lsding

lsding's Stars

• crewAIInc/crewAI

  Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.

  Language:Python23k3.2k

• modal-labs/quillman

  A voice chat app

  Language:Python1.1k124

• iamaziz/llm-voice-bot

  Speak (speech-to-text) to Ollama LLMs in any lanaguage - Streamlit app

  Language:Python398

• reworkd/AgentGPT

  🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.

  Language:TypeScript32.2k9.3k

• iszhouhuabo/chatgpt-next-web-fastapi

  ChatGPT-Next-Web For Python FastApi

  Language:TypeScript264

• langgenius/dify

  Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.

  Language:TypeScript56.3k8.3k

• ChatGPTNextWeb/ChatGPT-Next-Web

  A cross-platform ChatGPT/Gemini UI (Web / PWA / Linux / Win / MacOS). 一键拥有你自己的跨平台 ChatGPT/Gemini 应用。

  Language:TypeScript78k59.8k

• shibing624/chatgpt-webui

  ChatGPT WebUI using gradio. 给 LLM 对话和检索知识问答RAG提供一个简单好用的Web UI界面

  Language:Python10218

• GaiZhenbiao/ChuanhuChatGPT

  GUI for ChatGPT API and many LLMs. Supports agents, file-based QA, GPT finetuning and query with web search. All with a neat UI.

  Language:Python15.3k2.3k

• HobbitLong/RepDistiller

  [ICLR 2020] Contrastive Representation Distillation (CRD), and benchmark of recent knowledge distillation methods

  Language:Python2.2k401

• airaria/TextBrewer

  A PyTorch-based knowledge distillation toolkit for natural language processing

  Language:Python1.6k239

• mlc-ai/mlc-llm

  Universal LLM Deployment Engine with ML Compilation

  Language:Python19.5k1.6k

• Arm-China/Model_zoo

  Zhouyi model zoo

  9316

• SiliconLabs/mltk

  A Python package with command-line utilities and scripts to aid the development of machine learning models for Silicon Lab's embedded platforms

  Language:C536

• daohu527/dig-into-apollo

  Apollo notes (Apollo学习笔记) - Apollo learning notes for beginners.

  2.4k704

• zju3dv/EasyMocap

  Make human motion capture easier.

  Language:Python3.8k465

• zczcwh/DL-HPE

  48940

• qianlim/CAPE

  Official implementation of CVPR2020 paper "Learning to Dress 3D People in Generative Clothing" https://arxiv.org/abs/1907.13615

  Language:Python31440

• KevinLTT/video2bvh

  Extracts human motion in video and save it as bvh mocap file.

  Language:Python58692

• Shimingyi/MotioNet

  A deep neural network that directly reconstructs the motion of a 3D human skeleton from monocular video [ToG 2020]

  Language:Python56584

• ColbyZhuang/BVH_reader

  Language:Python31

• Dosomecrazy/video2bvh

  Extracts human motion in video and save it as bvh mocap file.

  Language:Python4715

• Jacob12138xieyuan/real-time-3d-pose-estimation-with-Unity3D

  Language:Python8726

• CalciferZh/AMCParser

  Parse and visualize asf/amc files from CMU MoCap dataset.

  Language:Python13925

• nosyarlin/YoPoCo

  Using OpenPose and a fully connected network, this project compares the user's pose and a target pose to see if the user is doing yoga correctly

  Language:Jupyter Notebook2418

• fjunqueira/pose-comparer

  An application for comparing human poses

  Language:Python161

• kr1210/Human-Pose-Compare

  Contains code on comparing actions performed by human beings and scoring them

  Language:Python9627

• boycehbz/MvSMPLfitting

  A multi-view SMPL fitting based on smplify-x

  Language:Python25228

• FORTH-ModelBasedTracker/MocapNET

  We present MocapNET, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the Human 3.6 Million (H3.6M) dataset compared to the baseline method (MocapNET) while maintaining real-time performance

  Language:C++867137

• inisis/brocolli

  Everything in Torch Fx

  Language:Python34164