metadata
license: mit
task_categories:
- robotics
Dataset of DeformPAM
Contents
Description
This is the dataset used in the paper DeformPAM: Data-Efficient Learning for Long-horizon Deformable Object Manipulation via Preference-based Action Alignment.
Structure
We offer two versions of the dataset: one is the full dataset used to train the models in our paper, and the other is a mini dataset 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:
├── 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, and then store the metadata to MongoDB.
- Or, you can modify the dataset to load data from local files.