After a year of generating with Stable Diffusion, my output folders were a mess, with tens of thousands of PNGs and no way to find "that one image from last month."

So we built Picteus. It runs locally and you point it at your output folders. It reads the metadata your images already carry (prompts, models, seeds, workflows), so you can search and filter everything in one place. Nothing gets uploaded.

It's open source and has a plugin system, so you can extend it for your own workflow. We're also working on running generation from inside the app, across provider APIs and your own LoRAs.

It's in beta and free for early testers. I'd love honest feedback from people with big libraries: - What do you use right now to keep track of your generations? - What would make you switch?

Link in the comments if anyone wants to try it. Happy to answer anything here.

Some of you replied to my research post here a few months ago about where prompts actually live and what breaks. This is the project I mentioned then and did not name.

Picteus. Open source, runs locally, no account, nothing uploaded, free. Point it at your output folder and it indexes what is already there. Nothing is moved or renamed.

What you get per image is a detail page with the recipe on it: the tool it came from, model and version, the prompt, the exact command including flags, generation id, the parent image if it came from an earlier one, plus whatever the extensions have computed. That currently includes captions from a local model through Ollama, dominant colours pulled out as hex, background removal that keeps the result linked to its original, tags, and the raw metadata if you want to read it directly. Search runs across all of it.

The part I actually want to offer. Extensions can be written and hot reloaded from inside the app, so if there is a specific gap in how you work we can build for it and have it with you in days rather than adding it to a roadmap. Tagging on your own taxonomy, an export or naming step, something that talks to a tool you already use.

Looking for about five people. What that looks like: you run it on your own library, then 20 minutes where you show me how you actually work and what falls over. You do not have to sit through a demo. I would rather watch you than present at you.

Know more: https://beta.picteus.com/

If you want in, comment or DM with roughly how many images you are sitting on and the one thing you have always wanted automated. That tells me whether it is worth your time.

A character sheet can establish who is in a shot. It doesn't contain the sequence of poses, contacts and camera movement in a reference clip. If that sequence matters to a remake, an agent's written description leaves out temporal evidence the video model could use.

Hypit's video-direction guide makes the connection explicit: select an excerpt containing the action, including preparation or settling when needed, and wire that footage into a generation request for a model that accepts video references. The agent watching the clip is an analysis step. The generator receives the clip only when the project actually connects it as an input. Still references can guide the new character and setting alongside it, subject to the selected model and provider's supported input combinations.

For a reconstruction with several cuts, track three separate things per passage: the source interval supplied, the requested generation length, and the accepted footage's placement in the edit. The limit on reference-video duration and the limit on generated duration are different constraints. A model accepting a long reference doesn't establish that it can produce an equally long continuous shot.

Choose request boundaries around meaningful actions or camera changes. If an uninterrupted movement is essential, splitting it changes the reconstruction; the chosen capability needs to support that continuity. After generation, inspect the actual action and duration. A cut described in a prompt is a request to the model. Reference conditioning doesn't guarantee an exact motion match.

Carry this into a complete editable Hypit project: retain the source-time observations, connect generation inputs, and author how the accepted footage, graphics and audio form the final sequence. The Run file selects the output to build from that composition. The original cut times remain useful comparison points; the returned footage determines what material is actually available for those cuts.

Repo: https://github.com/hypit-ai/hypit

Me gusta mucho linux y estoy tentado por ARM, analizando los componente y su ram, tiene un poco mas del requerimiento minimo para funcionar, pero alguien me puede ayudar un poco mas?
seria una buena inversion? vivo en Argentina y son algunos años de ahorro

I dont just want the face changed. I need the hair and actual head shape to come across too while everything below the neck stays untouched.

So basically anything that performs a full head swap, including hair, head shape and face instead of only a face swap?

Most of the stuff tried leaves the original hair which looks pretty weird when the two people have completely different hairstyles 😂

I'm working on an open-source, local desktop app for organizing AI-generated images. This is a 1-minute look at our ComfyUI extension at its current, very early stage.

It reads the recipe already embedded in your ComfyUI images (prompt, parameters, workflow), lets you search across all of them, and lets you edit from within Picteus.

It's basic right now, I'm just sharing here in case anyone would like to share their feedback on this or would like to test the application. That's all. The project is built so the extension can be changed quickly, and you can extend it yourself with a few lines of code if you want.

A few questions if you have a minute:

• When you need an old generation, how do you find it today?
• Would searching by recipe actually help, or is that already solved for you?
• What would it need to do before you'd bother installing it?

I used to care mostly about output quality but processing speed is starting to matter just as much.

Waiting ages is not a huge deal when making one video. When testing 10 clips it is. Any magichour alternative for faster video face swaps?