NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

Convert JSON annotations into YOLO format.

AI-First Process Automation with Large ([Language (LLMs) / Action (LAMs) / Multimodal (LMMs)] / Visual Language (VLMs)) Models

Profile for Glenn Jocher

Ultralytics GitHub Actions

MkDocs plugin for Ultralytics Docs at https://docs.ultralytics.com

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

Ultralytics HUB tutorials and support

xView 2018 Object Detection Challenge: YOLOv3 Training and Inference.

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Ultralytics Docs at https://docs.ultralytics.com/

Quickly detect and classify different species of harmful algae within natural water in real-time with AI and a camera (i.e., ESP32-CAM, smartphone, or webcam).

An open-source project dedicated to constructing robust data pipelines and scalable software infrastructure. We leverage industry-standard tools favored by developers to enhance efficiency and reliability. Uniquely, these pipelines are field-tested on farms across Sumatra, Indonesia, ensuring real-world applicability and resilience.

Object recognition in photo captured from webcam

This project leverages a custom-trained YOLOv9 model to detect objects related to room cleanliness. Built with Gradio, it provides an interactive web interface where users can upload images and adjust detection parameters. The app returns images with annotated bounding boxes around detected objects, aiding in room organization tasks.

Object Detection, Object Segmentation, and Pose Detection with Tracking Using the Official Models of Ultralytics YOLOv8.

🚀🚀🚀 A collection of some awesome public YOLO object detection series projects.

Track user eye in front of webcam using pre-trained Haar cascade eye detection model, openCv and ultralytics yolov5

Deep learning course