MetaCLIP
emoji_search
MetaCLIP | emoji_search | |
---|---|---|
5 | 2 | |
1,038 | 8 | |
4.6% | - | |
7.5 | 7.4 | |
3 days ago | 5 months ago | |
Python | Python | |
GNU General Public License v3.0 or later | - |
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.
MetaCLIP
-
A History of CLIP Model Training Data Advances
(Github Repo | Most Popular Model | Paper)
-
How to Build a Semantic Search Engine for Emojis
Whenever I’m working on semantic search applications that connect images and text, I start with a family of models known as contrastive language image pre-training (CLIP). These models are trained on image-text pairs to generate similar vector representations or embeddings for images and their captions, and dissimilar vectors when images are paired with other text strings. There are multiple CLIP-style models, including OpenCLIP and MetaCLIP, but for simplicity we’ll focus on the original CLIP model from OpenAI. No model is perfect, and at a fundamental level there is no right way to compare images and text, but CLIP certainly provides a good starting point.
- MetaCLIP by Meta AI Research
- MetaCLIP – Meta AI Research
emoji_search
-
How to Build a Semantic Search Engine for Emojis
pip install git+https://github.com/jacobmarks/emoji_search.git
By “this”, I mean an open-source semantic emoji search engine, with both UI-centric and CLI versions. The Python CLI library can be found here, and the UI-centric version can be found here. You can also play around with a hosted (also free) version of the UI emoji search engine online here.
What are some alternatives?
blip-caption - Generate captions for images with Salesforce BLIP
emoji-search-plugin - Semantic Emoji Search Plugin for FiftyOne
BLIP - PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
uform - Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts, images, and 🔜 video, up to 5x faster than OpenAI CLIP and LLaVA 🖼️ & 🖋️
autodistill-metaclip - MetaCLIP module for use with Autodistill.
fiftyone - The open-source tool for building high-quality datasets and computer vision models
NumPyCLIP - Pure NumPy implementation of https://github.com/openai/CLIP
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
open_clip - An open source implementation of CLIP.