Search Results for "visual-" - Page 3
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Showing 530 open source projects for "visual-"
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Book4_Power-of-Matrix
Book_4_Matrix Power | The Iris Book: From Addition, Subtraction
Book4_Power-of-Matrix is an open educational repository that forms part of the Visualize-ML book series, focusing on explaining matrix mathematics and linear algebra concepts through visual and intuitive methods. The project is designed to help readers progress from basic arithmetic toward machine learning fundamentals by building a strong conceptual understanding of vectors, matrices, and their operations. It combines explanatory text, diagrams, and Python examples to bridge theory and practical computation. The material emphasizes geometric interpretation and visual reasoning, which makes abstract linear algebra topics more accessible to beginners and self-learners. ... -
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claude-video
Give Claude the ability to watch any video
...The workflow checks captions first, downloads only what is necessary, extracts timestamped frames, and produces a transcript through native captions or Whisper fallback. It supports different detail levels so users can trade speed, token cost, and visual coverage depending on the task. The skill is useful for summarizing videos, reviewing screen recordings, analyzing content structure, diagnosing visual bugs, and turning course material into notes. It can be installed through Claude Code, agent skill hosts, claude.ai, or manual setup. -
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Watermark-Removal
Machine learning image inpainting task that removes watermarks
Watermark-Removal repository is a machine learning project focused on removing visible watermarks from digital images using deep learning and image inpainting techniques. The system analyzes an image containing a watermark and attempts to reconstruct the underlying visual content so that the watermark is removed while preserving the original appearance of the image. The project uses neural network models inspired by research in contextual attention and gated convolution, which are methods commonly applied to image restoration tasks. Through these techniques, the model learns to identify regions of the image affected by the watermark and generate realistic replacements for the missing visual information. ... -
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GPT-Image2-Skill
GPT Image 2 prompt gallery, image prompt library, agentic skill
GPT-Image2-Skill is a prompt gallery, image prompt library, agent skill, and CLI for OpenAI image generation and editing workflows. It collects curated prompt examples with generated outputs so users can reuse strong visual patterns instead of starting from scratch. The project includes categories such as anime, gaming, cyberpunk, animation, character design, typography, illustration, watercolor, ink, pixel art, isometric scenes, product visuals, and food imagery. It can be installed as an agent skill for supported runtimes or used through a local CLI. ... -
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VideoRAG
"VideoRAG: Chat with Your Videos
VideoRAG is a retrieval-augmented generation (RAG) framework tailored for video content that enables AI systems to answer questions, summarize, and reason over long videos by combining visual embeddings with contextual search. The system works by first breaking video into clips, extracting visual and audio-textual features, and indexing them into embeddings, then using an LLM with a retriever to pull relevant segments on demand. When a user query is received, VideoRAG locates semantically relevant moments in the video using the embedding index, retrieves associated clips or transcripts, and feeds them to a generative model to produce accurate, grounded answers or summaries. ... -
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Super Magic
All-in-one AI productivity platform with agents, workflows, and IM
...Magic centers around a general-purpose AI agent system called Super Magic, which can autonomously understand tasks, plan actions, execute workflows, and perform error correction. Alongside this, Magic includes a visual workflow engine that enables users to design complex AI processes using a drag-and-drop interface without requiring extensive coding knowledge. It also provides an enterprise-grade instant messaging system that integrates AI conversations with internal communication, allowing teams to collaborate while leveraging intelligent assistants. ... -
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PaperBanana
Extension of Google Research’s PaperBanana
PaperBanana is an open-source agentic framework designed to automatically generate publication-quality academic diagrams and statistical plots directly from text descriptions. The project focuses on helping researchers, educators, and data scientists transform conceptual descriptions of figures into structured visual outputs suitable for research papers, presentations, and technical reports. Instead of manually designing charts or diagrams using traditional visualization tools, users can describe the desired figure in natural language and allow the system to generate the visual representation automatically. PaperBanana integrates modern multimodal AI models capable of interpreting instructions and producing graphics that follow academic conventions. ... -
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FramePack
Lets make video diffusion practical
FramePack explores compact representations for sequences of image frames, targeting tasks where many near-duplicate frames carry redundant information. The idea is to “pack” frames by detecting shared structure and storing differences efficiently, which can accelerate training or inference on video-like data. By reducing I/O and memory bandwidth, datasets become lighter to load while models still see the essential temporal variation. The repository demonstrates both packing and unpacking... -
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claude-real-video
Let Claude (or any LLM) actually watch a video
...It is useful for reviewing screen recordings, summarizing visual content, analyzing tutorials, and turning video into LLM-readable context. -
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Qtile
A full-featured, hackable tiling window manager written in Python
A full-featured, hackable tiling window manager written and configured in Python. Optimize your workflow by configuring your environment to fit how you work. Efficiently use screen real-estate by automatically arranging windows with minimal visual cruft. Save your wrists from RSI by ditching the mouse and driving with the keyboard. Qtile is simple, small, and extensible. It's easy to write your own layouts, widgets, and built-in commands. Qtile is written and configured entirely in Python. Leverage the full power and flexibility of the language to make it fit your needs. The Qtile community is active and growing. ... -
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VOID-TOOLS
OSINT, Discord, web & network utilities
VOID-TOOLS is a Python terminal multitool suite for OSINT, Discord, web, network, social, Roblox, and utility workflows. It is built around a Rich-powered terminal dashboard with keyboard navigation, a cinematic boot flow, category panels, and a live sidebar. The tool organizes many modules into categories and marks premium tools separately from free ones. It includes bilingual setup, theme selection, fuzzy search, category filters, custom plugin loading, and remote manifest updates. The... -
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AppAgent
Multimodal Agents as Smartphone Users, an LLM-based multimodal agent
AppAgent is an open-source multimodal agent framework designed to enable large language models to operate smartphone applications through natural interactions with graphical user interfaces. The system allows an AI agent to interpret visual information from the screen and translate natural language instructions into actions such as tapping, swiping, and navigating between application screens. Instead of requiring backend access to application APIs, the framework interacts with apps the same way a human user would, making it compatible with a wide variety of mobile applications. ... -
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LLM Vision
Visual intelligence for your home.
...The project enables Home Assistant to analyze images, video files, and live camera feeds using vision-capable AI models. Instead of relying only on traditional object detection pipelines, it allows users to send prompts about visual content and receive contextual descriptions or answers about what is happening in camera footage. The system can process events from surveillance platforms such as Frigate and convert them into meaningful summaries, notifications, or structured data for automation workflows. It also maintains a timeline of analyzed camera events that can be displayed in dashboards or queried through the assistant interface. -
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Wan2.1
Wan2.1: Open and Advanced Large-Scale Video Generative Model
Wan2.1 is a foundational open-source large-scale video generative model developed by the Wan team, providing high-quality video generation from text and images. It employs advanced diffusion-based architectures to produce coherent, temporally consistent videos with realistic motion and visual fidelity. Wan2.1 focuses on efficient video synthesis while maintaining rich semantic and aesthetic detail, enabling applications in content creation, entertainment, and research. The model supports text-to-video and image-to-video generation tasks with flexible resolution options suitable for various GPU hardware configurations. ... -
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Frontend Slides
Create beautiful slides on the web using Claude's frontend skills
Frontend Slides is a lightweight tool that enables users to create visually appealing, animation-rich web presentations without requiring knowledge of CSS or JavaScript by leveraging a guided, interactive workflow. It operates on a “show, don’t tell” philosophy, generating visual previews of styles so users can select their preferred design rather than describing it abstractly. The system produces fully self-contained HTML presentations with inline CSS and JavaScript, eliminating the need for external dependencies, build tools, or frameworks. It also supports converting existing PowerPoint files into web-based presentations while preserving content such as images, text, and structure. ... -
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dnstwist
Detects phishing and lookalike domains using DNS fuzzing techniques
...Security teams can use the tool to discover potential threats where attackers attempt to deceive users with lookalike domains. dnstwist also helps detect phishing activity by comparing web page content and visual similarity between domains using fuzzy hashing and perceptual hashing techniques. By automating DNS fuzzing and analysis, it provides organizations with an additional source of targeted threat intelligence. The tool can output results in structured formats, making it easier to integrate with security workflows or further analyze suspicious domains. -
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VOID
Video Object and Interaction Deletion
VOID is an advanced AI video processing system developed by Netflix that focuses on removing objects from videos while preserving the physical and visual realism of the surrounding environment. Unlike traditional inpainting methods that only erase pixels or simple artifacts, VOID models the full interaction dynamics between objects and their environment, including shadows, reflections, and even physical consequences such as movement or balance changes. Built on top of transformer-based architectures and fine-tuned for video inpainting tasks, the system uses interaction-aware mask conditioning to ensure temporal consistency across frames. ... -
