Artificial Intelligence(12)
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Offline Standalone(local) Mac(Apple Silicon M1, M2) Installer for Stable Diffusion Web UI (unofficial) 20230330 Pre-release
An offline standalone(local) Mac(Apple Silicon M1, M2) installer for a slightly modified version of AUTOMATIC1111's Stable Diffusion Web UI. It changes have been applied to AUTOMATIC1111@a9fed7c from https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/a9fed7c364061ae6efb37f797b6b522cb3cf7aa2 Releases · brkirch/stable-diffusion-webui (github.com) Releases · brkirch/stable-diffusion-web..
2023.04.03 -
Run Stable Diffusion on Mac Silicon M1, M2 with CoreML v0.3.0 Released
A. How to run Stable Diffusion on Mac Silicon M1, M2 with CoreML v0.3.0 Released By optimizing CoreML for stable diffusion and simplifying model transformations, developers can more easily use machine learning hardware in their apps in a way that is both privacy and costeffective while achieving optimal performance on Apple Silicon Mac M1 and M2. B. Release Notes v0.3.0 ml-stable-diffusion / ima..
2023.03.29 -
2D image to 3D model (mesh) AI free : Point E
Point E : Automatically convert 2D image to 3D object modeling mesh with AI. Powered by machine-learning algorithms, this enables developers to create their 3D modeling mesh in a quick and free. This image-to-3D model was fed a set of images paired with 3D objects mesh so that it learned to effectively translate. GitHub - openai/point-e: Point cloud diffusion for 3D model synthesis GitHub - open..
2022.12.21 -
InvokeAI 2.2.4 (2022-12-12) Release
InvokeAI is a fork of CompVis/stable-diffusion, the open source text-to-image generator. It provides a streamlined process with various new features and options to aid the image generation process. It runs on Windows, Apple MacOS and Linux. It provides both a polished web interface(Web-UI), and a command-line interface. Getting Started with InvokeAI 1. Windows 1-1. Download for Windows https://g..
2022.12.13 -
hand style : dall-e2 vs stable diffusion
hand style : dall-e2 vs stable diffusion Dall-e2가 스탁 이미지 등 명확한 표현을 보장하는 데이터셋이 4배 정도 더 많고, Stable Diffusion의 Default CFG가 손 모양 표현에 적합하지 않기 때문에, Stable Diffusion에서 손 모양을 개선하는 방법은 손에 대한 표현이 풍부한 라벨링 데이터, 손 모양에 대한 스타일 데이터셋의 충분량 필요, 그리고 손이나 발 모양 표현에 적합한 Steps와 CFG로 설정하는 것이 좋다. 다음은 Stable Diffusion 2.1에서 많은 개선이 이뤄졌다는 손 모양에 대한 여러가지 출력결과(개선된 로직이 동일 데이터셋 문제로 인하여 개선의 정도를 알 수 없을 정도..) Stable Diffusion 2.1 p..
2022.12.11