| --- |
| license: mit |
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| |
| # TACDEC Pipeline |
| This is a simple model with weights and reproducible code for the results in TACDEC-paper. |
|
|
| What you can find in this repo is: |
| - The simple [model](https://huggingface.co/SimulaMet-HOST/TACDEC-model/resolve/main/model.py?download=true) used in the TACDEC-paper |
| - The [weights](https://huggingface.co/SimulaMet-HOST/TACDEC-model/resolve/main/simple_model_weights.pt?download=true) used in the proof-of-concept section in the TACDEC-paper |
| - A first notebook, [feature_extraction.ipynb](https://huggingface.co/SimulaMet-HOST/TACDEC-model/resolve/main/feature_extraction.ipynb?download=true), that contains a feature extraction process using DINOv2. |
| - A second notebook, [train_classifier.ipynb](https://huggingface.co/SimulaMet-HOST/TACDEC-model/resolve/main/train_classifier.ipynb?download=true), that uses the features that were either extracted using the first notebook, or downloaded directly from [TACDEC repo](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC). |
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| We highly recommend downloading the already extracted and concatenated (features)[https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/sorted_cls_tokens_features.pt] and the concatenated (labels)[https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/sorted_cls_tokens_labels.npy] if you wish to try the dataset/model. You would then just have to run the second notebook. |
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| Prior to running the notebooks, make sure to have all the dependencies needed. See [requirements.txt](https://huggingface.co/SimulaMet-HOST/TACDEC-model/resolve/main/requirements.txt?download=true). |
| When downloaded, run: |
|
|
| ``` |
| pip install -r requirements.txt |
| ``` |
|
|
| If you hold more interest in DINOv2, the **feature_extraction.ipynb** could hold good value. |
| |
| In both notebooks, there should be good enough documentation, but should you have any questions, see [TACDEC](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC). |
| |
| ## More information |
| For any other information or information about the dataset: |
| [TACDEC](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC) |
