Computer Vision

Because commodity WiFi already bounces off your body, RuView uses cheap ESP32 nodes to detect presence, vital signs, and even body pose without cameras or wearables.

It turns images and PDFs into structured JSON and Markdown so your RAG pipeline doesn't have to squint.

It exists to handle the tedious wiring—annotations, dataset formats, tracking—that sits between a trained model and a useful application.

Ultralytics wants to stop you from stitching together separate repos for every computer vision task by bundling detection, segmentation, tracking, and pose estimation into one YOLO-backed package.

OmniParser turns raw screenshots into structured, labeled UI elements so vision-language models can finally click what they mean to click.

Upscayl gives desktop users a free way to enlarge and enhance low-resolution images using local Real-ESRGAN models and a Vulkan-compatible GPU.

It rounds up hundreds of AI project links so you don't have to hunt them down yourself.

OpenCV is an open-source C++ computer vision library whose own README acts as a portal rather than a product page.

Frigate performs real-time, local object detection on IP camera streams using OpenCV and TensorFlow, designed to integrate tightly with Home Assistant.

A Tencent research project that restores degraded faces by tapping into the rich priors locked inside a pretrained StyleGAN2 model.

It turns images of text into searchable documents across more than 100 languages, offering both a command-line tool and a C++ library for builders.

It exists to let developers run customized vision, text, and audio machine learning across mobile, web, and edge hardware without cloud round-trips.

It exists so you can extract text from screenshots, PDFs, and barcodes without a network connection or a cloud bill.

It renders high-quality novel views of real-world scenes at 30 fps by replacing costly neural radiance fields with optimized 3D Gaussians.

Real-ESRGAN turns the ESRGAN research model into a practical tool for upscaling and restoring real-world images and videos using only synthetic training data.

It turns face swaps and lip-syncs into queued, retryable batch jobs instead of one-off scripts.

An OCR model that asks how few vision tokens an LLM needs before it can no longer read the page.

CMU's real-time multi-person pose estimator detects body, face, hands, and feet simultaneously—body runtime stays flat even as the crowd grows.

OCRmyPDF exists because most free OCR tools botch text placement, bloat file sizes, or mangle image resolution when trying to make scanned documents searchable.

YOLOv5 made real-time object detection as easy as `torch.hub.load`, then exported to everything from iOS to edge chips.