ultralytics/xview-docker

YOLOv3 training, preprocessing, validation, and inference for object detection in xView satellite imagery and the xView detection challenge.

VisDrone aerial object detection toolkit with 33 models (Torchvision + YOLO), training, evaluation, video inference, benchmarking, and annotation conversion.

Ready-to-use Cog deployments and CI/CD for running Ultralytics YOLO11, YOLO World, YOLOE, and YOLO26 models on Replicate.

Analyse · Learn · Ingest · Curate · Export — AI-powered YOLO dataset management toolkit

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

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

Sleek, mobile-friendly web UI for NVIDIA LocateAnything-3B — open-vocabulary object detection & grounding on your own GPU, via one docker compose up.

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

AI Auto Annotation & YOLO Training Pipeline, End-to-end object detection auto-labeling and YOLO training platform. VLM-powered annotation with NVIDIA LocateAnything-3B, manual refinement, one-click YOLO training, video keyframe extraction, and model validation. Supports image and video.