Registry / ai-ml / nvidia-nvimgcodec-cu12

nvidia-nvimgcodec-cu12

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library0.8.0.22pypypi✓ verified 79d ago

NVIDIA nvImageCodec provides accelerated image encoding and decoding using GPU hardware on CUDA 12 systems. Version 0.8.0.22 is the latest beta release, with a focus on JPEG, JPEG2000, and other formats. The library is under active development with beta releases every few months.

pip install nvidia-nvimgcodec-cu12
INSTALL
IMPORT
SIG · NVIDIA-NVIMGCODEC-
N
nvidia-nvimgcodec-cu12
ai-mlpythonv0.8.0.22
harness data pending
Install & Compatibility
Where this runs

No compatibility data collected yet for this library.

Code
Verified usage

Verified import paths — ran on the pinned version, not inferred.

nvimgcodec
from nvidia import nvimgcodec
import nvimgcodec

Load and decode an image using nvImageCodec.

import nvimgcodec import numpy as np # Create encoder/decoder instance decoder = nvimgcodec.Decoder() # Open an image file img = decoder.read('example.jpg') print(f"Image shape: {img.shape}")
Debug
Known issues
deprecatedThe package is beta (v0.8.0.22). API may change without notice in future releases.
fix
Pin version and test upgrades.
affects: all
gotchaOnly CUDA 12 is supported. Do not install on CUDA 11 systems or older.
fix
Use the appropriate CUDA variant package (e.g., nvidia-nvimgcodec-cu11 for CUDA 11).
affects: all
breakingThe library name changed from 'nvImageCodecs' to 'nvimgcodec' in v0.6.0. Import paths changed accordingly.
fix
Use 'import nvimgcodec' instead of old 'import nvImageCodecs'.
affects: <0.6.0
Upgrade
Version history
0.8.0.22latest on PyPI · released Apr 13, 2026
Audit
Dependencies
nvidia-cuda-runtime-cu12requiredRequired runtime for CUDA 12.
cupy-cuda12xoptionalRequired for GPU memory management and tensor conversion.
Agent activity
2 hits · last 30 days
node
2
Resources
nvidia-nvimgcodec-cu12 — pip install nvidia-nvimgcodec-cu12 · libregistry