zhaoyk1986 Goto Github PK

followers: 3.0 following: 118.0 repos: 267.0 gists: 0.0

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zhaoyk1986's Projects

transformers

🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

tts

:robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)

tts-1

🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

u-2-net

The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

ugatit-pytorch

Official PyTorch implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation

ultra-light-fast-generic-face-detector-1mb

💎1MB lightweight face detection model (1MB轻量级人脸检测模型)

unet-stylegan2

A Pytorch implementation of Stylegan2 with UNet Discriminator

uvcgan2

UVCGAN v2: An Improved Cycle-Consistent GAN for Unpaired Image-to-Image Translation

v2ray-core

A platform for building proxies to bypass network restrictions.

v2rayu

V2rayU,基于v2ray核心的mac版客户端,用于科学上网,使用swift4.2编写,支持vmess,shadowsocks,socks5等服务协议,支持订阅, 支持二维码,剪贴板导入,手动配置,二维码分享等

vibe

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

videofilter

play and save video with gpu filter

vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

vnn

VNN是由欢聚集团(Joyy Inc.)推出的高性能、轻量级神经网络部署框架。目前已为Hago、VOO、VFly、马克相机等App提供20余种AI能力的支持，覆盖直播、短视频、视频编辑等泛娱乐场景和工程场景

vtoonify

[SIGGRAPH Asia 2022] VToonify: Controllable High-Resolution Portrait Video Style Transfer

vulkan

Examples and demos for the new Vulkan API

waifu2x

PyTorch on Super Resolution

waifu2x-ncnn-vulkan

waifu2x converter ncnn version, runs fast on intel / amd / nvidia GPU with vulkan

wasserstein-style-transfer

Performs style transfer by defining the style loss as the Wasserstein distance between the distribution of the the style image features and the generated image features.