Popular GitHub Repositories for Real Time Rendering

real time face swap and one-click video deepfake with only a single image

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

Clone a voice in 5 seconds to generate arbitrary speech in real-time

GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

?AI拟声: 5秒内克隆您的声音并生成任意语音内容 Clone a voice in 5 seconds to generate arbitrary speech in real-time

The first real AI developer

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

Real-time face swap for PC streaming or video calls

Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.

Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. ?Docker-friendly.?Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.

Filament是一个实时物理渲染引擎，支持Android、iOS、Windows、Linux、macOS和WebGL2平台。

Turns Data and AI algorithms into production-ready web applications in no time.

Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"

Video, Image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, Real-CUGAN, RTX Video Super Resolution VSR, SRMD, RealSR, Anime4K, RIFE, IFRNet, CAIN, DAIN, and ACNet.

A toolkit for making real world machine learning and data analysis applications in C++

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Open source AI coding agent. Designed for large projects and real world tasks.

RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.