Metadata-Version: 2.4
Name: nvidia-vipe
Version: 0.1.2
Summary: NVIDIA Video Pose Engine
Author-email: The ViPE Authors <jiahuih@nvidia.com>
License-Expression: Apache-2.0
Project-URL: Homepage, https://research.nvidia.com/labs/toronto-ai/vipe
Project-URL: Repository, https://github.com/nv-tlabs/vipe
Project-URL: Paper, https://research.nvidia.com/labs/toronto-ai/vipe/assets/paper.pdf
Keywords: computer-vision,depth-estimation,nvidia,pose-estimation,video
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Processing
Requires-Python: <3.15,>=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch
Requires-Dist: torchvision
Requires-Dist: click
Requires-Dist: einops
Requires-Dist: gdown
Requires-Dist: huggingface_hub
Requires-Dist: hydra-core
Requires-Dist: imageio[ffmpeg]
Requires-Dist: kornia
Requires-Dist: matplotlib
Requires-Dist: ninja
Requires-Dist: numpy
Requires-Dist: omegaconf
Requires-Dist: opencv-python
Requires-Dist: OpenEXR<3.3.0
Requires-Dist: pydantic<3,>=2
Requires-Dist: pillow
Requires-Dist: python-pycg
Requires-Dist: ray
Requires-Dist: rerun-sdk
Requires-Dist: safetensors
Requires-Dist: scipy
Requires-Dist: timm
Requires-Dist: tqdm
Requires-Dist: transformers<5,>=4
Requires-Dist: viser
Dynamic: license-file

# ViPE: Video Pose Engine for Geometric 3D Perception

<p align="center">
  <img src="assets/teaser.gif" alt="teaser"/>
</p>

**TL;DR: ViPE is a useful open-source spatial AI tool for annotating camera poses and dense depth maps from raw videos!**

ViPE estimates camera intrinsics, camera motion, and dense near-metric depth maps from unconstrained raw videos, including pinhole, wide-angle, and 360-degree panorama footage.

## Links

- 📖 [Documentation](https://nv-tlabs.github.io/vipe/)
- 🌐 [Project page](https://research.nvidia.com/labs/toronto-ai/vipe)
- 📄 [Technical whitepaper](https://research.nvidia.com/labs/toronto-ai/vipe/assets/paper.pdf)
- 📊 [Datasets](https://nv-tlabs.github.io/vipe/dataset/)

## Installation

```bash
pip install nvidia-vipe
```

This installs the `vipe` Python package and the `vipe` CLI. ViPE releases are published as source distributions, so pip builds the native CUDA extensions during installation. The environment needs a CUDA-enabled PyTorch build and an available CUDA toolkit with `nvcc`.

## License

This project will download and install additional third-party **models and softwares**. Note that these models or softwares are not distributed by NVIDIA. Review the license terms of these models and projects before use. This source code, **except for the Unik3D part (which is under the BY-NC-SA 4.0 license)** , is released under the [Apache 2 License](https://www.apache.org/licenses/LICENSE-2.0).
