#IOS#YOLOv5 🚀 是在 COCO 数据集上预训练的一系列对象检测架构和模型，代表 Ultralytics 对未来视觉 AI 方法的开源研究，结合了经过数千小时研究和开发的经验教训和最佳实践。
#计算机科学#YOLOv3 in PyTorch > ONNX > CoreML > TFLite
NVIDIA DeepStream SDK 7.1 / 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1 implementation for YOLO models
Open Source Generative Process Automation (i.e. Generative RPA). AI-First Process Automation with Large ([Language (LLMs) / Action (LAMs) / Multimodal (LMMs)] / Visual Language (VLMs)) Models
🚀 Easier & Faster YOLO Deployment Toolkit for NVIDIA 🛠️
Convert JSON annotations into YOLO format.
Ultralytics YOLOv8, YOLOv9, YOLOv10, YOLOv11, YOLOv12 for ROS 2
🚀 A high performance real-time object detection solution using YOLO11 ⚡️ powered by ONNX-Runtime
#计算机科学#Packaged version of ultralytics/yolov5 + many extra features
Converting COCO annotation (CVAT) to annotation for YOLO-seg (instance segmentation) and YOLO-obb (oriented bounding box detection)
#计算机科学#xView 2018 Object Detection Challenge: YOLOv3 Training and Inference.
ROS/ROS 2 package for Ultralytics YOLOv8 real-time object detection and segmentation. https://github.com/ultralytics/ultralytics
#IOS#Ultralytics YOLO iOS App source code for running YOLO in your own iOS apps 🌟
A PyTorch implementation of Spiking-YOLOv3. Two branches are provided, based on two common PyTorch implementation of YOLOv3(ultralytics/yolov3 & eriklindernoren/PyTorch-YOLOv3), with support for Spiki...
#安卓#Flutter plugin for Ultralytics YOLO
Easy-to-use finetuned YOLOv8 models.