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394 个仓库

Awesome GitHub RepositoriesDiffusion & Visual Synthesis Models

Explore 394 awesome GitHub repositories matching artificial intelligence & ml · Diffusion & Visual Synthesis Models. Refine with filters or upvote what's useful.

Awesome Diffusion & Visual Synthesis Models GitHub Repositories

用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
  • trimstray/the-book-of-secret-knowledgetrimstray 的头像

    trimstray/the-book-of-secret-knowledge

    228,641在 GitHub 上查看↗

    该项目作为一个中心化的、社区驱动的技术知识和管理资源仓库。它提供了一个结构化的分类体系,将分散的信息聚合到一个可搜索的框架中,支持系统管理员和网络安全从业者的持续学习和快速问题解决。通过映射跨越进攻性安全、基础设施管理和软件开发的资源,它为技能获取和专业参考提供了统一路径。 该项目由命令行优先的设计理念定义,优先考虑基于终端的实用程序和可脚本化的接口,以促进高效的系统管理和可重复的安全工作流。它通过平台无关的方法脱颖而出,维护在不同类 Unix 和云环境中保持适用的文档和操作指南。这种模块化的工具链集成允许用户组合针对特定管理或安全任务定制的自定义环境。 该仓库涵盖了广泛的能力领域,包括用于系统审计、网络管理和基础设施加固的综合工具包。它为网络安全技能发展提供了结构化的学习路径,范围从道德黑客实验室和渗透测试标准到漏洞评估和系统配置最佳实践。该集合还包含广泛的生产力工具、诊断实用程序和教育材料,旨在简化日常维护并增强整体安全态势。

    Generate realistic synthetic media, images, and text using advanced artificial intelligence tools.

    awesomeawesome-listbsd
    在 GitHub 上查看↗228,641
  • automatic1111/stable-diffusion-webuiAUTOMATIC1111 的头像

    AUTOMATIC1111/stable-diffusion-webui

    163,743在 GitHub 上查看↗

    Stable Diffusion Web UI is a browser-based interface designed for managing text-to-image generation tasks. It provides a centralized dashboard for controlling generative processes, including native support for multi-stage model architectures to facilitate high-quality image refinement. The platform distinguishes itself through granular control over the generation process, offering tools for precise parameter management and advanced prompt engineering. Users can customize generation styles and capabilities by integrating external model-extension formats, such as textual inversions, low-rank ad

    Centralizes image generation, model management, and configuration tasks within a unified browser-based dashboard.

    Pythonaiai-artdeep-learning
    在 GitHub 上查看↗163,743
  • huggingface/transformershuggingface 的头像

    huggingface/transformers

    161,630在 GitHub 上查看↗

    Transformers is a comprehensive library for machine learning that provides a unified interface for training, fine-tuning, and deploying transformer-based models. It supports a wide range of tasks, including text classification, language modeling, question answering, and sequence-to-sequence translation, while offering specialized architectures for both text and vision processing. The framework includes tools for managing the entire model lifecycle, from data preprocessing and tokenization to distributed training and inference. The library features extensive support for model optimization and

    Splits long prompt processing across multiple forward passes to prevent blocking other concurrent requests during generation.

    Pythonaudiodeep-learningdeepseek
    在 GitHub 上查看↗161,630
  • comfyanonymous/comfyuicomfyanonymous 的头像

    comfyanonymous/ComfyUI

    117,322在 GitHub 上查看↗

    ComfyUI is a modular generative AI workflow orchestrator and node-based GUI for designing and executing complex diffusion model pipelines. It functions as both a visual interface for building generative logic graphs and a programmable backend API that exposes diffusion model operations for external integration. The system distinguishes itself through a graph-based execution model that supports differential workflow execution, re-running only modified nodes to reduce computation. It features dynamic model offloading to manage memory between system RAM and GPU VRAM and utilizes metadata-embedde

    Designing complex generative pipelines for images, video, and audio using a modular node-based graph interface.

