CV-CUDA Python Package

Platform

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 0.18.0 for CUDA 13.

Metadata

Release files for cvcuda-cu13 0.18.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for cvcuda-cu13 0.18.0
File	Interpreter	ABI	Platform	Reset
cvcuda_cu13-0.18.0-py3-none-manylinux_2_27_aarch64.whl 135.7 MB Sep 16, 2026	Python 3	none	Linux glibc 2.27+ ARM64	Details
cvcuda_cu13-0.18.0-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl 99.0 MB Sep 16, 2026	Python 3	none	Linux glibc 2.17+ x86-64	Details

Total release size: 234.7 MB

Release files / cvcuda_cu13-0.18.0-py3-none-manylinux_2_27_aarch64.whl

Download URL	cvcuda_cu13-0.18.0-py3-none-manylinux_2_27_aarch64.whl
Size	135.7 MB
Tags	Linux glibc 2.27+ ARM64 Python 3
SHA-256 checksum How to use checksums	`dbfe256d0696c2e5d8c5f2d41861af656376c69c6dc50ee910996ea658ac4455`
BLAKE2b-256 checksum How to use checksums	`3e2faf1fda102897bb1e3db9a12c2ce76a76e44b24d21519b6cfd41b659767f6`
Upload date	Sep 16, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.14.7`

Release files / cvcuda_cu13-0.18.0-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl

Download URL	cvcuda_cu13-0.18.0-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Size	99.0 MB
Tags	Linux glibc 2.17+ x86-64 Python 3
SHA-256 checksum How to use checksums	`8225d8a35bdb76f51f4ab85e2c71929cdfaa499aa5e5991827763b8cb5638c4f`
BLAKE2b-256 checksum How to use checksums	`87e827cec3fdd04b1a07b304dfca0ebcd533699fbc0edef4b325d19a0ffb1860`
Upload date	Sep 16, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.14.7`