Awesome GitHub RepositoriesSeeded Generation

Needs to generate some texts to test if my GUI rendering codes good or not. so I made this.

Faker is a Ruby library used to generate randomized, realistic placeholder information for testing and development. It produces synthetic data to populate databases and test application logic without the use of real user information. The library provides localized data generation, using region-specific formats and strings for names, addresses, and phone numbers. It supports deterministic output through seedable random number generation, ensuring that sequences of fake data can be repeated across different test runs. The generator covers a wide range of domains, including personal identity, f

Trianglify is an algorithmic background generator and vector art toolkit used to produce pseudo-random geometric patterns and polygonal meshes. It functions as a rendering engine that converts geometric data into either scalable vector graphics or rasterized canvas elements. The system utilizes deterministic pattern generation via seed values to ensure consistent geometric output. It supports customizable color gradients, coordinate grid jittering, and custom geometry definitions to control the placement and shape of the generated meshes. The project covers algorithmic art generation and gen

Bogus is a fake data generator for .NET applications, including C#, F#, and VB.NET. It provides a deterministic mock data engine and an object configuration mapper to produce realistic profiles, addresses, and financial records. The library differentiates itself through a localization data provider that generates region-specific identifiers across various international languages and locales. It ensures reproducibility across executions by using seed values to control the sequence of generated data. The project covers wide-ranging data synthesis capabilities, including the generation of netwo

DiceBear is an SVG avatar generation library and image API that creates deterministic profile pictures from seed strings. It provides a system for generating consistent visual outputs across different environments and programming languages using JSON style definitions. The project distinguishes itself with a comprehensive design toolkit, including a visual style designer and a Figma integration plugin that converts design frames into JSON schemas. It supports sophisticated visual control through weighted probability distributions for components, contrast-aware color management for accessibili

Mockoon is an HTTP API simulation platform and design tool used to create fake API endpoints that simulate server responses without a backend. It functions as an OpenAPI mock server tool and a JSON API mocking utility, allowing for the rapid iteration of API contracts and the generation of response templates. The project distinguishes itself through a combination of stateful mocking, using a local JSON database to simulate CRUD operations, and the ability to run as a headless API mock server via a command line interface. It supports real-time collaborative editing and AI-assisted prototyping

SpaceshipGenerator is a 3D model generator and procedural asset creator designed to produce unique spaceship meshes within Blender. It functions as a procedural mesh generator that uses random seeds and configurable geometry settings to automate the creation of complex vessel designs. The tool includes a texture mapping utility that applies custom images to 3D surfaces using cube mapping to simulate reflections and window lighting. It generates diverse spacecraft shapes to support the production of science fiction concept art. The system manages the generation process through parametric hull

qrbtf is an AI QR code generator and image synthesis system that blends machine-readable data with artistic imagery. It uses a latent diffusion model and spatial control networks to produce functional QR codes that incorporate visual art generated from descriptive text prompts. The system provides a dedicated interface and programmatic API for tuning visual output, allowing for the adjustment of control strength, padding ratios, and error correction levels. It supports deterministic sampling via random seeds and the use of negative prompts to refine the final aesthetic of the generated assets

Mimesis 是一个 Python 合成数据生成器，用于为软件测试和开发创建逼真的虚假数据集和模拟数据。它作为一个基于模式的数据集生成器，能够生成结构化记录和关系数据集，同时也可作为生产数据脱敏工具，用合成值替换敏感信息。 该库的特色在于全面的多语言支持，允许生成特定区域的信息以模拟区域用户画像。它通过使用种子进行确定性数据生成来确保可重复性，从而在不同运行中创建一致的数据集。 该工具涵盖了广泛的合成内容，包括个人身份、财务数据、地理地址、网络元数据和科学序列。其功能扩展到通过条件逻辑和管道进行数据转换，以及与 DataFrame 和工厂模式的集成。它还支持生成标准化的系统代码、加密令牌和二进制文件模拟。 该框架可通过自定义数据提供程序和字段处理器进行扩展，允许用户集成特定领域的逻辑和外部 JSON 文件以进行专门的数据生成。

ComfyUI-Easy-Use is a custom node suite and workflow optimizer designed to simplify Stable Diffusion generation pipelines. It provides a set of integrated tools to reduce visual clutter and streamline the process of creating images from text and existing image references. The project distinguishes itself through a pipeline manager that consolidates models, conditioning, and latents into unified data pipes, eliminating complex wiring in the node graph. It also introduces a logical operator set that enables conditional if-else branching and for-loop structures directly within the visual program