    Python
    在 GitHub 上查看↗117,322
  • comfy-org/comfyuiComfy-Org 的头像

    Comfy-Org/ComfyUI

    117,227在 GitHub 上查看↗

    ComfyUI is a node-based generative AI orchestration engine designed for constructing, testing, and executing complex image and video synthesis pipelines. By utilizing a directed acyclic graph execution model, the platform allows users to build reproducible workflows through modular, interconnected processing blocks without requiring manual code implementation. It serves as both a local environment for high-performance model inference and a production-ready server for deploying generative capabilities. The platform distinguishes itself through its focus on workflow portability and extensibilit

    Orchestrates multi-stage pipelines that synthesize dynamic video content from text prompts.

    Pythonaicomfycomfyui
    在 GitHub 上查看↗117,227
  • compvis/stable-diffusionCompVis 的头像

    CompVis/stable-diffusion

    73,125在 GitHub 上查看↗

    Stable Diffusion is a generative machine learning pipeline that synthesizes high-resolution visual content by performing iterative denoising within a compressed latent space. By mapping natural language embeddings into pixel outputs through conditioned probabilistic processes, the framework enables the generation of images from text prompts and the transformation of existing visual inputs based on semantic instructions. The architecture utilizes a modular execution environment that decouples model loading, scheduler logic, and inference components to support diverse hardware configurations. I

    Leverages denoising autoencoders within latent representations to synthesize detailed visual content efficiently.

    Jupyter Notebook
    在 GitHub 上查看↗73,125
  • labmlai/annotated_deep_learning_paper_implementationslabmlai 的头像

    labmlai/annotated_deep_learning_paper_implementations

    66,981在 GitHub 上查看↗

    This project is a collection of deep learning research papers translated into annotated code. It serves as a resource for reproducing academic research, providing implementations of transformers, diffusion models, and reinforcement learning architectures. The library distinguishes itself by using a side-by-side annotation format that combines executable Python code with descriptive markdown notes. This approach provides a structured way to explain the logic of neural network papers alongside their PyTorch-based implementations. The codebase covers several major capability areas, including ge

    Ships a library of generative AI models, including GANs and diffusion processes, for synthetic data and image creation.

    Pythonattentiondeep-learningdeep-learning-tutorial
    在 GitHub 上查看↗66,981
  • nexu-io/open-designnexu-io 的头像

    nexu-io/open-design

    65,830在 GitHub 上查看↗

    Open Design is an AI design orchestration platform and LLM agent workspace designed for generating prototypes, presentations, and motion graphics. It functions as a local-first environment that integrates various command-line AI agents and coding tools into a unified design workflow, allowing users to migrate design specifications into brand-compliant source code. The project is distinguished by its ability to enforce visual consistency through a design system manager that defines brand contracts and tokens using Markdown. It features a specialized motion graphics generator that converts HTML

    Provides modular sequences of processing steps to orchestrate complex AI design workflows from discovery to critique.

    TypeScriptagent-skillsai-agentsai-design
    在 GitHub 上查看↗65,830
  • keras-team/keraskeras-team 的头像

    keras-team/keras

    64,094在 GitHub 上查看↗

    Keras is a high-level deep learning framework designed for constructing and training neural networks through the composition of modular, functional layers. It serves as a comprehensive modeling toolkit that provides standardized procedures for defining, evaluating, and deploying complex architectures. By utilizing a directed acyclic graph approach, the framework allows users to build intricate models with multiple inputs, outputs, and shared layers, ensuring consistent numerical execution through functional state management. The project distinguishes itself as a multi-backend machine learning

    Initializes image synthesis models using standardized presets to ensure efficient memory management and parameter configuration during diffusion tasks.

    Pythondata-sciencedeep-learningjax
    在 GitHub 上查看↗64,094
  • microsoft/vibevoicemicrosoft 的头像

    microsoft/VibeVoice

    49,394在 GitHub 上查看↗

    VibeVoice is a generative artificial intelligence platform designed for text-to-speech synthesis. It functions as a neural audio generation framework that converts written text into natural-sounding spoken audio, specifically engineered to maintain consistent vocal characteristics and narrative prosody across extended passages of content. The system distinguishes itself through its ability to generate long-form conversational speech while preserving speaker identity and linguistic content. By utilizing latent space disentanglement, the model separates speaker traits from the input text, allow

    Uses latent space disentanglement to separate speaker identity from linguistic content for consistent voice cloning.

