vidformer

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A drop-in declarative optimization framework for rendering video data visualizations.

vidformer 최신버젼 다운로드

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# vidformer

[![DOI](https://zenodo.org/badge/842723851.svg)](https://doi.org/10.5281/zenodo.19710152)
[![Test](https://github.com/ixlab/vidformer/actions/workflows/test.yml/badge.svg)](https://github.com/ixlab/vidformer/actions/workflows/test.yml)
[![PyPI version](https://img.shields.io/pypi/v/vidformer.svg)](https://pypi.org/project/vidformer/)
[![Crates.io Version](https://img.shields.io/crates/v/vidformer)](https://crates.io/crates/vidformer)
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ixlab/vidformer/blob/main/misc/Colab_Vidformer.ipynb)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/ixlab/vidformer/blob/main/LICENSE)

A research project for accelerating video/data visualization.
See the [preprint on arXiv](https://arxiv.org/abs/2601.17221) for details.

Developed by the OSU Interactive Data Systems Lab.

![Vidformer teaser](https://raw.githubusercontent.com/ixlab/vidformer/main/misc/landing-page/static/images/teaser.png)

## Quick Start

To quickly try out Vidformer you can:

*  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ixlab/vidformer/blob/main/misc/Colab_Vidformer.ipynb)
* try the online [Vidformer Playground](https://ixlab.github.io/vidformer/playground/)

Or, you can deploy it yourself:

```bash
git clone https://github.com/ixlab/vidformer
cd vidformer
docker build -t igni -f Dockerfile .
docker-compose -f vidformer-igni/docker-compose-local.yaml up
```

You can find details on this in our [Getting Started Guide](https://ixlab.github.io/vidformer/docs/getting-started.html).

## Why vidformer

Vidformer efficiently transforms videos, enabling faster annotation, editing, and processing of video data—without having to focus on performance. Just swap `import cv2` with `import vidformer.cv2 as cv2` to see video outputs instantly.

Vidformer uses a declarative specification format to represent transformations. This enables:

* **Transparent Optimization:** Vidformer optimizes the execution of declarative specifications just like a relational database optimizes relational queries.

* **Lazy/Deferred Rendering:** Video results can be retrieved on-demand, allowing for practically instantaneous playback of video results.

Vidformer usually renders videos 2-3x faster than cv2, and hundreds of times faster (*practically instantly*) when serving videos on-demand.

Vidformer builds on open technologies you may already use:
  * **OpenCV:** A `cv2`-compatible interface ensures both you (and LLMs) can use existing knowledge and code.
  * **Supervision:** [Supervision](https://supervision.roboflow.com/latest/)-compatible annotators make visualizing computer vision models trivial.
  * **FFmpeg:** Built on the same libraries, codecs, and formats that run the world.
  * **Jupyter:** View transformed videos instantly right in your notebook.
  * **HTTP Live Streaming (HLS):** Serve transformed videos over a network directly into any media player.
  * **Apache OpenDAL:** Access source videos no matter where they are stored.

## Documentation

* [🌐 Website](https://ixlab.github.io/vidformer/)
* [🌐 Docs](https://ixlab.github.io/vidformer/docs/)
* [🚀 Getting Started](https://ixlab.github.io/vidformer/docs/getting-started.html)
* [🐍 vidformer-py](https://ixlab.github.io/vidformer/vidformer-py/)
* [🛠️ vidformer core](https://ixlab.github.io/vidformer/vidformer/)

## About the project

**Cite:**
```
@misc{winecki2026_vidformer,
      title={Vidformer: Drop-in Declarative Optimization for Rendering Video-Native Query Results},
      author={Dominik Winecki and Arnab Nandi},
      year={2026},
      eprint={2601.17221},
      archivePrefix={arXiv},
      primaryClass={cs.DB},
      url={https://arxiv.org/abs/2601.17221},
}
```

**File Layout**:
- [*./vidformer*](./vidformer/): The core rendering library (Rust)
- [*./vidformer-py*](./vidformer-py/): The Python frontend
- [*./vidformer-igni*](./vidformer-igni/): The vidformer server
- [*./misc/vidformer-mcp*](./misc/vidformer-mcp/): An MCP server
- [*./misc/vidformer-slack*](./misc/vidformer-slack/): A slack bot
- [*./misc/tla*](./misc/tla/): A TLA+ model of the rendering engine
- [*./docs*](./docs/): The [project docs](https://ixlab.github.io/vidformer/docs/)

Vidformer components are detailed [here](https://ixlab.github.io/vidformer/docs/modules.html).

**License:** Vidformer is open source under [Apache-2.0](./LICENSE).
Contributions are welcome.

**Acknowledgements:** Supported by the Imageomics Institute (NSF Award #2118240) and NSF Award #1910356. Any opinions, findings and conclusions or recommendations expressed in the materials here are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

vidformer

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