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