    Python
    在 GitHub 上查看↗49,394
  • quantumnous/new-apiQuantumNous 的头像

    QuantumNous/new-api

    39,722在 GitHub 上查看↗

    This project is an AI model API gateway and proxy server designed to provide a unified interface for interacting with diverse artificial intelligence service providers. It functions as a centralized middleware platform that routes, load balances, and translates API requests across multiple models, enabling developers to access text, image, audio, and video generation capabilities through a single, standardized integration. The gateway distinguishes itself through comprehensive administrative and financial controls, including event-driven usage accounting, real-time token consumption tracking,

    Synthesizes dynamic video content from descriptive text prompts using generative models.

    Goai-gatewayclaudedeepseek
    在 GitHub 上查看↗39,722
  • chatchat-space/langchain-chatchatchatchat-space 的头像

    chatchat-space/Langchain-Chatchat

    38,211在 GitHub 上查看↗

    Langchain-Chatchat is a system for building retrieval-augmented generation applications and autonomous AI agents. It integrates a knowledge base management system and an agent framework to enable language models to interact with private documents and execute multi-step tasks through external tools. The platform supports local deployment of language models on private infrastructure to operate without an internet connection. It includes a multimodal AI platform that combines vision models for image analysis with text-to-image generation capabilities. The system provides a web-based conversatio

    Generates images from natural language text prompts using integrated generative models.

    Pythonchatbotchatchatchatglm
    在 GitHub 上查看↗38,211
  • exacity/deeplearningbook-chineseexacity 的头像

    exacity/deeplearningbook-chinese

    37,285在 GitHub 上查看↗

    This project is a comprehensive Chinese translation of a technical deep learning textbook, providing an educational resource on the theory and implementation of neural networks. It functions as a collaborative technical translation project designed to make complex academic AI literature accessible to non-English speakers. The project utilizes a community-driven translation model that integrates external suggestions and pull requests to refine linguistic accuracy and reduce bias. It employs standardized terminology mapping to ensure a uniform vocabulary throughout the translated content. To i

    Explains how to map simple latent distributions to complex data using neural generators.

    TeX
    在 GitHub 上查看↗37,285
  • xingangpan/dragganXingangPan 的头像

    XingangPan/DragGAN

    35,822在 GitHub 上查看↗

    DragGAN is an interactive generative AI editor and GAN image editing tool designed for modifying the shape and structure of objects within images. It functions as a latent space manipulator that enables precise geometric and appearance editing by transforming images into editable latent codes. The system provides a web-based visual dashboard for real-time manipulation. Users can change the appearance of generated objects through an interactive point-based dragging interface, utilizing a process where source and target coordinates drive the optimization of the generative model. The project in

    Manipulates compressed latent representations via gradient descent to achieve specific geometric and appearance changes.

    Pythonartificial-intelligencegenerative-adversarial-networkgenerative-models
    在 GitHub 上查看↗35,822
  • microsoft/taskmatrixmicrosoft 的头像

    microsoft/TaskMatrix

    34,079在 GitHub 上查看↗

    TaskMatrix is a visual language model orchestration framework and modular visual pipeline designed to coordinate disparate foundation models. It functions as a multi-model workflow coordinator that sequences visual and textual models through logic paths to handle image processing tasks without requiring additional training. The system integrates large language models with visual foundation models to enable the exchange of image data during interactive chat sessions. It utilizes template-based orchestration to chain specialized models together for complex visual tasks. The framework supports

    Provides text-guided image editing using bounding boxes and segmentation masks to perform targeted generative inpainting.

    Python
    在 GitHub 上查看↗34,079
  • chenfei-wu/taskmatrixchenfei-wu 的头像

    chenfei-wu/TaskMatrix

    34,082在 GitHub 上查看↗

    TaskMatrix is a multimodal AI chat interface and visual task orchestrator. It combines language models with visual recognition to enable the exchange, analysis, and modification of images within a conversational environment. The system coordinates multiple foundation models through orchestration pipelines that chain language, detection, and segmentation models. This allows for complex visual operations, such as using text instructions to guide image masking and executing modular inpainting workflows to edit specific image regions. The project includes a computer vision toolset for object det

    Provides a modular workflow for modifying image regions using segmentation masks and diffusion models.

