rom1504/clip-retrieval
Easily compute clip embeddings and build a clip retrieval system with them
# Technical Summary Provides modular components for CLIP-based semantic search at scale: high-speed inference (1500 samples/s on 3080), efficient vector indexing via FAISS, and a Flask backend with Python client API for remote querying. The pipeline integrates with img2dataset for data acquisition and supports filtering, deduplication, and safety/aesthetic scoring on retrieved results. Designed for billion-scale deployment with end-to-end orchestration from raw image URLs through indexed retrieval UI.
2,733 stars. No commits in the last 6 months. Available on PyPI.
Stars
2,733
Forks
240
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Aug 15, 2025
Commits (30d)
0
Dependencies
28
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/rom1504/clip-retrieval"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
unum-cloud/UForm
Pocket-Sized Multimodal AI for content understanding and generation across multilingual texts,...
mazzzystar/Queryable
Run OpenAI's CLIP and Apple's MobileCLIP model on iOS to search photos.
Ubaida-M-Yusuf/Makimus-AI
AI-powered media search — find images and videos using natural language or visual queries
s-emanuilov/litepali
LitePali is a minimal, efficient implementation of ColPali for image retrieval and indexing,...
HEGOM61ita/OffGallery
Catalogatore AI di immagini fotografiche · Compatibile con Lightroom — Tag automatici, Metadata...