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machine-learning-refined
Master the fundamentals of machine learning, deep learning
machine-learning-refined is an educational repository designed to help students and practitioners understand machine learning algorithms through intuitive explanations and interactive examples. The project accompanies a series of textbooks and teaching materials that focus on making machine learning concepts accessible through visual demonstrations and simple code implementations. Instead of presenting algorithms purely through mathematical derivations, the repository emphasizes geometric intuition, visualization, and step-by-step experimentation. It includes Jupyter notebooks and scripts that illustrate core machine learning topics such as regression, classification, optimization methods, and neural networks. ... -
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DeepWiki Open
AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories
...Users can enter a repository URL and the system will clone the project, build semantic embeddings of its codebase, extract architecture and relationships, generate human-readable documentation, and produce visual diagrams to help explain complex code structure. DeepWiki’s output turns raw repositories into interactive, web-style wikis complete with navigable sections, diagrams, and contextual explanations, making it easier for developers and collaborators to understand unfamiliar code. It includes an “Ask” feature that lets users query the generated wiki using RAG-style retrieval, enabling interactive question-answering and exploration. -
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LatentSync
Taming Stable Diffusion for Lip Sync
...The system leverages a U-Net diffusion backbone, with cross-attention of audio embeddings (via an audio encoder) and reference video frames to guide generation, and applies a set of loss functions (temporal, perceptual, sync-net based) to enforce lip-sync accuracy, visual fidelity, and temporal consistency. Over versions, LatentSync has improved temporal stability and lowered resource requirements — making inference more practical (e.g. 8 GB VRAM for earlier versions, somewhat higher for latest models). -
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CyberPPT
A Codex Skill for generating high-density, editable PowerPoints
...It extracts facts, numbers, claims, recommendations, conflicts, and caveats from formats such as PDF, DOCX, TXT, and XLSX. The workflow builds an MBB-style evidence table before developing storylines and converging on an SCR narrative. Users select from eight fixed visual systems, after which the skill plans each slide’s hierarchy, grid, charts, palette, and information density. Image-generation blueprints guide reconstruction while native text, shapes, tables, charts, and vectors preserve core editability. Multiple quality gates inspect structure, visuals, overflow, spatial alignment, curves, and editable elements. ... -
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DriveLM
Driving with Graph Visual Question Answering
DriveLM is a research-oriented framework and dataset designed to explore how vision-language models can be integrated into autonomous driving systems. The project introduces a new paradigm called graph visual question answering that structures reasoning about driving scenes through interconnected tasks such as perception, prediction, planning, and motion control. Instead of treating autonomous driving as a purely sensor-driven pipeline, DriveLM frames it as a reasoning problem where models answer structured questions about the environment to guide decision making. ... -
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LISA
LISA: Reasoning Segmentation via Large Language Model
...The project introduces a framework where a large language model can interpret natural language instructions and produce segmentation masks that highlight relevant regions in an image. Instead of relying solely on predefined object categories, the model is capable of reasoning about complex textual queries and translating them into visual segmentation outputs. This approach allows the system to identify objects or regions in images based on semantic descriptions, contextual reasoning, and world knowledge. The model integrates multimodal capabilities by combining language understanding with visual perception so that text instructions guide the segmentation process. ... -
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FastVLM
This repository contains the official implementation of FastVLM
...The repository documents model variants, showcases head-to-head numbers against known baselines, and explains how the encoder integrates with common LLM backbones. Apple’s research brief frames FastVLM as targeting real-time or latency-sensitive scenarios, where lowering visual token pressure is critical to interactive UX. In short, it’s a practical recipe to make VLMs fast without exotic token-selection heuristics. -
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ML Ferret
Refer and Ground Anything Anywhere at Any Granularity
Ferret is Apple’s end-to-end multimodal large language model designed specifically for flexible referring and grounding: it can understand references of any granularity (boxes, points, free-form regions) and then ground open-vocabulary descriptions back onto the image. The core idea is a hybrid region representation that mixes discrete coordinates with continuous visual features, so the model can fluidly handle “any-form” referring while maintaining precise spatial localization. The repo presents the vision-language pipeline, model assets, and paper resources that show how Ferret answers questions, follows instructions, and returns grounded outputs rather than just text. In practice, this enables tasks like “find that small red icon next to the chart and describe it” where both the linguistic reference and the visual region are ambiguous without fine spatial reasoning.