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@@ -29,7 +29,9 @@ NASA GeneLab VisionTransformer on BPS Microscopy Data
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  [Sylvain Costes](https://www.nasa.gov/people/sylvain-costes/), NASA Ames Resarch Center<br>
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  ## General:
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- This Vision Transformer model has been fine-tuned on BPS Microscopy data. The images used are available here:
 
 
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  [Biological and Physical Sciences (BPS) Microscopy Benchmark Training Dataset](https://registry.opendata.aws/bps_microscopy/) or as a Huggingface dataset here:
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  [kenobi/GeneLab_BPS_BenchmarkData](https://huggingface.co/datasets/kenobi/GeneLab_BPS_BenchmarkData).
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  This is a Vision Transformer model trained on Fluorescence microscopy images of individual nuclei from mouse fibroblast cells,
@@ -53,9 +55,9 @@ We will include more technical details here soon.
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  ![](images/XRay_irradiated_Nuclei.png)
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  ![Right-click on this link (not the picture seen above) use 'save as'](https://roosevelt.devron-systems.com/HF/P278_73668090728-A7_003_027_proj.tif)
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- ## ViT base training data
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  The ViT model was pretrained on a dataset consisting of 14 million images and 21k classes ([ImageNet-21k](http://www.image-net.org/).
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- More information on the base model used can be found here: (https://huggingface.co/google/vit-base-patch16-224-in21k)
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  ## How to use this Model
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  (quick snippets to work on Google Colab)
 
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  [Sylvain Costes](https://www.nasa.gov/people/sylvain-costes/), NASA Ames Resarch Center<br>
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  ## General:
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+
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+ This Vision Transformer model has been fine-tuned on BPS Microscopy data. We are currently working on an expansive optimisation and evaluation framework.
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+ The images used are available here:
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  [Biological and Physical Sciences (BPS) Microscopy Benchmark Training Dataset](https://registry.opendata.aws/bps_microscopy/) or as a Huggingface dataset here:
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  [kenobi/GeneLab_BPS_BenchmarkData](https://huggingface.co/datasets/kenobi/GeneLab_BPS_BenchmarkData).
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  This is a Vision Transformer model trained on Fluorescence microscopy images of individual nuclei from mouse fibroblast cells,
 
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  ![](images/XRay_irradiated_Nuclei.png)
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  ![Right-click on this link (not the picture seen above) use 'save as'](https://roosevelt.devron-systems.com/HF/P278_73668090728-A7_003_027_proj.tif)
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+ ## ViT base training data (currently being replaced)
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  The ViT model was pretrained on a dataset consisting of 14 million images and 21k classes ([ImageNet-21k](http://www.image-net.org/).
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+ More information on the base model used can be found here: (https://huggingface.co/google/vit-base-patch16-224-in21k);
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  ## How to use this Model
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  (quick snippets to work on Google Colab)