semvec/pypi-packages huggingface dataset:
cvcuda-cu13 0.16.0
CUDA-accelerated Computer Vision algorithms
License: Apache-2.0
Requires Python: <3.15,>=3.9
Keywords: cuda, computer-vision, image-processing, nvidia, gpu

[//]: # "SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved."
[//]: # "SPDX-License-Identifier: Apache-2.0"

# CV-CUDA Python Package

[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![CUDA](https://img.shields.io/badge/CUDA-13-green.svg)](https://developer.nvidia.com/cuda-toolkit)
[![Python](https://img.shields.io/badge/python-3.9--3.14-blue)](https://www.python.org/)
![Platform](https://img.shields.io/badge/Platform-Linux%20x86__64%20%7C%20Linux%20aarch64%20%7C%20WSL2-blue)

CV-CUDA is an open-source library of GPU-accelerated computer vision algorithms designed for speed and scalability.
It delivers high-throughput, low-latency image/video processing for AI pipelines across NVIDIA cloud, desktop, and edge platforms.
CV-CUDA is built for performance and works seamlessly with C/C++ and Python frameworks.

For more information on available operators, API documentation, and getting started guides, refer to our [online documentation][CV-CUDA Documentation].

## Installation

```bash
pip install cvcuda-cu13
```

## CV-CUDA in action

Fully GPU-accelerated image resizing with [nvImageCodec](https://docs.nvidia.com/cuda/nvimagecodec/index.html) and CV-CUDA.

```python
import cvcuda
from nvidia import nvimgcodec

# Decode image directly to GPU
decoder = nvimgcodec.Decoder()
image = decoder.read("input.jpg")

# Convert to CV-CUDA tensor and process
cvcuda_tensor = cvcuda.as_tensor(image, "HWC")
resized = cvcuda.resize(cvcuda_tensor, (224, 224, 3), cvcuda.Interp.LINEAR)
```

## Documentation

- [Official Documentation](https://cvcuda.github.io)
- [Samples](https://cvcuda.github.io/samples)

## Requirements

- CUDA Toolkit 13 or later
- Python 3.9 or later
- NumPy 1.23.5 or later
- Linux x86_64 (Ubuntu 20.04, 22.04, or later)

## License

CV-CUDA is licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0).

## Support

- [GitHub Issues](https://github.com/CVCUDA/CV-CUDA/issues)
- [GitHub Discussions](https://github.com/CVCUDA/CV-CUDA/discussions)

## Citation

If you use CV-CUDA in your research, please cite:

```bibtex
@software{cvcuda,
  title = {CV-CUDA},
  author = {NVIDIA Corporation},
  year = {2023},
  url = {https://github.com/CVCUDA/CV-CUDA}
}
```

---

**Note**: This is version 0.16.0 for CUDA 13.

[CV-CUDA Documentation]: https://cvcuda.github.io