Showing 4 open source projects for "visual code"

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    StarVector

    StarVector

    StarVector is a foundation model for SVG generation

    ...This approach allows StarVector to create scalable graphics that maintain visual quality regardless of resolution, which is especially useful for design tools and illustration workflows. Because the model produces SVG code rather than pixel images, the output can be edited programmatically or integrated directly into web and design environments.
    Downloads: 0 This Week
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  • 2
    claude-real-video

    claude-real-video

    Let Claude (or any LLM) actually watch a video

    claude-real-video is a local video processing tool that prepares videos for analysis by Claude or other LLMs. It accepts public video URLs or local files and extracts the visual and audio evidence an AI model needs. Instead of sampling at a fixed interval, it detects scene changes and removes near-duplicate frames to reduce unnecessary token usage. It can transcribe audio, generate a clean output folder, and create a local viewer with the video, keyframe grid, and transcript. The tool can also be installed as a Claude Code skill so an agent can process videos more directly. ...
    Downloads: 3 This Week
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  • 3
    AI-Codereview-Gitlab

    AI-Codereview-Gitlab

    GitLab automatic code review tool based on large models

    AI-Codereview-Gitlab is an open-source automation tool that integrates large language models into the GitLab development workflow to perform automated code reviews. The system monitors GitLab repositories and analyzes commits or merge requests using AI models to identify potential issues, coding mistakes, and quality improvements before the code is merged. By leveraging multiple large language model providers—including OpenAI, DeepSeek, ZhipuAI, or local models through Ollama—the platform...
    Downloads: 0 This Week
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  • 4
    MGIE

    MGIE

    Guiding Instruction-based Image Editing via Multimodal Large Language

    MGIE—Guiding Instruction-based Image Editing—demonstrates how a multimodal LLM can parse natural-language editing instructions and then drive image transformations accordingly. The project focuses on making edits explainable and controllable: the model interprets text guidance, reasons over image content, and outputs edits aligned with user intent. It’s positioned as an ICLR 2024 Spotlight work, with code and references that show how to connect language planning to concrete image operations....
    Downloads: 0 This Week
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