I recently tried to recover text from 8 frames of an office-shot YouTube video, where only a small, blurry portion of a computer screen was visible. After spending half a day with Astra on it, the conclusion was that it’s not possible to read.

Later that evening, I just paused the YouTube video on my phone, circled the part of the display with Google Lens, and it read the whole thing with pretty good accuracy. It was mindblowing :)

Mostly unrelated but fun thing I discovered earlier this year with Apple's vision - if you have text both correctly oriented and upside down in the same image, it likes to interpret the upside down text as a Cyrillic alphabet. I was trying to use it to read the text on camera lenses and it came up with all sorts of bizarre interpretations. If anyone's interested, I got around it by splitting the text at a point and unrolling it into a straight line before running OCR on it.

My own experiments with tesseract were very mixed. I did use just a locally runnable version from a public repository. Text from webpages. Sometimes it would do great but small variations could make it fail completely. Paddleocr on single line text for me has accuracy in the range of 95%

This. Learn all the knobs and dials, too. Useful performance gains to be made by tuning the right settings.

Turns out it's possible to build something without a glorified next-character search engine afterall

So the prompt was probably something like: build me x using Tesseract.

nullsanity got downvoted into oblivion, but they are correct. This is one of the many reasons why vibe coding produces worse software. The code that is generated and the best practice recommendations are completely separate. They both come from a distribution of "most common", and best practice is rarely common. Especially when a practice is first established, or in a specific niche.

Hey author here! :) Great point.

You're totally right. Apple Vision is generally way faster and more accurate on Apple Silicon. Pure Mac-only, I'd use it. (also smaller)

Main reason I went Tesseract: I want SCM to stay portable easily. It's ARM Mac for now, but the inference layer is all JS end-to-end — Transformers.js + ONNX for CLIP/SigLIP + Whisper, Tesseract.js WASM for OCR, all in plain Node workers.

A bit of background: I'm actually an iOS/macOS dev and I really love SwiftUI and AppKit — I just wanted v1 to stay portable by construction. Exploring a native Swift + MLX v2 track separately for speed.

And this is why vibe coders always make inferior software.

copywriting is the art of writing copy for products/marketing maybe you were thinking of sherlocking [1]

1. https://news.ycombinator.com/item?id=34080326

I don't see why LLMs should make the legal part different. It's like saying if you can copyright a book considering LLMs now can copy / write a new one in just one hour. Making it faster doesn't change the legal aspect / ownership of something.

ianal but copyright law has nothing to say about being sherlocked. it's happening - virtually any software you can think of has some shit slop clone out there already

[flagged]

Tried immich and there was a lot not to like. It behooves everyone to try each one and see if it fits.

Just for product aesthetics, i believe it created a thumbnail folder with every resolution, which is annoying since i have a multi-decade 8tb library.

There were other actual issues with organization and display. But with this I realized I can just get gemini to write a DAM for me in a weekend.

Not OP, but probably because they have no idea what they are doing or what CLIP even is. And the whole thing is likely just from one llm prompt, and then they dumped the whole thing onto GitHub, undoubtedly without even looking at any of the code or architecture.

And then you end up with image metadata processing code like this, which just by a cursory glance I’m sure has edge case bugs : https://github.com/allenv0/SCM/blob/main/screenshot-probe.js

[flagged]

Maybe you need a minimal downscale version as well, I heard is very common technique in the video editing world.

Based on my experience, sampling rate can be tricky if what you are looking for lasted less than interval period.

Have you tried scene detection? I would guess camera cuts are even less frequent than keyframes.

> 12k videos ?

you are pirating first-release movies for commercial purposes?

[flagged]

YES! I can confirm it works perfectly on M1/M2/M3 machines (16g/64g).

Apple Photos can already search photos with natural language using on-device AI. Is it not working well for you?

Glad you like it :)!

Thank you :) It's 100% free and open source!

Because you haven't rereleased your own fork in rust yet! The "LLMs can do it" cuts both ways. If that doesn't sound worth your time then it's silly to rudely suggest it is worth someone else's.

Would require you to be locked in to the one embedding model in the camera though and cameras would need to use the same or be incompatible. Would be fine with a standard model like CLIP but would leave a lot of potential on the table compared to a good way to do your own embedding for everything.

[flagged]