Stars
An MIT License of YOLOv9, YOLOv7, YOLO-RD
[WACV 2024 Oral] - ARNIQA: Learning Distortion Manifold for Image Quality Assessment
[CVPRW 2022] MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment
"rsync for cloud storage" - Google Drive, S3, Dropbox, Backblaze B2, One Drive, Swift, Hubic, Wasabi, Google Cloud Storage, Azure Blob, Azure Files, Yandex Files
Dashboard and Active Job extensions to operate and troubleshoot background jobs
Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
Documentation that simply works
We write your reusable computer vision tools. π
Calculate total daily dose, basal, and bolus insulin from data downloaded from Nightscout.
Interact with your documents using the power of GPT, 100% privately, no data leaks
Chatbot for documentation, that allows you to chat with your data. Privately deployable, provides AI knowledge sharing and integrates knowledge into your AI workflow
π¨ Beautiful images of your code β from right inside your terminal.
A set of iOS tools for building closed-loop insulin delivery apps
hybridgroup / go-aravis
Forked from thinkski/go-aravisGo wrapper around libaravis
Using GANs to correct color distortion in underwater images.
An automated insulin delivery app for iOS, built on LoopKit
Display avalance warnings from The Norwegian Avalanche Warning Service as Widgets on macOS, iOS and iPadOS.
YOLOv5 π in PyTorch > ONNX > CoreML > TFLite