CV-CUDA Python Package
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.
Installation
pip install cvcuda-cu13
CV-CUDA in action
Fully GPU-accelerated image resizing with nvImageCodec and CV-CUDA.
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
Requirements
- CUDA Toolkit 13 or later
- Python 3.10 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.
Support
Citation
If you use CV-CUDA in your research, please cite:
@software{cvcuda,
title = {CV-CUDA},
author = {NVIDIA Corporation},
year = {2023},
url = {https://github.com/CVCUDA/CV-CUDA}
}
Note: This is version 0.19.0 for CUDA 13.
Metadata
Release files for cvcuda-cu13 0.19.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cvcuda_cu13-0.19.0-py3-none-manylinux_2_27_aarch64.whl | Python 3 | none | Linux glibc 2.27+ ARM64 | Details |
| cvcuda_cu13-0.19.0-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl | Python 3 | none | Linux glibc 2.17+ x86-64 | Details |
Total release size: 327.0 MB
Release files / cvcuda_cu13-0.19.0-py3-none-manylinux_2_27_aarch64.whl
| Download URL | cvcuda_cu13-0.19.0-py3-none-manylinux_2_27_aarch64.whl |
|---|---|
| Size | 199.2 MB |
| Tags | Linux glibc 2.27+ ARM64 Python 3 |
|
SHA-256 checksum How to use checksums |
f0c798fe7e8ea80e03bbc454599c38564645519e9b0cf7052e9dbca9251dec6f
|
|
BLAKE2b-256 checksum How to use checksums |
2d78b0ea40bcdc55528725d696be822077ed2af9426a4f8cd5a4108782168944
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.8
|
Release files / cvcuda_cu13-0.19.0-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
| Download URL | cvcuda_cu13-0.19.0-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl |
|---|---|
| Size | 127.8 MB |
| Tags | Linux glibc 2.17+ x86-64 Python 3 |
|
SHA-256 checksum How to use checksums |
dd62ea08f13e4bebfd62c02e947fedd6d48705cea6f11d6abc7b8e5f65f101ae
|
|
BLAKE2b-256 checksum How to use checksums |
1ab83a05d2170ecb4381531ccf68ac7968d2cb39d24f48cf93ca46778c51b37a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.8
|
Security for cvcuda-cu13 0.19.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
