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Show HN: Sisi – Semantic Image Search CLI tool, locally without third party APIs

128 points| zcbenz | 1 year ago |github.com

I wrote this tool to get familiar with CLIP model, I know many people have written similar tools with CLIP before, but I'm new to machine learning and writing a classic tool helps my study.

The unusual thing with my version is, it is in pure Node.js, with the power of node-mlx, a Node.js machine learning framework.

The repo in the link is mostly about implementing indexing and CLI, the code of the model implementation lives as a Node.js module: https://github.com/frost-beta/clip .

Hope this helps other learners!

41 comments

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notsylver|1 year ago

I was planning to do this myself lol. I was going to use SQLite as the index, and use `sqlite-vec` or something similar to query for similar files directly. I think the only other thing I was planning were more filters, `"positive term" -"negative term"` to be able to negate results, `>90"search"` to find images that match by >90% and some generic filters like `--size >1mb` to help narrow it down when you are looking for a specific image. Quantizing embeddings to make them smaller/faster also seemed interesting but I haven't tried doing it yet.

progx|1 year ago

Uses only 1 core 100% under linux, can this be changed?

10 images, each ~20 kb size, took more than 10 minutes to index, is that normal without GPU-acceleration?

zcbenz|1 year ago

No it is not normal, I only tested x64/arm64 macs, I will try on linux.

sureIy|1 year ago

Wow that’s atrocious performance. So there’s no chance to use this on real photos

sureIy|1 year ago

This is cool. Is there also a way to show contents of the image as indexed? i.e. image 1 has cat and dog

There are a lot of tool/apps that let you “search images” but not much that lets you just as easily “read images”

kjeldsendk|1 year ago

I have wanted to clean up my photo collection for ages and remove any nsfw picture that might hide somewhere.

Would this be able to do that and how likely is it It will see a pc release.

Eisenstein|1 year ago

This script doesn't do search, but it generates keywords for images and places them in the image metadata. You can then search for keywords using something like Diffractor. I will warn though that any AI solution not geared towards NSFW will not give good information on NSFW images, though it may give a keyword such as 'intimate' or 'adult content' which is all you need.

* https://github.com/jabberjabberjabber/LLavaImageTagger/

y04nn|1 year ago

How does CLIP compare to YOLO[1]? I haven't looked into image classification/object recognition for a while, but I remember that YOLO was quite good was working on realtime video too.

[1]: https://pjreddie.com/darknet/yolo/

Eisenstein|1 year ago

CLIP and YOLO work completely differently and have different purposes. CLIP uses transformers and embeddings and can compare text with images for classification. YOLO using a CNN and is trained with bounding boxes on images and is used for image recognition.

Give an image to CLIP and you can compare the similarity between the image and a sentence like 'a vase with roses in it'. Whereas with YOLO you give it an image and get the coordinates of bounding boxes around a vase, and around roses.

ivanjermakov|1 year ago

In russian, "sisi" is a variation of "tits".

Is there a job/services that confirm that branding is appropriate across different languages? Seems like a non trivial problem to solve.

visarga|1 year ago

> Seems like a non trivial problem to solve.

Took me 5 minutes to land this GPT prompt.

https://chatgpt.com/share/66e84c0c-a92c-800a-b452-255d6fe942...

Results:

- Chinese (Simplified) 四四 (sì sì) – sounds like "four-four", which can be associated with bad luck due to the number four in Chinese culture

- Arabic "Sisi" is a common nickname, also associated with Egypt's President Abdel Fattah el-Sisi

- Russian Сиси (sisi) – slang for breasts

- Bulgarian Сиси (sisi) – slang for breasts

- Serbian Сиси (sisi) – slang for breasts

- Croatian Sisi – slang for breasts

You should probably complement with a web search and a wiktionary search because they have all languages on a single page.

kristopolous|1 year ago

I read about a company in the 1990s that did that. They went one step further - picking culturally appropriate colors, shapes, numbers, and then permuting the brand names to favorable variations for a country. My (probably wrong) 25 year old recollection was when they introduced subway in China they basically found a way to pronounce it that translated to "this place is delicious". I bet it was in Wired. If not that, probably New York Magazine.

phito|1 year ago

It's definitely not a good name in English either

rlpb|1 year ago

Sounds like something one might try to train an AI to do :)

philsnow|1 year ago

In cantonese it’s what a toddler might call poop

Jack5500|1 year ago

Isn‘t clip superseeded by multimodal llms?

Eisenstein|1 year ago

In this program CLIP is being used to create embeddings. A multimodal LLM does something very similar. In this case the language model is not needed because the embeddings are being used to search directly.