reproducing the analysis environment (rorqual or beluga CC cluster)
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├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
├── src <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module
│ ├── utils.py <- Miscellaneous support functions
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│ ├── datamodule <- Pytorch lightning datamodule scripts
│ │ └── videollama2_vlb_datamodule.py
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│ ├── litmodule <- Pytorch lightning litmodule scripts
│ │ └── videollama2_vlb_litmodule.py
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│ ├── preprocessing <- Scripts to extract features from input and to prepare lazy loading batches
│ │ ├── videollama2_vlb_extractfeatures.py
│ │ └── videollama2_vlb_lazyloading.py
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│ └── postprocessing <- Scripts to project accuracy metrics onto the brain
│ └── make_acc_brainmaps.py
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└── train.py <- Main train script
Project based on the cookiecutter data science project template. #cookiecutterdatascience