Update README.md

README.md

@@ -1,67 +1,80 @@
----
-license: mit
----
-
-# Foundation Tactile (FoTa) - a multi-sensor multi-task large dataset for tactile sensing
-
-[![Paper](https://badgen.net/badge/icon/arXiv?icon=awesome&label&color=red)](https://github.com/alanzjl/t3_release)
-[![Repo](https://badgen.net/badge/icon/GitHub?icon=github&label)](https://github.com/alanzjl/t3_release)
-[![Colab](https://badgen.net/badge/icon/Colab?icon=terminal&label&color=yellow)](https://github.com/alanzjl/t3_release)
-
-[Jialiang (Alan) Zhao](https://alanz.info/), 
-[Yuxiang Ma](https://yuxiang-ma.github.io/), 
-[Lirui Wang](https://liruiw.github.io/), and 
-[Edward H. Adelson](https://persci.mit.edu/people/adelson/)
-MIT CSAIL
-
-[[Project Website]](https://t3.alanz.info/)
-
-![img](https://t3.alanz.info/imgs/data_vis.jpg)
-
-## Overview
-FoTa was released with Transferable Tactile Transformers (T3) as a large dataset for tactile representation learning.
-It aggregates some of the largest open-source tactile datasets, and it is released in a unified [WebDataset](https://webdataset.github.io/webdataset/) format.
-
-Fota contains over 3 million tactile images collected from 13 camera-based tactile sensors and 11 tasks.
-
-## File structure
-
-After downloading and unzipping, the file structure of FoTa looks like:
-
-```
-dataset_1
-    |---- train
-        |---- count.txt
-        |---- data_000000.tar
-        |---- data_000001.tar
-        |---- ...
-    |---- val
-        |---- count.txt
-        |---- data_000000.tar
-        |---- ...
-dataset_2
-:
-dataset_n
-```
-
-Each `.tar` file is one sharded dataset. At runtime, wds (WebDataset) api automatically loads, shuffles, and unpacks all shards on demand.
-The nicest part of having a `.tar` file, instead of saving all raw data into matrices (e.g. `.npz` for zarr), is that `.tar` is easy to visualize without the need of any code.
-Simply double clip on any `.tar` file to check its content.
-
-Although you will never need to unpack a `.tar` manually (wds does that automatically), it helps to understand the logic and file structure.
-
-```
-data_000000.tar
-    |---- file_name_1.jpg
-    |---- file_name_1.json
-    :
-    |---- file_name_n.jpg
-    |---- file_name_n.json
-```
-The `.jpg` files are tactile images, and the `.json` files store task-specific labels.
-
-For more details on operations of the paper, checkout our GitHub repository and Colab tutorial.
-
-## Citation
-
+---
+license: mit
+---
+
+# Foundation Tactile (FoTa) - a multi-sensor multi-task large dataset for tactile sensing
+
+<a href="#" class="btn btn-light" role="button" aria-pressed="true">
+    <svg class="btn-content" style="height: 1.5rem" aria-hidden="true" focusable="false" data-prefix="fas" data-icon="file-pdf" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 384 512" data-fa-i2svg=""><path fill="currentColor" d="M181.9 256.1c-5-16-4.9-46.9-2-46.9 8.4 0 7.6 36.9 2 46.9zm-1.7 47.2c-7.7 20.2-17.3 43.3-28.4 62.7 18.3-7 39-17.2 62.9-21.9-12.7-9.6-24.9-23.4-34.5-40.8zM86.1 428.1c0 .8 13.2-5.4 34.9-40.2-6.7 6.3-29.1 24.5-34.9 40.2zM248 160h136v328c0 13.3-10.7 24-24 24H24c-13.3 0-24-10.7-24-24V24C0 10.7 10.7 0 24 0h200v136c0 13.2 10.8 24 24 24zm-8 171.8c-20-12.2-33.3-29-42.7-53.8 4.5-18.5 11.6-46.6 6.2-64.2-4.7-29.4-42.4-26.5-47.8-6.8-5 18.3-.4 44.1 8.1 77-11.6 27.6-28.7 64.6-40.8 85.8-.1 0-.1.1-.2.1-27.1 13.9-73.6 44.5-54.5 68 5.6 6.9 16 10 21.5 10 17.9 0 35.7-18 61.1-61.8 25.8-8.5 54.1-19.1 79-23.2 21.7 11.8 47.1 19.5 64 19.5 29.2 0 31.2-32 19.7-43.4-13.9-13.6-54.3-9.7-73.6-7.2zM377 105L279 7c-4.5-4.5-10.6-7-17-7h-6v128h128v-6.1c0-6.3-2.5-12.4-7-16.9zm-74.1 255.3c4.1-2.7-2.5-11.9-42.8-9 37.1 15.8 42.8 9 42.8 9z"></path></svg>
