I built a local Elixir/Python pipeline to curate 14,000 RAW photos
I had 14,000 photos sitting on a drive and wanted an excuse to play with local vision models and Elixir/Phoenix. I originally tried to get LLaVA to tell me if a photo was 'good' or matched my style, but quickly learned that LLMs have terrible taste. I ended up demoting the LLM to just extract metadata, and built a custom CLIP/Ridge Regression pipeline to actually learn my preferences based on how I rate things. The stack is Phoenix/Oban on the orchestrator side, and Python/FastAPI/Instructor for the AI workers. Happy to answer any questions about the architecture,…
I built a local Elixir/Python pipeline to curate 14,000 RAW photos launched on April 20, 2026 with 5 votes, #1,846 of 21,248 launches that month and more than 75% of that year's launches.
What it does
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I have thousands of photos. Like approximately 14,000 RAW, TIFF, RAF, JPG, and JPEG files. Setting aside the time, cost, and workflows I do not know of using tools such as lightroom or Pixea, Its also hard to find which photos are meet my imaginary threshold for being an artful memory. Which am I emotionally attached to because I spent 45 minutes on my knees in the dirt? Which has that grain that makes me goo ohhh? Wait one sec, peep my shi. This problem presented a good excuse to excuse to hop back into using machine learning tools as software. The last time I did anything in this space was deploying a transformer model in 2021 2 . In AI years that's basically as old as your mom... The…from qwelian.com
In the maker’s words, at launch
I had 14,000 photos sitting on a drive and wanted an excuse to play with local vision models and Elixir/Phoenix. I originally tried to get LLaVA to tell me if a photo was 'good' or matched my style, but quickly learned that LLMs have terrible taste. I ended up demoting the LLM to just extract metadata, and built…
Does a similar job
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Source: Show HN post ↗ · launch text quoted in part
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