为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, m…

Wechat Chat History Exporter 微信聊天记录导出备份程序

Implementation of popular deep learning networks with TensorRT network definition API

chinese tts

Unofficial Parallel WaveGAN (+ MelGAN & Multi-band MelGAN & HiFi-GAN & StyleMelGAN) with Pytorch

😝 TensorFlowTTS: Real-Time State-of-the-art Speech Synthesis for Tensorflow 2 (supported including English, French, Korean, Chinese, German and Easy to adapt for other languages)

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

（已过时）中文语音合成，改自 https://github.com/Rayhane-mamah/Tacotron-2 和 https://github.com/begeekmyfriend/Tacotron-2

PyTorch reimplementation of Tacotron2 in Mandarin

LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

Machine learning, in numpy

Official implementation of CVPR2020 paper "VIBE: Video Inference for Human Body Pose and Shape Estimation"

船长关于机器学习、计算机视觉和工程技术的总结和分享

CVPR 2024 论文和开源项目合集

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

In this project, I've built a facial keypoint detection model using various computer vision techniques as well as deep learning architectures which take in an image of a human face and predicts the…

A simplified implemention of Faster R-CNN that replicate performance from origin paper

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

《可解释的机器学习--黑盒模型可解释性理解指南》，该书为《Interpretable Machine Learning》中文版

List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.

This is a list of awesome methods about data augmentation.

This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.