I

image-classification

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 sandbox for testing convolutional networks, ResNets, and other architectures on MNIST digits.

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

https://ultralytics.com

An open-source computer vision framework for wildlife image analysis, featuring state-of-the-art models for species classification and detection.