This guide covers the dataset tools utilities available in LeRobot for modifying and editing existing datasets.
## Overview
LeRobot provides several utilities for manipulating datasets:
1. **Delete Episodes** - Remove specific episodes from a dataset
2. **Split Dataset** - Divide a dataset into multiple smaller datasets
3. **Merge Datasets** - Combine multiple datasets into one. The datasets must have identical features, and episodes are concatenated in the order specified in `repo_ids`
4. **Add Features** - Add new features to a dataset
5. **Remove Features** - Remove features from a dataset
`lerobot-edit-dataset` is a command-line script for editing datasets. It can be used to delete episodes, split datasets, merge datasets, add features, remove features, and convert image datasets to video format.
There are no constraints on the split names, they can be determined by the user. Resulting datasets are saved under the repo id with the split name appended, e.g. `lerobot/pusht_train`, `lerobot/pusht_task1`, `lerobot/pusht_task2`.
#### Merge Datasets
Combine multiple datasets into a single dataset.
```bash
# Merge train and validation splits back into one dataset
Convert an image-based dataset to video format, creating a new LeRobotDataset where images are stored as videos. This is useful for reducing storage requirements and improving data loading performance. The new dataset will have the exact same structure as the original, but with images encoded as MP4 videos in the proper LeRobot format.
```bash
# Local-only: Save to a custom output directory (no hub push)
# Convert with custom video codec and quality settings
lerobot-edit-dataset \
--repo_id lerobot/pusht_image \
--operation.type convert_to_video \
--operation.output_dir outputs/pusht_video \
--operation.vcodec libsvtav1 \
--operation.pix_fmt yuv420p \
--operation.g 2 \
--operation.crf 30
# Convert only specific episodes
lerobot-edit-dataset \
--repo_id lerobot/pusht_image \
--operation.type convert_to_video \
--operation.output_dir outputs/pusht_video \
--operation.episode_indices "[0, 1, 2, 5, 10]"
# Convert with multiple workers for parallel processing
lerobot-edit-dataset \
--repo_id lerobot/pusht_image \
--operation.type convert_to_video \
--operation.output_dir outputs/pusht_video \
--operation.num_workers 8
```
**Parameters:**
- `output_dir`: Custom output directory (optional - by default uses `new_repo_id` or `{repo_id}_video`)
- `vcodec`: Video codec to use - options: `h264`, `hevc`, `libsvtav1` (default: `libsvtav1`)
- `pix_fmt`: Pixel format - options: `yuv420p`, `yuv444p` (default: `yuv420p`)
- `g`: Group of pictures (GOP) size - lower values give better quality but larger files (default: 2)
- `crf`: Constant rate factor - lower values give better quality but larger files, 0 is lossless (default: 30)
- `fast_decode`: Fast decode tuning option (default: 0)
- `episode_indices`: List of specific episodes to convert (default: all episodes)
- `num_workers`: Number of parallel workers for processing (default: 4)
**Note:** The resulting dataset will be a proper LeRobotDataset with all cameras encoded as videos in the `videos/` directory, with parquet files containing only metadata (no raw image data). All episodes, stats, and tasks are preserved.
When you record a dataset using `lerobot`, it automatically uploads to the Hugging Face Hub unless you specify otherwise. To view the dataset online, use our **LeRobot Dataset Visualizer**, available at:
