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#1
davidrmiller
/
biosim4
Biological evolution simulator
biosim4
Status
This project is transitioning to maintenance-only. Thanks to all who contributed improvements to this project. We will continue to welcome bug fixes that enable this program to compile and execute, and we welcome discussions about this program and related topics in the Issues section.
What is this?
This pile of code was used to simulate biological creatures that evolve through natural selection. The results of the experiments are summarized in this YouTube video:
"I programmed some creatures. They evolved."
https://www.youtube.com/watch?v=N3tRFayqVtk
This command line program lacks a friendly interface, so compiling and executing the program may require attention to details. If you ask questions in the Issues, I'll try to help if I can. For a nicer user interface, check out the fork of this project hosted by @ilyabrilev.
Document Contents
#2
AppFlowy-IO
/
AppFlowy
Bring projects, wikis, and teams together with AI. AppFlowy is the AI collaborative workspace where you achieve more without losing control of your data. The leading open source Notion alternative.
AppFlowy
⭐️ The Open Source Alternative To Notion ⭐️
AppFlowy is the AI workspace where you achieve more without losing control of your data
Website • Forum • Discord • Reddit • Twitter
User Installation
- Download AppFlowy Desktop (macOS, Windows, and Linux)
- Other channels: FlatHub, Snapcraft, Sourceforge
- Available on
- App Store: iPhone
- Play Store: Android 10 or above; ARMv7 is not supported
- Self-hosting AppFlowy
- Source
Built With
Stay Up-to-Date
Getting Started with development
Please view the documentation for OS specific development instructions
Roadmap
If you'd like to propose a feature, submit a feature
request here
If you'd like to report a bug, submit a bug
report here
Releases
Please see the changelog for more details about a given release.
Contributing
Contributions make the open-source community a fantastic place to learn, inspire, and create. Any contributions you make are…
#3
Build infinite canvas apps in React with the tldraw SDK
Docs · Examples · Starter kits
Feature highlights
tldraw provides a feature-complete infinite canvas engine designed to be the foundation for any canvas app. Create custom shapes, tools, bindings and UI components for a custom experience. Use the default whiteboarding tool set or use the library's primitives to build entirely new shapes and interactions.
-
Multiplayer — self-hostable real-time collaboration with
@tldraw/sync - Drawing and diagramming — pressure-sensitive drawing, geometric shapes, rich text, arrows, snapping to shapes, edge scrolling, image and video support, image export
- Runtime API - drive the canvas at runtime with the Editor API
- Fully extensible — custom shapes, tools, bindings, UI components, side effects, and event hooks
- AI integrations — canvas primitives for building with LLMs
- DOM canvas — web rendering supports anything the browser supports, including embedded websites from YouTube, Figma, GitHub, and…
#4
Medusa
Building blocks for digital commerce
Getting Started
The fastest way to get started is with Medusa Cloud. It provides a managed environment optimized for Medusa applications, with automated deployments, scaling, and maintenance. Get started on Medusa Cloud
To set up a Medusa application locally, visit the Documentation.
About Medusa
Medusa is a commerce platform with a built-in framework for customization that allows you to build custom commerce applications without reinventing core commerce logic. The framework and modules can be used to support advanced B2B or DTC commerce stores, marketplaces, distributor platforms, PoS systems, service businesses, or similar solutions that need foundational commerce primitives. All commerce modules are open-source and freely available on npm.
Learn more about Medusa’s architecture and commerce modules in the Docs.
Upgrades & Integrations
Follow the Release Notes to keep your Medusa project up-to-date.
Check out all available Medusa integrations.
#5
ava-labs
/
avalanchego
Go implementation of an Avalanche node.
Node implementation for the Avalanche network - a blockchains platform with high throughput, and blazing fast transactions.
Installation
Avalanche is an incredibly lightweight protocol, so the minimum computer requirements are quite modest Note that as network usage increases, hardware requirements may change.
The minimum recommended hardware specification for nodes connected to Mainnet is:
- CPU: Equivalent of 8 AWS vCPU
- RAM: 16 GiB
- Storage: 1 TiB
- Nodes running for very long periods of time or nodes with custom configurations may observe higher storage requirements.
- OS: Ubuntu 22.04/24.04 or macOS >= 12
- Network: Reliable IPv4 or IPv6 network connection, with an open public port.
If you plan to build AvalancheGo from source, you will also need the following software:
Building From Source
Clone The Repository
Clone the AvalancheGo repository:
git clone git@github.com:ava-labs/avalanchego.git
cd avalanchego
This will clone and checkout the master branch.
Building AvalancheGo
Build AvalancheGo…
#6
TachibanaYoshino
/
AnimeGANv2
[Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime
AnimeGANv2
The improved version of AnimeGAN.
Project Page | Landscape photos / videos to anime
News
- (2022.08.03) Added the AnimeGANv2 Colab: 🖼️ Photos
| 🎞️ Videos
- (2021.12.25) AnimeGANv3 has been released. 🎄
- (2021.02.21) The pytorch version of AnimeGANv2 has been released, Be grateful to @bryandlee for his contribution.
- (2020.12.25) AnimeGANv3 will be released along with its paper in the spring of 2021.
Focus:
| Anime style | Film | Picture Number | Quality | Download Style Dataset |
|---|---|---|---|---|
| Miyazaki Hayao | The Wind Rises | 1752 | 1080p | Link |
| Makoto Shinkai | Your Name & Weathering with you | 1445 | BD | |
| Kon Satoshi | Paprika | 1284 | BDRip |
News:
The improvement directions of AnimeGANv2 mainly include the following 4 points:
-
1. Solve the problem of high-frequency artifacts in the generated image.
-
2. It is easy to train and directly achieve the effects in the paper.
-
3. Further reduce the number of parameters of the generator network. (generator size: 8.17 Mb)…
#7
jaakkopasanen
/
AutoEq
Automatic headphone equalization from frequency responses
AutoEq
AutoEq is a tool for automatically equalizing headphones.
Go to autoeq.app to get started.
This Github repository now mainly serves developers. The contributions of this project are:
- Web application for easily equalize and tweak headphone frequency responses without needing to install anything
- Library for working with (headphone) frequency responses and optimizing parametric equalizers
- PyPi package for installing the library on your projects
- Collection of headphone measurements as numerical data from oratory1990 crinacle Innerfidelity, Rtings and legacy headphone.com measurements (which are not the same as what the company produces today).
- Collection of different headphone frequency response targets as numerical data
- Pre-computed equalizer settings in results, although these should not be used by normal users since autoeq.app exists
Sennheiser HD 800 equalization results plotted
Updates
2023-10-29 AutoEq version 4.0.0. Improved and unified naming conventions across the project. Cleaned up obsolete files and reorganized directory structure. Completely reworked…
#8
rougier
/
scientific-visualization-book
An open access book on scientific visualization using python and matplotlib
Scientific Visualization: Python + Matplotlib
Nicolas P. Rougier, Bordeaux, November 2021.
The Python scientific visualisation landscape is huge. It is composed of a myriad of tools, ranging from the most versatile and widely used down to the more specialised and confidential. Some of these tools are community based while others are developed by companies. Some are made specifically for the web, others are for the desktop only, some deal with 3D and large data, while others target flawless 2D rendering. In this landscape, Matplotlib has a very special place. It is a versatile and powerful library that allows you to design very high quality figures, suitable for scientific publishing. It also offers a simple and intuitive interface as well as an object oriented architecture that allows you to tweak anything within a figure. Finally, it can be used as a regular graphic library in order to design non‐scientific figures. This…
#9
google
/
filament
Filament is a real-time physically based rendering engine for Android, iOS, Windows, Linux, macOS, and WebGL2
Filament
Filament is a real-time physically based rendering engine for Android, iOS, Linux, macOS, Windows and WebGL. It is designed to be as small as possible and as efficient as possible on Android.
Download
Download Filament releases to access stable builds. Filament release archives contains host-side tools that are required to generate assets.
Make sure you always use tools from the same release as the runtime library. This is particularly
important for matc (material compiler).
If you'd rather build Filament yourself, please refer to our build manual.
Android
Android projects can simply declare Filament libraries as Maven dependencies:
repositories {
// ...
mavenCentral()
}
dependencies {
implementation 'com.google.android.filament:filament-android:1.71.0'
}
Here are all the libraries available in the group com.google.android.filament:
| Artifact | Description |
|---|---|
 |
The Filament rendering engine itself. |
 |
Debug version of filament-android. |
 |
A glTF 2.0 loader for Filament, depends on filament-android. |
 |
KTX loading, Kotlin math, and |
#10
ardalis
/
CleanArchitecture
Clean Architecture Solution Template: A proven Clean Architecture Template for ASP.NET Core 10
Clean Architecture
A starting point for Clean Architecture with ASP.NET Core. Clean Architecture is just the latest in a series of names for the same loosely-coupled, dependency-inverted architecture. You will also find it named hexagonal, ports-and-adapters, or onion architecture.
Learn more about Clean Architecture and this template in NimblePros' Introducing Clean Architecture course. Use code ARDALIS to save 20%.
This architecture is used in the DDD Fundamentals course by Steve Smith and Julie Lerman.
🏫 Contact Steve's company, NimblePros, for Clean Architecture or DDD training and/or implementation assistance for your team.
Take the Course!
Learn about how to implement Clean Architecture from NimblePros trainers Sarah "sadukie" Dutkiewicz and Steve "ardalis" Smith.
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