Fast-UMI: A Scalable and Hardware-Independent Universal Manipulation Interface

Welcome to the official repository of FastUMI!

Project Page | Hugging Face Dataset | PDF (Early Version) | PDF (TBA)

FastUMI Prototype

Physical prototypes of the Fast-UMI system

.hdf5 ├── observations/ │ ├── images/ │ │ └── (Dataset) │ └── qpos (Dataset) ├── action (Dataset) └── attributes/ └── sim = False ``` Attributes: sim - Type: Boolean - Value: False - Description: Indicates whether the data was recorded in simulation (True) or real-world (False). Groups and Datasets: observations/ - images/ - Description: Stores image data from camera. - Datasets: - front - Type: Dataset containing image arrays. - Shape: (num_frames, height=1920, width=1080, channels=3) - Data Type: uint8 - Compression: gzip with compression level 4. - qpos - Type: Dataset - Shape: (num_timesteps, 7) - Description: Stores position and orientation data for each timestep. - Columns: [Pos X, Pos Y, Pos Z, Q_X, Q_Y, Q_Z, Q_W] - action - Type: Dataset - Shape: (num_timesteps, 7) - Description: Stores action data corresponding to each timestep. In this script, actions mirror the qpos data. - Columns: [Pos X, Pos Y, Pos Z, Q_X, Q_Y, Q_Z, Q_W] ### 📂 A. Splitting Data The data is split to ensure each part remains below the 50GB limit. The splitting process divides large `.tar.gz` files into smaller chunks. **Splitting Overview:** - **Method**: Use file splitting tools or commands to divide large files into manageable parts. - **Example Tool**: `split` command in Unix-based systems. **Example Command:** ```bash split -b 8G FastUMI_Data.tar.gz FastUMI_Data.tar.gz.part- ``` This command splits `FastUMI_Data.tar.gz` into 8GB parts with filenames starting with `FastUMI_Data.tar.gz.part-`. ### 💡 B. Merging Data After downloading the split files, users need to merge them to reconstruct the original dataset. **Merging Instructions:** 1. **Navigate to the Download Directory:** ```bash cd path_to_downloaded_files ``` 2. **Merge Files Using `cat`:** Use the `cat` command to concatenate the split parts. Replace `filename.tar.gz.part-001`, `filename.tar.gz.part-002`, etc., with your actual file names. ```bash cat filename.tar.gz.part-* > filename.tar.gz ``` **Example:** ```bash cat FastUMI_Data.tar.gz.part-* > FastUMI_Data.tar.gz ``` 3. **Alternatively, Use the Provided Python Script to Automate Merging:** Save the following script as `merge_files.py`: ```python import os import glob def merge_files(part_pattern, output_file): """ Merges split file parts into a single file. :param part_pattern: Pattern matching the split file parts, e.g., "filename.tar.gz.part-*" :param output_file: Name of the output merged file, e.g., "filename.tar.gz" """ parts = sorted(glob.glob(part_pattern)) if not parts: raise FileNotFoundError(f"No parts found for pattern: {part_pattern}") with open(output_file, 'wb') as outfile: for part in parts: print(f"Merging {part} into {output_file}") with open(part, 'rb') as infile: while True: chunk = infile.read(1024 * 1024) # 1MB if not chunk: break outfile.write(chunk) print(f"Merge completed: {output_file}") if __name__ == "__main__": import argparse parser = argparse.ArgumentParser(description="Merge split file parts into a single file.") parser.add_argument('--pattern', type=str, required=True, help='Pattern of split file parts, e.g., "filename.tar.gz.part-*"') parser.add_argument('--output', type=str, required=True, help='Name of the output merged file, e.g., "filename.tar.gz"') args = parser.parse_args() merge_files(args.pattern, args.output) ``` **Usage:** 1. **Run the Merging Script:** ```bash python merge_files.py --pattern "filename.tar.gz.part-*" --output "filename.tar.gz" ``` Replace `filename.tar.gz.part-*` and `filename.tar.gz` with your actual file name pattern and desired output file name. 2. **Example:** ```bash python merge_files.py --pattern "FastUMI_Data.tar.gz.part-*" --output "FastUMI_Data.tar.gz" ``` 4. **Verify the Merged File:** Ensure that the merged file size matches the original file size before splitting. You can use the `ls -lh` command to check file sizes. ```bash ls -lh FastUMI_Data.tar.gz ``` 5. **Extract the Dataset:** Once merged, extract the dataset using the `tar` command: ```bash tar -xzvf FastUMI_Data.tar.gz ``` ## 🔧 Usage After successfully merging and extracting the dataset, you can utilize it for training and evaluating robotic manipulation models. Detailed methodologies and application examples are available on the [Project Page](https://fastumi.com/) and in the [Early Version PDF](https://arxiv.org/abs/2409.19499). ## License This project is licensed under the [MIT License](https://opensource.org/licenses/MIT). ## Contact For questions or feedback, please reach out to the yding25@binghamton.edu or visit our [website](https://fastumi.com/).