Ultralytics YOLO11 🚀

Implementation of popular deep learning networks with TensorRT network definition API

A fast, easy-to-use, production-ready inference server for computer vision supporting deployment of many popular model architectures and fine-tuned models.

🚀 你的YOLO部署神器。TensorRT Plugin、CUDA Kernel、CUDA Graphs三管齐下，享受闪电般的推理速度。| Your YOLO Deployment Powerhouse. With the synergy of TensorRT Plugins, CUDA Kernels, and CUDA Graphs, experience lightning-fast inference speeds.

🚀 Use YOLO11 in real-time for object detection tasks, with edge performance ⚡️ powered by ONNX-Runtime.

Python library for YOLO small object detection and instance segmentation

This repository is based on shouxieai/tensorRT_Pro, with adjustments to support YOLOv8.

Enhances construction site safety using YOLO for object detection, identifying hazards like workers without helmets or safety vests, and proximity to machinery or vehicles. HDBSCAN clusters safety cone coordinates to create monitored zones. Post-processing algorithms improve detection accuracy.

Samples code for world class Artificial Intelligence SoCs for computer vision applications.

A comprehensive tool for processing and analyzing video footage, producing detailed insights into gameplay and player performance enhancing game understanding and performance evaluation.

Based on tensorrt v8.0+, deploy detection, pose, segment, tracking of YOLO11 with C++ and python api.

YOLOv11 re-implementation using PyTorch

Ultralytics VSCode snippets plugin to provide quick examples and templates of boilerplate code to accelerate your code development and learning.

This repository contains Jupyter Notebooks for training the YOLO11 model on custom datasets for image classification, instance segmentation, object detection, and pose estimation tasks.

Automatic Sorting Bin. Separating recyclables, landfill and compost

YOLOv9 / YOLOv10 - Players Identification of CS2

The model is trained using the YOLO11 framework on a custom dataset of Rock-Paper-Scissors hand gestures. With real-time detection capabilities, this model can be used for live applications, enabling smooth gesture recognition.

This project uses a custom-trained YOLOv11 model with 40 classes to detect hand signs for sign language recognition. The project employs OpenCV for real-time inference through webcam feed.

AI-YOLO Project Object Detection / Computer Vision

YOLOv10 - Players Identification of Valorant