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Image MetaHub is a free, local-first desktop application published by LuqP2, currently at version 0.19.3, with three versions released to date. Its purpose is to help users browse, search, and organize large libraries of AI-generated images by reading the generation metadata embedded directly in image files. The software extracts details such as the prompt, model, LoRA, seed, and sampler, and it can also read the full ComfyUI workflow stored within a file, making it suitable for images produced by ComfyUI, Stable Diffusion, and similar generation tools. Because it indexes this embedded metadata, users can filter and search their entire collection instantly, which is particularly valuable when working with sizable libraries where manual organization would be impractical. Typical use cases include locating a specific image by the prompt or seed that created it, grouping outputs by model or LoRA, reviewing sampler settings to reproduce a result, and managing extensive archives of generated artwork without relying on filenames or folder structures alone. The application is designed with privacy and independence as core principles: it runs completely offline and never uploads images or data, so all indexing and searching happen on the user's own machine. This local-first approach means there is no dependency on cloud services, accounts, or network connectivity, and sensitive or private image collections remain fully under the user's control. As a desktop organizer, Image MetaHub fits within the categories of image management, media cataloging, and AI workflow tooling, serving artists, hobbyists, and professionals who generate images regularly and need a reliable way to keep track of how each file was created. With its combination of instant metadata-based search, support for full workflow data, and offline operation, it provides a focused solution for organizing AI-generated image libraries of any scale.
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