Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
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Updated
Aug 11, 2026 - Python
Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
X-AnyLabeling: A lightweight, efficient, and unified cross-platform desktop application for annotating text, image, video, and multimodal data, combining versatile built-in tools with state-of-the-art AI models and flexible multi-format export.
OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.
🚀 Easier & Faster YOLO Deployment Toolkit for NVIDIA 🛠️
A Simple, Lightweight, and Extensible Serving Framework for X-AnyLabeling
Train Yolo with C#
A curated list of awesome resources for generic object detection in aerial images.
AI for remote sensing, remote sense, object detection, oriented object detection, computer vision, cv
Real-Time Oriented Object Detection Transformer in Remote Sensing Images (TGRS 2026)
Repository containing community-contributed Ultralytics model configs.
GIoU for rotated bounding boxes, vectorized and differentiable
This is a PyTorch based rotated object detection using yolov4, forked from https://github.com/kunnnnethan/R-YOLOv4.
Differenciable IoU of rotated polygons in PyTorch
Deep learning for rotated object detection in Microscopy
ResNetnetwork (<2M params) for Rotated Object Detection with Modulated Rotation Loss and noisy data
Template matching for rotation using Radon transforms.
Ultralytics-YOLO11 免安装一键启动整合包
REST API to detect objects in images. Get labels, confidence scores, and bounding box coordinates. Powered by neural networks.
Fork of ultralytics/ultralytics. Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Detecting hair follicles with rotated bounding boxes
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