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@@ -15,17 +15,17 @@ The dataset is fully open for research and educational purposes. Use of the data
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  ## How to download dataset:
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- Everything that is related directly to the dataset is located within this repo. For instructions related to testing the model used or verifying results from TACDEC-paper, see [TACDEC-model](https://huggingface.co/SimulaMet-HOST/TACDEC-model) repo.
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  What you can find in this repo is:
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  - All 425 [videos](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/videos.zip)
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  - All 425 [labels](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/labels.zip)
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  In addition:
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- - A torch, [sorted_cls_tokens_feature.pt](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/sorted_cls_tokens_features.pt) , containing all the CLS-tokens (features) from DINOv2 used concatenated in a sorted order
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  - A numpy array, [sorted_cls_tokens_labels.npy](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/sorted_cls_tokens_labels.npy), containing all the labels used, concatenated in the same sorted order
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- We highly recommend downloading these if you choose to implement/test the model, as running the large DINOv2 model is highly computationally expensive.
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  **Citation:**
@@ -47,7 +47,7 @@ We highly recommend downloading these if you choose to implement/test the model,
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  **Contact**
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- For any questions regarding the dataset, or to discuss potential collaboration and joint research opportunities, please contact the following people:
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  - Evan Jåsund Kassab: evanjk@uio.no
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  - Cise Midoglu: cise@simula.no
 
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  ## How to download dataset:
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+ Everything that is related directly to the dataset is located within this repo. For instructions related to testing the model used or verifying results from TACDEC-paper, see [TACDEC-model repo](https://huggingface.co/SimulaMet-HOST/TACDEC-model).
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  What you can find in this repo is:
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  - All 425 [videos](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/videos.zip)
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  - All 425 [labels](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/labels.zip)
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  In addition:
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+ - A torch, [sorted_cls_tokens_feature.pt](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/sorted_cls_tokens_features.pt), containing all the CLS-tokens (features) from DINOv2 used concatenated in a sorted order
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  - A numpy array, [sorted_cls_tokens_labels.npy](https://huggingface.co/datasets/SimulaMet-HOST/TACDEC/resolve/main/sorted_cls_tokens_labels.npy), containing all the labels used, concatenated in the same sorted order
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+ We highly recommend downloading these if you want to implement/test the model, as running the large DINOv2 model is highly computationally expensive.
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  **Citation:**
 
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  **Contact**
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+ For any questions regarding the dataset, or to discuss potential collaboration and joint research opportunities, please get in touch with the following people:
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  - Evan Jåsund Kassab: evanjk@uio.no
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  - Cise Midoglu: cise@simula.no