Installation#
Pre-requisites#
This section describes the recommended dependencies to use nvImageCodec.
Supported operating systems and architectures:
Architecture |
Distribution Info |
|
|---|---|---|
Name |
Version |
|
x86_64 |
Amazon Linux |
2023 |
Azure Linux |
3 |
|
Debian |
12, 13 |
|
Fedora |
44 |
|
Kylin |
11 |
|
OpenSUSE |
15 |
|
RHEL |
8, 9, 10 |
|
Rocky |
8, 9, 10 |
|
SLES |
15 |
|
SUSE |
16 |
|
Ubuntu |
22.04, 24.04, 26.04 |
|
Windows |
10, 11 |
|
arm64-sbsa |
Amazon Linux |
2023 |
Azure Linux |
3 |
|
Debian |
12, 13 |
|
Kylin |
11 |
|
RHEL |
8, 9, 10 |
|
SLES |
15 |
|
SUSE |
16 |
|
Ubuntu |
22.04, 24.04, 26.04 |
|
aarch64-jetson |
Ubuntu |
22.04 |
Additional requirements:
- Linux
NVIDIA driver >= 530.30.02
aarch64-jetson requires CUDA Toolkit >= 12.1, < 13.0
- Windows
NVIDIA driver >= 531.14
CUDA Toolkit >= 12.1
Python >= 3.9
GCC >= 14.0
cmake >= 3.18
Install nvImageCodec library#
You can download and install the appropriate built binary packages from the nvImageCodec Developer Page or install nvImageCodec Python from PyPI as it is described below.
CUDA version |
Instructions |
|---|---|
CUDA 12.x, 13.x |
|
CUDA 12.x (Tegra platforms) |
|
Install optional dependencies#
You can also install optional dependencies to run the nvjpeg, nvjpeg2k and nvtiff extensions. To install nvImageCodec with all the optional dependencies, you can do
CUDA version |
Instructions |
|---|---|
CUDA 12.x, 13.x |
|
CUDA 12.x, (Tegra platforms) |
|
Alternatively, you can specify a subset of the dependencies: nvjpeg, nvjpeg2k, nvtiff. Here are some examples:
Example |
Instructions |
|---|---|
nvjpeg2k extension support |
|
nvjpeg2k and nvtiff extension support |
|
In the following subsections, you can see how to install those dependencies manually, instead of relying on nvimagecodec’s “extra” packages.
Manual installation of nvJPEG library#
If you do not have CUDA Toolkit installed, or you would like install nvJPEG library independently, you can install it manually as a Python package
CUDA version |
Instructions |
|---|---|
CUDA 12.x, 13.x |
|
Manual installation of nvJPEG2000 library#
nvJPEG2000 library can be installed in the system, or installed as a Python package. For the latter, follow the instructions below.
CUDA version |
Instructions |
|---|---|
CUDA 12.x, 13.x |
|
CUDA 12.x (Tegra platforms) |
|
Please see also nvJPEG2000 installation documentation for more information.
Manual installation of nvTIFF library#
nvTIFF library can be installed in the system, or installed as a Python package. For the latter, follow the instructions below. Note that nvImageCodec requires nvTIFF 0.8.0 or newer. If nvTIFF is already installed, use pip install --upgrade ... to ensure the installed package satisfies this requirement.
CUDA version |
Instructions |
|---|---|
CUDA 12.x, 13.x |
|
CUDA 12.x (Tegra platforms) |
|
Please see also nvTIFF installation documentation for more information.
Manual installation of nvCOMP library#
nvCOMP library can be installed in the system, or installed as a Python package. For the latter, follow the instructions below. nvCOMP is required if you want to use nvTIFF with images that use Deflate compression.
CUDA version |
Instructions |
|---|---|
CUDA 12.x, 13.x |
|
Please see also nvCOMP installation documentation for more information.