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---
license: mit
task_categories:
- robotics
---

# 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).

- [Paper](https://arxiv.org/pdf/2410.11584.pdf)
- [Project Homepage](https://deform-pam.robotflow.ai)
- [GitHub Repository](https://github.com/xiaoxiaoxh/DeformPAM)
- [Pretrained Models](https://huggingface.co/WendiChen/DeformPAM_PrimitiveDiffusion)

## Structure

We offer two versions of the dataset: one is the [full dataset](https://huggingface.co/datasets/WendiChen/DeformPAM_Dataset/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_Dataset/tree/main/dataset_mini) for easier examination.
Both versions include the supervised and finetuning subsets of granular pile shaping, rope shaping, and T-shirt unfolding.
Each subset is structured as follows:

```
β”œβ”€β”€ annotations
β”‚   β”œβ”€β”€ 0aa71092-06c1-4d3f-8f70-e0bf86eeaeab
β”‚   β”‚   └── metadata.yaml annotations and other detailed information
β”‚   β”œβ”€β”€ ...
└── observations
    β”œβ”€β”€ 0aa71092-06c1-4d3f-8f70-e0bf86eeaeab
    β”‚   β”œβ”€β”€ mask
    β”‚   β”‚   └── begin.png mask img used for segmenting the point cloud
    β”‚   β”œβ”€β”€ metadata.yaml detailed information
    β”‚   β”œβ”€β”€ pcd
    β”‚   β”‚   β”œβ”€β”€ processed_begin.npz segmented point cloud of the object; processed_begin["points"]: np.ndarray (N, 3) float16
    β”‚   β”‚   └── raw_begin.npz raw point cloud of the object; raw_begin["points"]: np.ndarray (N, 3) float16
    β”‚   └── rgb
    β”‚       └── begin.jpg RGB image of the object
    β”œβ”€β”€ ...
```

## 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.