Alternatives
Products that do what Deut.li does
Free client-side ComfyUI/A1111 PNG metadata extractor
- 1IA
Hey everyone! Excited to be able to share the release of `InvokeAI 2.0 - A Stable Diffusion Toolkit`, an open source project that aims to provide both enthusiasts and professionals a suite of robust image creation tools. Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a 512x768 image (and less for smaller images), and is compatible with Windows/Linux/Mac (M1 & M2). InvokeAI was one of the earliest forks off of the core CompVis repo (formerly lstein/stable-diffusion), and recently evolved into a full-fledged community driven and open source stable…
2022 · github.com
- 2SD
2022 · getimg.ai
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- 5SD
2022 · healthydiffusion.com
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- 8FS
2022 · app.baseten.co
- 9
ChatGPT + Stable Diffusion to convert links into OG images
2023
- 10TS
2022 · computerender.com
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Extract web data into structured JSON, no scraper required.
Jun 2026 · tabstack.ai
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- 15AS
I was frustrated with laggy notebook stable diffusion demos. Plus they usually didn't have all the features I wanted (for example some of them only had inpainting and some only had img2img, so if I wanted both I had to repeatedly copy images between notebooks). So I made this desktop frontend which has much smoother performance than notebook alternatives and integrates image generation, inpainting and img2img into the same workflow. See a video demo here: https://user-images.githubusercontent.com/6392321/191858568-... Features include: * Can run locally or connect to a…
2022 · github.com
- 16AT
Hey HN! Really excited to share this new image de-identifier. Kind of like a game of image telephone, you can upload an image and our app will convert the image to a caption, then will generate an image using stable diffusion using the parameters you set for the model yourself. We had so much fun making this and seeing the varying levels of scary generated images.
2023 · imafake.tonic.ai
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- 18I4
It's our new text-to-image model: a 9.3B single-stream diffusion transformer trained entirely from scratch. We focused heavily on controllability through structured JSON prompts, with strong text rendering, spatial awareness through bounding box guidance, and color palette control. It has the best text rendering of any open-weight model we've tested so far, and the NF4 quantized checkpoint runs on a single 24GB GPU. For more technical details and examples see our blog post: https://ideogram.ai/blog/ideogram-4.0/ We will be happy to answer any questions :)
Jun 2026 · github.com
- 19AW
2014 · github.com
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RAG-ready web scraping that cuts your LLM token costs
Apr 2026 · geekflare.com
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- 22RL
We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers. LLMs seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that: - Raw HTML is full of nav bars, footers, and tracking junk that eats your token budget. A typical product page is 80% noise. - LLMs return malformed JSON more often than you'd expect, especially with…
Mar 2026 · github.com
- 23SD
2022 · healthydiffusion.com
- 24OW
2022 · github.com
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