+    <span class="btn-content">Paper</span>
+</a>
+<a href="https://github.com/alanzjl/t3_release" class="btn btn-light" role="button" aria-pressed="true">
+    <svg class="btn-content" style="height: 1.5rem" aria-hidden="true" focusable="false" data-prefix="fab" data-icon="github" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512" data-fa-i2svg=""><path fill="currentColor" d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg>
+    <span class="btn-content">Code</span>
+</a>
+<a href="#" class="btn btn-light" role="button" aria-pressed="true">
+    <svg class="btn-content" style="height: 1.5rem" viewBox="0 0 24 24"><!--?lit$3829301306$--><g id="colab-logo"><path d="M4.54,9.46,2.19,7.1a6.93,6.93,0,0,0,0,9.79l2.36-2.36A3.59,3.59,0,0,1,4.54,9.46Z" style="fill:var(--colab-logo-dark)"></path><path d="M2.19,7.1,4.54,9.46a3.59,3.59,0,0,1,5.08,0l1.71-2.93h0l-.1-.08h0A6.93,6.93,0,0,0,2.19,7.1Z" style="fill:var(--colab-logo-light)"></path><path d="M11.34,17.46h0L9.62,14.54a3.59,3.59,0,0,1-5.08,0L2.19,16.9a6.93,6.93,0,0,0,9,.65l.11-.09" style="fill:var(--colab-logo-light)"></path>
+        <path d="M12,7.1a6.93,6.93,0,0,0,0,9.79l2.36-2.36a3.59,3.59,0,1,1,5.08-5.08L21.81,7.1A6.93,6.93,0,0,0,12,7.1Z" style="fill:var(--colab-logo-light)"></path>
+        <path d="M21.81,7.1,19.46,9.46a3.59,3.59,0,0,1-5.08,5.08L12,16.9A6.93,6.93,0,0,0,21.81,7.1Z" style="fill:var(--colab-logo-dark)"></path>
+      </g></svg>
+    <span class="btn-content">Colab</span>
+</a>
+
+[Jialiang (Alan) Zhao](https://alanz.info/), 
+[Yuxiang Ma](https://yuxiang-ma.github.io/), 
+[Lirui Wang](https://liruiw.github.io/), and 
+[Edward H. Adelson](https://persci.mit.edu/people/adelson/)
+
+MIT CSAIL
+
+[[Project Website]](https://t3.alanz.info/)
+
+<img src="https://t3.alanz.info/imgs/data_vis.jpg" width="50%" />
+
+## Overview
+FoTa was released with Transferable Tactile Transformers (T3) as a large dataset for tactile representation learning.
+It aggregates some of the largest open-source tactile datasets, and it is released in a unified [WebDataset](https://webdataset.github.io/webdataset/) format.
+
+Fota contains over 3 million tactile images collected from 13 camera-based tactile sensors and 11 tasks.
+
+## File structure
+
+After downloading and unzipping, the file structure of FoTa looks like:
+
+```
+dataset_1
+    |---- train
+        |---- count.txt
+        |---- data_000000.tar
+        |---- data_000001.tar
+        |---- ...
+    |---- val
+        |---- count.txt
+        |---- data_000000.tar
+        |---- ...
+dataset_2
+:
+dataset_n
+```
+
+Each `.tar` file is one sharded dataset. At runtime, wds (WebDataset) api automatically loads, shuffles, and unpacks all shards on demand.
+The nicest part of having a `.tar` file, instead of saving all raw data into matrices (e.g. `.npz` for zarr), is that `.tar` is easy to visualize without the need of any code.
+Simply double clip on any `.tar` file to check its content.
+
+Although you will never need to unpack a `.tar` manually (wds does that automatically), it helps to understand the logic and file structure.
+
+```
+data_000000.tar
+    |---- file_name_1.jpg
+    |---- file_name_1.json
+    :
+    |---- file_name_n.jpg
+    |---- file_name_n.json
+```
+The `.jpg` files are tactile images, and the `.json` files store task-specific labels.
+
+For more details on operations of the paper, checkout our GitHub repository and Colab tutorial.
+
+## Citation
+
 MIT License.