clip-retrieval VS dmd

The tool clip-retreival lets you filter those 400 million images to whatever subsets you're interested in --- for example, 10,000 images of (mostly) handwriting.

Hehe, well you know, PR welcome, the front end is 500 lines https://github.com/rom1504/clip-retrieval/blob/main/front/sr...

Other people have done a few alternate front ends already

This one is meant to be functional, but could sure be made prettier

This might work: https://github.com/rom1504/clip-retrieval .

HaveIBeenTrained uses clip retrieval to search the Laion-5B and Laion-400M image datasets. These are currently the largest public text-to-image datsets, and they are used to train models like Stable Diffusion, Imagen, among many others.

Done https://github.com/rom1504/clip-retrieval/commit/53e3383f58b...

Using clip for searching is better than direct text indexing for a variety of reasons but here for example because it matches better what stable diffusion sees

Based on OpenAI's CLIP and the clip-retrieval library (https://github.com/rom1504/clip-retrieval), I've built an end-to-end demo for a semantic and similarity image search engine. It's incredibly powerful for finding similar images amongst large image datasets, or just submitting text/natural language queries and finding the most relevant images in your dataset. Really useful tool for introspection into large datasets before annotation or ML work begins. This could potentially be used to filter or downsize your datasets by several orders of magnitude and make annotation and ML work easier and less costly.

Checkout the demo here:

http://ec2-52-39-251-116.us-west-2.compute.amazonaws.com/

And you can checkout our website or email me for updates and email list, etc.:

https://machineperception.co

Assuming you have an NVIDIA GPU, you can build a semantic search engine by indexing CLIP embeds (image or text).

https://github.com/rom1504/clip-retrieval

Here's the pipeline spitting out the same error as on my macbook did.

https://github.com/dlang/dmd/actions/runs/8023469412/job/219...

Not completely on topic (if you read TFA) but my favorite Git commit is by compiler badass and HN frequenter, where he checks in an entire C compiler to the D language repo:

https://github.com/dlang/dmd/pull/12507

https://news.ycombinator.com/item?id=27102584

A new generated code alone is 4000 lines long [1]. The actual code added is just 2000 lines, and some are used to pay debts, I mean, to make a proper code generator (which can be alternatively written in a simpler scripting langauge). In any case it is never comparable to the entier C parser proper.

[1] https://github.com/dlang/dmd/pull/15307/files#diff-3677bcc89...

D is completely opensource already (https://github.com/dlang/dmd). The "open" of OpenD is just ADR saying that OpenD will be more open to new language features than D has historically been.

The reference compiler, DMD, is open source: https://github.com/dlang/dmd

But they don't accept just any Pull Request or features the community submits, understandably. There's a process called DIP for language improvements: https://github.com/dlang/DIPs/blob/master/DIPs/README.md

However, by some accounts, it's really hard to get anything through.

Given D already has so many feature, I find that to be a good thing , to be honest, by not everyone agrees, of course.