docs: add dataset details to README

README.md

@@ -1,3 +1,53 @@
----
-license: mit
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+---
+license: mit
+---
+
+# Dataset of DeformPAM
+
+## Contents
+
+- [Description](#description)
+- [Structure](#structure)
+- [Usage](#usage)
+
+## Description
+
+This is the dataset used in the paper [DeformPAM: Data-Efficient Learning for Long-horizon Deformable
+Object Manipulation via Preference-based Action Alignment](https://deform-pam.robotflow.ai).
+
+- [Project Homepage](https://deform-pam.robotflow.ai)
+- [Github Repository](https://github.com/xiaoxiaoxh/DeformPAM)
+- [Paper](https://arxiv.org/pdf/2410.11584.pdf)
+
+## Structure
+
+We offer two versions of the dataset: one is the [full dataset](https://huggingface.co/datasets/WendiChen/DeformPAM/tree/main/dataset_full) used to train the models in our paper,
+and the other is a [mini dataset](https://huggingface.co/datasets/WendiChen/DeformPAM/tree/main/dataset_mini) for easier examination.
+Both datasets include data for the supervised and finetuning stages of granular pile shaping, rope shaping, and T-shirt unfolding.
+Each subset is structured as follows:
+
+```
+├── annotations
+│   ├── 0aa71092-06c1-4d3f-8f70-e0bf86eeaeab
+│   │   └── metadata.yaml annotations and other detailed information
+│   ├── ...
+└── observations
+    ├── 0aa71092-06c1-4d3f-8f70-e0bf86eeaeab
+    │   ├── mask
+    │   │   └── begin.png mask img used for segmenting the point cloud
+    │   ├── metadata.yaml detailed information
+    │   ├── pcd
+    │   │   ├── processed_begin.npz segmented point cloud of the object; processed_begin["points"]: np.ndarray (N, 3) float16
+    │   │   └── raw_begin.npz raw point cloud of the object; raw_begin["points"]: np.ndarray (N, 3) float16
+    │   └── rgb
+    │       └── begin.jpg RGB image of the object
+    ├── ...
+```
+
+## Usage
+
+There are two ways to utilize the dataset for training:
+
+- Install the tool according to the [data management toolkit's installation guide](https://github.com/xiaoxiaoxh/DeformPAM/blob/main/tools/data_management/README.md),
+  and then store the metadata to MongoDB.
+- Or, you can modify the [dataset](https://github.com/xiaoxiaoxh/DeformPAM/blob/main/learning/datasets/runtime_dataset_real.py#L307) to load data from local files.