> This page is for version Release 2.2.
> For other versions, use one of these documentation indexes:
> - Release 3.0 (default): https://docs.nvidia.com/isaaclab/3.0/llms.txt
> - Release 2.3: https://docs.nvidia.com/isaaclab/2.3/llms.txt
> - Release 2.2: https://docs.nvidia.com/isaaclab/2.2/llms.txt
> - Release 2.1: https://docs.nvidia.com/isaaclab/2.1/llms.txt

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/isaaclab/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/isaaclab/_mcp/server.

# Recording video clips during training

Isaac Lab supports recording video clips during training using the
[gymnasium.wrappers.RecordVideo](https://gymnasium.farama.org/main/_modules/gymnasium/wrappers/record_video/) class.

This feature can be enabled by installing `ffmpeg` and using the following command line arguments with the training
script:

* `--video`: enables video recording during training
* `--video_length`: length of each recorded video (in steps)
* `--video_interval`: interval between each video recording (in steps)

Make sure to also add the `--enable_cameras` argument when running headless.
Note that enabling recording is equivalent to enabling rendering during training, which will slow down both startup and runtime performance.

Example usage:

```shell
python scripts/reinforcement_learning/rl_games/train.py --task=Isaac-Cartpole-v0 --headless --video --video_length 100 --video_interval 500
```

The recorded videos will be saved in the same directory as the training checkpoints, under
`IsaacLab/logs/<rl_workflow>/<task>/<run>/videos/train`.