    Python
    在 GitHub 上查看↗34,082
  • huggingface/diffusershuggingface 的头像

    huggingface/diffusers

    33,872在 GitHub 上查看↗

    Diffusers is a PyTorch-based library and generative AI framework used to build, train, and deploy diffusion pipelines for producing multi-modal media. It provides a suite of tools for generating images, video, and audio from natural language descriptions, as well as specialized systems for text-to-image generation. The project differentiates itself through a modular architecture that separates noise schedulers, pretrained model blocks, and pipeline compositions. This structure allows for the construction of custom generation workflows and the ability to swap individual components of the diffu

    Provides high-resolution image generation from natural language text prompts using diffusion pipelines.

    Pythondeep-learningdiffusionflux
    在 GitHub 上查看↗33,872
  • linshenkx/prompt-optimizerlinshenkx 的头像

    linshenkx/prompt-optimizer

    30,927在 GitHub 上查看↗

    Prompt Optimizer is a framework designed for the iterative refinement and testing of text-based instructions for large language models. It functions as an automated evaluation pipeline that systematically adjusts prompt structure, constraints, and clarity to improve the accuracy and consistency of model outputs. The system distinguishes itself through a model-agnostic interface that standardizes communication across different artificial intelligence providers. It incorporates a versioned asset management system to track prompt history, enabling developers to maintain consistency and perform r

    Creates visual content from text descriptions by applying specific style parameters and model configurations.

    TypeScriptllmpromptprompt-engineering
    在 GitHub 上查看↗30,927
  • openbmb/voxcpmOpenBMB 的头像

    OpenBMB/VoxCPM

    29,985在 GitHub 上查看↗

    VoxCPM is a multilingual speech synthesis system and text-to-speech inference server. It functions as an AI voice cloning tool and a synthetic voice designer, capable of generating natural speech across global languages and regional dialects using a GPU-accelerated audio generator. The project features a speech model fine-tuning framework that supports both full parameter updates and low-rank adaptation for customizing voice characteristics. It enables high-fidelity voice cloning from reference audio, including cross-lingual voice transfer and acoustic environment mimicry, as well as the crea

    Uses a hierarchical diffusion-based autoregressive architecture to generate high-fidelity continuous speech representations.

    Pythonaudiodeeplearningminicpm
    在 GitHub 上查看↗29,985
  • sillytavern/sillytavernSillyTavern 的头像

    SillyTavern/SillyTavern

    29,463在 GitHub 上查看↗

    SillyTavern is a comprehensive interface and orchestration platform designed for immersive AI roleplay and interactive chat experiences. It functions as a unified gateway that connects users to a wide array of local and cloud-based large language models, providing a centralized environment to manage complex character personas, narrative context, and model-driven interactions. The platform distinguishes itself through its advanced prompt engineering and automation capabilities. It utilizes a sophisticated macro-based templating engine and vector-database retrieval to dynamically inject lore, c

    Produces images and spoken audio responses from AI models to enhance interactive experiences.

    JavaScriptaichatllm
    在 GitHub 上查看↗29,463
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探索子标签

  • Generation Utilities4 个子标签Auxiliary tools and modules that enhance generative AI workflows through visualization, prefilling, and model extension capabilities.
  • Generative AI Architectures1 个子标签Structural components and mechanisms, such as attention layers, that enable models to generate new content.
  • Generative AI Capabilities2 个子标签Functional capabilities that allow artificial intelligence systems to synthesize new media, such as images or audio.
  • Generative AI Models7 个子标签Pre-trained models and scheduling algorithms specifically designed for generating synthetic data, images, or complex patterns.
  • Generative AI Pipelines4 个子标签End-to-end sequences of operations that transform input data into generated media like images or video.
  • Generative AI Tasks4 个子标签Specific high-level tasks that involve the synthesis of new content from existing media inputs.
  • Generative AI Workflows5 个子标签Defined sequences of automated steps for creating and refining generative content through iterative processing.
  • Generative Models1 个子标签Statistical models capable of learning data distributions to produce new, original samples from latent spaces.
  • Synthetic Content Generators2 个子标签Systems that automatically generate new media, such as images, audio, or text, from existing data.