yoshiweb's starred repositories
Auto-Photoshop-StableDiffusion-Plugin
A user-friendly plug-in that makes it easy to generate stable diffusion images inside Photoshop using either Automatic or ComfyUI as a backend.
diffusionbee-stable-diffusion-ui
Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed.
stable-diffusion-webui
Stable Diffusion web UI
tfjs_webgl_app
Realtime TensorFlow.js + WebGL visualization apps. 3D Hand pose estimation, 3D Human pose estimation, Face swap, Depth estimation, Higher accuracy face detection.
automator-workflows
A collection of Automator workflows (services) that speed up your design / development process. Compatible with LaunchBar 6 actions
page-transitions-travelapp
Travel App, Native-like Page Transitions
medical-ai-course-materials
メディカルAIコース オンライン講義資料
pytorch-pix2pix
a fork of pytorch-pix2pix
WebAssemblyStudio
Learn, Teach, Work and Play in the WebAssembly Studio
AutonomousDrivingCookbook
Scenarios, tutorials and demos for Autonomous Driving
JapaneseTokenizers
aim to use JapaneseTokenizer as easy as possible
neural_ime
Neural IME: Neural Input Method Engine
advent-calendar-2017
データ分析勉強用 advent calendar (https://adventar.org/calendars/2631) リポジトリ
liteaccount-conversation-bot-sample
IBM Cloud (Bluemix) のライト・アカウントで作成可能なチャットボット・アプリケーションのサンプルコードをご紹介します。 お客様の顔色(感情)を読み取り、対応内容を変化させるシナリオを想定しています。チャットボットのフレームワークにIBM Watson Conversationサービス、感情の分析にIBM Watson Tone Analyzerサービスを利用します。IBM Cloudライト・アカウントの登録はこちらから。https://console.bluemix.net/registration/free
Deep-Image-Analogy
The source code of 'Visual Attribute Transfer through Deep Image Analogy'.
chainer-fast-neuralstyle-models
Models for the chainer fast neuralstyle
chainer-fast-neuralstyle
Chainer implementation of "Perceptual Losses for Real-Time Style Transfer and Super-Resolution".
rcnn-text-classification
Recurrent Conventinal NN Text Classification for chainer
deep-learning-book
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"