AI
towhee
| AI | towhee | |
|---|---|---|
| 4 | 26 | |
| 14 | 3,015 | |
| - | 2.5% | |
| 10.0 | 8.6 | |
| about 7 years ago | 4 months ago | |
| Python | ||
| GNU General Public License v3.0 only | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
AI
- What's Postgres Got to Do with AI?
-
Do Simpler Machine Learning Models Exist and How Can We Find Them?
> similar to genetic programming
A genetical algorithm was also what I was thinking of. Come up with some kind of symbolic (textual) way to represent a wiring/circuit diagram (graph) and evolve the most efficient "learner" using mutation and cross-breeding (e-sex). The earliest GA I read about used Lisp dicing.
As far as "easiest" AI for humans to work with, "Factor tables" may be a way:
https://github.com/RowColz/AI
AI tuning them becomes more like accounting instead of a lab with Doc Brown.
-
A Gentle Introduction to Vector Databases
It's kind of like Factor Tables. I'd like to see research projects experimenting with it, rather than just these "garage projects".
towhee
- FLaNK Stack Weekly for 14 Aug 2023
- Welcome to generate your embeddings with Towhee
-
Vector database built for scalable similarity search
As another commenter noted, Milvus is overkill and a "bit much" if you're learning/playing.
A good intro to the field with progression towards a full Milvus implementation could be starting with towhee[0] (which is also supported by Milvus).
towhee has an example to do exactly what you want with CLIP[1].
[0] - https://towhee.io/
[1] - https://github.com/towhee-io/examples/tree/main/image/text_i...
-
What Is DocArray?
The description of this is kind of confusing but I think the easiest way to understand it is that it is a data processing pipeline of sorts. Take unstructured data and apply transformation and computation. A similar project to this is Towhee (https://github.com/towhee-io/towhee). This project tries to simplify unstructured data processing and provides pretrained models and pipelines from their hub.
-
[P] My co-founder and I quit our engineering jobs at AWS to build “Tensor Search”. Here is why.
Milvus also has incredible flexibility when it comes to choosing an indexing strategy, and we also have a library specifically meant to help vectorize a variety of data called Towhee (https://github.com/towhee-io/towhee).
-
Deep Dive into Real-World Image Search Engine with Python
Benchmarking the models with towhee is as simple as:
-
A quick tip on DataFrame.apply
The project's homepage is https://github.com/towhee-io/towhee, and you can find more about towhee by going through the documents.
-
Build an Image Search Engine in Minutes
I made a tutorial for building an image search engine with python. The code example is as simple as 10 lines of code, using Towhee and Milvus To put images into the search engine:
-
Any good libraries for feature extraction?
Traditionally, I've done this through PyTorch by adding a hook, but this requires knowledge of the model itself (i.e. model arch and layer names). I found https://github.com/Hironsan/awesome-embedding-models but it didn't provide many CV-focused open-source projects. There's also https://github.com/towhee-io/towhee which is great but more targeted towards application development.
-
A python framework for unstructured data processing
You can check the result from the tutorial.
What are some alternatives?
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
pgsql-http - HTTP client for PostgreSQL, retrieve a web page from inside the database.
Milvus - A cloud-native vector database, storage for next generation AI applications
SymbolicRegression.jl - Distributed High-Performance Symbolic Regression in Julia
examples - Analyze the unstructured data with Towhee, such as reverse image search, reverse video search, audio classification, question and answer systems, molecular search, etc.
symreg - A Symbolic Regression engine
PySceneDetect - :movie_camera: Python and OpenCV-based scene cut/transition detection program & library.
pgvector - Open-source vector similarity search for Postgres
torchscale - Foundation Architecture for (M)LLMs
awesome-embedding-models - A curated list of awesome embedding models tutorials, projects and communities.
marqo - Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai