| --- |
| license: other |
| license_name: corridor-key-licence-2.0 |
| license_link: LICENSE |
| pipeline_tag: image-segmentation |
| tags: |
| - video-matting |
| - green-screen |
| - blue-screen |
| - chroma-key |
| - vfx |
| --- |
| |
| # CorridorKey 2.0 |
|
|
| Machine-learning green screen and blue screen keying at native resolution, by |
| [Corridor Digital](https://www.corridordigital.com). Given a clip, CorridorKey |
| predicts a matte and a clean foreground for every frame, with optional hints |
| to tell it which subject to key. It is HDR-capable and can write scene-linear |
| OpenEXR sequences. |
|
|
| > **Want CorridorKey inside your compositing or editing software?** The |
| > CorridorKey plugin at **[corridorkey.com](https://corridorkey.com)** brings |
| > this model into media software packages as a one-time purchase. |
|
|
| ## How to use |
|
|
| These weights are loaded by the CorridorKey 2.0 inference engine: |
| **https://github.com/nikopueringer/CorridorKey2.0** |
|
|
| ``` |
| git clone https://github.com/nikopueringer/CorridorKey2.0 |
| cd CorridorKey2.0 |
| pip install -r requirements.txt |
| python scripts/download_weights.py |
| python infer.py --input shot.mp4 --output_dir out |
| ``` |
|
|
| `scripts/download_weights.py` downloads the files in this repository along |
| with the three foundation models listed below. See the GitHub README for |
| inference modes, hints, HDR/EXR output, and low-VRAM settings. |
|
|
| ## Files |
|
|
| | File | Contents | |
| |---|---| |
| | `corridorkey_v2.safetensors` | CorridorKey 2.0 model weights (2.66 GB) | |
| | `foundation_stats.safetensors` | Normalization statistics for the foundation-model features | |
|
|
| ## Requirements |
|
|
| - NVIDIA GPU, RTX 30-series or newer, with at least 4 GB of VRAM for footage |
| up to 1440p, or 6 GB for 4K |
| - CUDA-enabled PyTorch (tested with 2.9.1) and `ffmpeg` |
|
|
| ## Foundation models |
|
|
| CorridorKey runs on features from three frozen foundation models. They are not |
| included in this repository; the download script fetches them from their |
| original publishers, under their own licenses: |
|
|
| | Model | Publisher | License | |
| |---|---|---| |
| | [C-RADIOv4-SO400M](https://huggingface.co/nvidia/C-RADIOv4-SO400M) | NVIDIA | NVIDIA Open Model License | |
| | [MoGe-2 ViT-B](https://huggingface.co/Ruicheng/moge-2-vitb-normal) | Microsoft | MIT | |
| | [RVM small](https://github.com/google-deepmind/representations4d) | Google DeepMind | CC-BY 4.0 | |
|
|
| ## Training data |
|
|
| All training data for CorridorKey 2.0 was generated in-house at Corridor |
| Digital using 3D rendering. |
|
|
| ## License |
|
|
| Use CorridorKey for whatever you'd like, including processing footage for |
| commercial projects. What you make with it is yours. |
|
|
| - You may not sell this model, or charge for access to it, and you may not |
| offer it as a paid API or inference service. |
| - You may build on the code and model, but what you release must be freely |
| accessible, stay under this same license, and keep the CorridorKey name. |
| Donationware and pay-what-you-want are fine. |
| - Organizations with more than US $20 million in annual revenue need to |
| purchase a seat of the CorridorKey plugin for each person using this model. |
| See [corridorkey.com](https://corridorkey.com). |
| - If you run a commercial software package and want to integrate CorridorKey, |
| email contact@corridordigital.com. |
|
|
| The full terms are in [LICENSE](LICENSE), a variation of |
| [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) with |
| additional terms. |
|
|
