Extension of PyAV (ffmpeg bindings) with hardware decoding support. Compatible with PyTorch and Nvidia codecs.
MIT License
Provide Docker build sequences of PyTorch for various environments.
Unifying Python/C++/CUDA memory: Python buffered array ↔️ `std::vector` ↔️ CUDA managed memory
Python library for fast time-series analysis on CUDA GPUs
A nvImageCodec library of GPU- and CPU- accelerated codecs featuring a unified interface
Goal: Low power cluster capable of serving 24+ streams of 4KHDR60 source transcodes while consumi...
Computer vision library with focus on heterogeneous systems
Provide Docker build sequences of Open3D for various environments.
Simple tests for JAX, PyTorch, and TensorFlow to test if the installed NVIDIA drivers are being p...
Archlinux PKGBUILDs for Data Science, Machine Learning, Deep Learning, NLP and Computer Vision
Object detection for video surveillance
Decoding Attention is specially optimized for multi head attention (MHA) using CUDA core for the ...
Provides an environment for compiling TensorFlow or PyTorch with CUDA for aarch64 on an x86 machi...
Performance-optimized wheels for TensorFlow (SSE, AVX, FMA, XLA, MPI)
A CLI tool which lets you install proprietary NVIDIA drivers and much more easily on Fedora Linux...
VUDA is a header-only library based on Vulkan that provides a CUDA Runtime API interface for writ...