#403 · Primary category: Computer Vision
tidy
Offline semantic Text-to-Image and Image-to-Image search on Android powered by quantized state-of-the-art vision-language pretrained CLIP model and ONNX Runtime inference engine
Project last updated:03/28/24
GitHub Stars
597
Forks
45
Contributors
1
License
GPL-3.0
Why we included this project
TIDY gives your Android phone a real image search engine that works without a network. It runs a quantized CLIP model through ONNX Runtime entirely on-device, so you can type a description like 'sunset over the beach' or pick a reference photo and get visually similar matches from your own library. Because everything stays on the phone, your photos and the index built from them never leave the device, which is a genuine privacy win and also means the app works in areas with poor or no connectivity. The first launch scans your library and builds the index; after that, new photos are added automatically on subsequent opens, so the setup cost is one-time. That makes it a practical, self-contained way to do semantic image retrieval on Android, not just a model demo.
Articles for this project
No articles for this project yet.
To suggest a topic or contribute an article, contact us.
Related projects in this category
opencv
Open Source Computer Vision Library
RuView
π RuView turns commodity WiFi signals into real-time spatial intelligence, vital sign monitoring, and presence detection — all without a single pixel of video.
PaddleOCR
Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.
MinerU
Transforms complex documents like PDFs and Office docs into LLM-ready markdown/JSON for your Agentic workflows.
tesseract
Tesseract Open Source OCR Engine (main repository)