Popular GitHub Repositories for Synthetic Time Series

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

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.

?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

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

Real-time face swap for PC streaming or video calls

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.

This repository is primarily maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), artificial intelligence security, vulnerability research, exploit development, reverse engineering, and more.

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

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

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

Supercharge your workflow automation with this curated collection of n8n templates! Instantly connect your favorite apps-like Gmail, Telegram, Google Drive, Slack, and more-with ready-to-use, AI-powered automations. Save time, boost productivity, and unlock the true potential of n8n in just a few clicks.

Code for Machine Learning for Algorithmic Trading, 2nd edition.

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.

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

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

A Library for Advanced Deep Time Series Models.

Fast and Accurate ML in 3 Lines of Code