Ultralytics YOLO 🚀

[CVPR 2024] Real-Time Open-Vocabulary Object Detection

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER

Unofficial implementation of YOLO-World + EfficientSAM for ComfyUI

YoloDotNet - A C# .NET 8.0 project for Classification, Object Detection, OBB Detection, Segmentation and Pose Estimation in both images and live video streams.

🌟Change the world, it will become a better place. | 以科研和竞赛为导向的最好的YOLO实践框架!

YOLO-UniOW: Efficient Universal Open-World Object Detection

Use this project to automatically annotate your dataset for free in CVAT

YOLO-World + EfficientViT SAM

Mamba-YOLO-World: Marrying YOLO-World with Mamba for Open-Vocabulary Detection

Get up and running with SAM1,2,3, EfficientSAM, YOLO-World, and other promptable vision models locally.

🍁 MapleStory Worlds (Artale) 自動化系統 - 使用 YOLO 深度學習的智能遊戲自動化工具

Python scripts performing Open Vocabulary Object Detection using the YOLO-World model in ONNX.

ROS package for SOTA Computer Vision Models including SAM, Cutie, GroundingDINO, YOLO-World, VLPart, DEVA and MaskDINO.

ComfyUI YOLO-World Integration

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Tensorrt codebase to inference in c++ for all major neural arch using onnx

Run zero-shot prediction models on your data

LingkBot: A Hierarchical Embodied AI Orchestration System for ROS 2, Nav2, RTAB-Map, YOLO-World, RAG and VLM Robotics,Email：qq693180059lrf@gmail.com

The goal of this project is to provide object detection and information on environment model on traffic activity which helps autonomous vehicles or surveillance systems. Computer vision is an essential component for autonomous scars. Accurate detection of vehicles, street buildings, pedestrians, and road signs could assist self-driving cars the drive as safely as humans. However, object detection has been a challenging task for years since images of objects in the real-world environment are affected by illumination, rotation, scale, and occlusion. A unified object detection model, You Only Look Once (YOLO), is used which could directly regress from the input image to object class scores and positions. In this project, we applied YOLO to two different datasets to test its general applicability. We fully analyzed its performance from various aspects on KITTI data set which is specialized for autonomous driving. We proposed a novel technique called memory map, which considers inter-frame information, to strengthen YOLO's detection ability in the driving scene. We broadened the model's applicability scope by applying it to a new orientation estimation task. For this project objective is to provide a information of quality and environmental model on traffic activity and to signal potentially anomalous situation and also apply various machine learning models for object detection such as SVM and CNN and compare and contrast the results with YOLO .

[ICCV2025] ModPrompt: Visual Modality Prompt for Adapting Vision-Language Object Detectors

ONNX models of YOLO-World (an open-vocabulary object detection).

Blood Cell Detection & Classification with Yolo: The World's Largest Microscopy Image Dataset for Body Fluid

This project leverages deep learning to solve complex CAPTCHAs with over 90% accuracy. It includes a custom YOLO model for character detection, a trained .h5 model for recognition, and a dataset of 500 challenging CAPTCHAs. With an integrated API and full source code, it showcases real-world applications in CAPTCHA solving and security testing.

ultralytics_pro 是一堆改過架構的模型大禮包 (包含 v3 ~ 26, yolo-master, RTMDet / RT-DETR, yolact, yoloe / yolo-world, PicoDet / PPyoloE / YoloX, YOLOR / goldyolo / Leyolo / damoyolo / fbrt-yolo / maf-yolo / bgf-yolo / cst-yolo / hyper-yolo / HEYDet / alss-yolo / rcs-yolo / syolo / pst / Vajrav1)

Real World Distance measurement by detecting and identifying the Object using WebCam. A prototype that can help blind people navigate smoothly. Algorithm: Yolo Object Detection Hardware: Raspberry Pi and Pi Camera

采用松灵机械臂在Mujoco环境下实现Yolo-world+Sam+Graspnet传统抓取方法

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YOLO-World-ONNX is a Python package for running inference on YOLO-WORLD Open-vocabulary-object detection model using ONNX models. It provides an easy-to-use interface for performing inference on images and videos using onnxruntime.

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