Instructions to use LibreYOLO/LibreVideoDepthAnythingl-depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LibreYOLO
How to use LibreYOLO/LibreVideoDepthAnythingl-depth with LibreYOLO:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 2,135 Bytes
0a8c53c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | ---
license: cc-by-nc-4.0
library_name: libreyolo
pipeline_tag: depth-estimation
tags:
- depth-estimation
- video-depth
- video-depth-anything
---
# LibreVideoDepthAnythingl-depth
Video Depth Anything Large (ViT-L DINOv2 encoder + temporal DPT head, 381.8M params), repackaged for LibreYOLO's `depth` task. Relative inverse depth (higher = closer), temporally consistent across the frames of a video.
> **Non-commercial use only.** These weights are CC BY-NC 4.0. The Small model
> ([LibreVideoDepthAnythings-depth](https://huggingface.co/LibreYOLO/LibreVideoDepthAnythings-depth))
> is Apache-2.0 and has no commercial restriction. You are responsible for
> complying with the weight licence.
## Source
Converted from [depth-anything/Video-Depth-Anything-Large](https://huggingface.co/depth-anything/Video-Depth-Anything-Large)
at revision `7aafbcb5c6af0bac741aad2b6471894fb4761afa` (`video_depth_anything_vitl.pth`).
Code: [DepthAnything/Video-Depth-Anything](https://github.com/DepthAnything/Video-Depth-Anything)
at commit `4f5ae23172ba60fd7bc11ef671cca678842c7072` (Apache-2.0).
Copyright (2025) Bytedance Ltd. and/or its affiliates.
The weights are licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
Chen, S., Guo, H., Zhu, S., Zhang, F., Huang, Z., Feng, J., and Kang, B.
"Video Depth Anything: Consistent Depth Estimation for Super-Long Videos." CVPR 2025.
## Modifications
None to the learned parameters: the upstream state dict is wrapped in LibreYOLO
checkpoint metadata with unchanged keys and tensors. See
`weights/convert_video_depth_anything_weights.py` in the
[LibreYOLO source repository](https://github.com/LibreYOLO/libreyolo).
## Usage
```python
from libreyolo import LibreYOLO
model = LibreYOLO("LibreVideoDepthAnythingl-depth.pt")
results = model.predict("video.mp4") # one Results per frame, one shared relative scale
depth = results[0].depth_map # DepthMap (H, W), higher = closer
```
## License
CC BY-NC 4.0. **Commercial use is not permitted.**
See the [`LICENSE`](./LICENSE) and [`NOTICE`](./NOTICE) files in this repository.
|