diff --git a/README.md b/README.md index a30a7023ce1c29bd1ee52292d06fec4eb585b7de..a649089d642c82019d81343ee5b4e11f1c976778 100644 --- a/README.md +++ b/README.md @@ -1,44 +1,71 @@ --- -pretty_name: object-slide +license: cc-by-nc-4.0 +tags: +- sparsh +- DIGIT +- SSL pre-training +pretty_name: touch-slide --- -# Dataset Card for Dataset Name +# Dataset Details - +Touch-Slide is a dataset inspired by [YCB-Slide](https://github.com/rpl-cmu/YCB-Slide). Its purpose is to increase the amount of data from multiple DIGIT sensors for self-supervised learning (SSL) pre-training of the Sparsh model. Touch-Slide consists of human-sliding interactions on toy kitchen objects using the DIGIT sensor. We used 9 objects, as shown below, and collected 5 trajectories for each, resulting in a total of 180k frames. -This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). + +![Touch-Slide](assets/touch_slide_objs.png) -## Dataset Details +This is a visual example of how the dataset was collected, showcasing sliding interactions that capture trajectories rich in shear forces: -### Dataset Description +![a](assets/bread-real.gif) ![b](assets/bread-digit.gif) - - -- **Curated by:** [More Information Needed] -- **License:** [More Information Needed] - -### Dataset Sources [optional] - - - -- **Repository:** [More Information Needed] - ## Uses - - -## Dataset Structure - - - +This dataset does not include labels and is intended for self-supervised training only. It is specifically designed for training the Sparsh models listed in the Hugging Face [Sparsh collection](https://huggingface.co/collections/facebook/sparsh-67167ce57566196a4526c328). +Please refer to the [Sparsh repo](https://github.com/facebookresearch/sparsh) for further information about usage. -## Citation [optional] - - - -**BibTeX:** +## Dataset Structure -[More Information Needed] +The dataset consists of 5 trajectories for each object. Each trajectory is stored as a pickle file, containing binarized tactile images. The structure is as follows: + +```bash +Touch-Slide +├── object_0 # eg: bread +│ ├── dataset_0.pkl +│ ├── ... +│ ├── dataset_4.pkl +├── object_1 # eg: corn +├── ... +``` + +This is a sample code for loading the dataset in pickle format and extracting the images: + +```python +def load_pickle_dataset(file_dataset): + with open(file_dataset, "rb") as f: + all_frames = pickle.load(f) + return all_frames + +def load_bin_image(io_buf): + img = Image.open(io.BytesIO(io_buf)) + img = np.array(img) + return img + +frames = load_pickle_dataset('bread/dataset_0.pkl') +img = load_bin_image(frames[0]) +``` + +## BibTeX entry and citation info + +```bibtex +@inproceedings{ + higuera2024sparsh, + title={Sparsh: Self-supervised touch representations for vision-based tactile sensing}, + author={Carolina Higuera and Akash Sharma and Chaithanya Krishna Bodduluri and Taosha Fan and Patrick Lancaster and Mrinal Kalakrishnan and Michael Kaess and Byron Boots and Mike Lambeta and Tingfan Wu and Mustafa Mukadam}, + booktitle={8th Annual Conference on Robot Learning}, + year={2024}, + url={https://openreview.net/forum?id=xYJn2e1uu8} +} +``` diff --git a/assets/bread-digit.gif b/assets/bread-digit.gif new file mode 100644 index 0000000000000000000000000000000000000000..00373d019ff922d1537de84228b44f22e6633998 --- /dev/null +++ b/assets/bread-digit.gif @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a3ac94d9d308fae4492a16b7ab705675245f64ea61138d5e95bf90531724e07e +size 8913075 diff --git a/assets/bread-real.gif b/assets/bread-real.gif new file mode 100644 index 0000000000000000000000000000000000000000..3c2ae9f647b9a5f22aafdb3c8b9eedf5fd1d8bcf --- /dev/null +++ b/assets/bread-real.gif @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bd48618b41c5bb5b1bea2f1bbb83d4e963c01c931694f81cc19ba60ef993e7f4 +size 11755367 diff --git a/assets/touch_slide_objs.png b/assets/touch_slide_objs.png new file mode 100644 index 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