Update README.md

README.md

@@ -4,15 +4,70 @@ task_categories:
 - robotics
 ---
 
-This dataset contains robot manipulation data from multiple sources, preserving the original folder hierarchy and individual files.
+<div align="center">
+<h2>Magma: A Foundation Model for Multimodal AI Agents</h2>
 
-## Dataset Structure
+[Jianwei Yang](https://jwyang.github.io/)<sup>*</sup><sup>1</sup><sup>†</sup>&nbsp;
+[Reuben Tan](https://cs-people.bu.edu/rxtan/)<sup>1</sup><sup>†</sup>&nbsp;
+[Qianhui Wu](https://qianhuiwu.github.io/)<sup>1</sup><sup>†</sup>&nbsp;
+[Ruijie Zheng](https://ruijiezheng.com/)<sup>2</sup><sup>‡</sup>&nbsp;
+[Baolin Peng](https://scholar.google.com/citations?user=u1CNjgwAAAAJ&hl=en&oi=ao)<sup>1</sup><sup>‡</sup>&nbsp;
+[Yongyuan Liang](https://cheryyunl.github.io)<sup>2</sup><sup>‡</sup>
+
+[Yu Gu](http://yu-gu.me/)<sup>1</sup>&nbsp;
+[Mu Cai](https://pages.cs.wisc.edu/~mucai/)<sup>3</sup>&nbsp;
+[Seonghyeon Ye](https://seonghyeonye.github.io/)<sup>4</sup>&nbsp;
+[Joel Jang](https://joeljang.github.io/)<sup>5</sup>&nbsp;
+[Yuquan Deng](https://scholar.google.com/citations?user=LTC0Q6YAAAAJ&hl=en)<sup>5</sup>&nbsp;
+[Lars Liden](https://sites.google.com/site/larsliden)<sup>1</sup>&nbsp;
+[Jianfeng Gao](https://www.microsoft.com/en-us/research/people/jfgao/)<sup>1</sup><sup>▽</sup>
+
+<sup>1</sup> Microsoft Research; <sup>2</sup> University of Maryland; <sup>3</sup> University of Wisconsin-Madison  
+<sup>4</sup> KAIST; <sup>5</sup> University of Washington
+
+<sup>*</sup> Project lead  <sup>†</sup> First authors  <sup>‡</sup> Second authors  <sup>▽</sup> Leadership  
+
+\[[arXiv Paper](https://www.arxiv.org/pdf/2502.13130)\] &nbsp; \[[Project Page](https://microsoft.github.io/Magma/)\] &nbsp; \[[Hugging Face Paper](https://huggingface.co/papers/2502.13130)\] &nbsp; \[[Github Repo](https://github.com/microsoft/Magma)\] &nbsp; \[[Video](https://www.youtube.com/watch?v=SbfzvUU5yM8)\] 
+
+</div>
+
+## Introduction
+
+This dataset contains the robotic manipulation data used in Magma pretraining. For fair comparison, we followed OpenVLA to use the data mix "siglip-224px+mx-oxe-magic-soup".
+
+The dataset is organized by following source datasets, with each source containing one or more arrow files:
+
+| Folder                                                |   Number of Shards |
+|:------------------------------------------------------|-------------------:|
+| austin_buds_dataset_converted_externally_to_rlds      |                  1 |
+| austin_sailor_dataset_converted_externally_to_rlds    |                  4 |
+| austin_sirius_dataset_converted_externally_to_rlds    |                  3 |
+| berkeley_autolab_ur5                                  |                  1 |
+| berkeley_cable_routing                                |                  1 |
+| berkeley_fanuc_manipulation                           |                  1 |
+| bridge_orig                                           |                 17 |
+| cmu_stretch                                           |                  1 |
+| dlr_edan_shared_control_converted_externally_to_rlds  |                  1 |
+| fractal20220817_data                                  |                 21 |
+| furniture_bench_dataset_converted_externally_to_rlds  |                  4 |
+| iamlab_cmu_pickup_insert_converted_externally_to_rlds |                  2 |
+| jaco_play                                             |                  1 |
+| kuka                                                  |                 21 |
+| language_table                                        |                  8 |
+| nyu_franka_play_dataset_converted_externally_to_rlds  |                  1 |
+| roboturk                                              |                  3 |
+| stanford_hydra_dataset_converted_externally_to_rlds   |                  4 |
+| taco_play                                             |                  3 |
+| toto                                                  |                  3 |
+| ucsd_kitchen_dataset_converted_externally_to_rlds     |                  1 |
+| utaustin_mutex                                        |                  4 |
+| viola                                                 |                  1 |
 
-The dataset is organized by source datasets, with each source containing one or more arrow files.
 
 ### Features
 
-The dataset contains the following fields:
+In addition to the default features, we extracted the visual traces of future 16 frames for each frame. The dataset contains the following fields:
+
 - `dataset_name`: Original source dataset name
 - `image`: Image of the robot scene (binary)
 - `task_string`: Description of the task
@@ -20,4 +75,20 @@ The dataset contains the following fields:
 - `traj_index`: Index of the trajectory in the dataset
 - `action`: Robot action vector (serialized numpy array)
 - `trace`: Robot trajectory trace (serialized numpy array)
-- `trace_visibility`: Visibility mask for the trace (serialized numpy array)
+- `trace_visibility`: Visibility mask for the trace (serialized numpy array)
+
+## Dataset Loading
+
+We can load the full data using:
+
+```py
+from datasets import load_dataset
+dataset = load_dataset("MagmaAI/Magma-OXE-ToM", streaming=True, split="train")
+```
+
+or specify a dataset by:
+
+```py
+from datasets import load_dataset
+dataset = load_dataset("MagmaAI/Magma-OXE-ToM", data_dir="austin_buds_dataset_converted_externally_to_rlds", streaming=True, split="train")
+```