Y

yolo

Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

GitHub: https://github.com/ultralytics/ultralytics

https://platform.ultralytics.com

Official Ultralytics YOLO Flutter plugin for real-time inference on Android and iOS across major vision tasks.

GitHub: https://github.com/ultralytics/yolo-flutter-app

https://pub.dev/packages/ultralytics_yolo

Ultralytics YOLO iOS app and Swift package for real-time Core ML inference across major computer vision tasks.

GitHub: https://github.com/ultralytics/yolo-ios-app

https://apps.apple.com/app/ultralytics-yolo/id1452689527

Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.

GitHub: https://github.com/ultralytics/yolov5

https://docs.ultralytics.com/yolov5/

PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.

GitHub: https://github.com/ultralytics/yolov3

https://docs.ultralytics.com/models/yolov3/

The ImagesAnnotator application project` annotations format data exporters library for NN training software

Edge deployment suite for RTUAV-YOLO frequency-attention drone detector (Zhang et al.). Trained on Seraphim dataset (95.63% mAP50, 0.78M params). Features NVIDIA TensorRT (445+ FPS), Apple CoreML ANE (328+ FPS), static ONNX, FastAPI, & Docker.

forked from https://github.com/openvinotoolkit/openvino_build_deploy/tree/master/ai_ref_kits/meter_reader

This repository provides Shinobi Docker images regulary built from the official Shinobi Docker image repository and microservice Shinobi Docker images.