功能特性

• K-Fold Cross Validation with Ultralytics
  • Introduction
  • Setup
  • Generating Feature Vectors for Object Detection Dataset
  • K-Fold Dataset Split
  • Save Records (Optional)
  • Train YOLO using K-Fold Data Splits
  • Conclusion
  • FAQ
    • What is K-Fold Cross Validation and why is it useful in object detection?
    • How do I implement K-Fold Cross Validation using Ultralytics YOLO?
    • Why should I use Ultralytics YOLO for object detection?
    • How can I ensure my annotations are in the correct format for Ultralytics YOLO?
    • Can I use K-Fold Cross Validation with custom datasets other than Fruit Detection?
• Ultralytics YOLO Hyperparameter Tuning Guide
  • Introduction
    • What are Hyperparameters?
    • Genetic Evolution and Mutation
  • Preparing for Hyperparameter Tuning
  • Steps Involved
    • Initialize Hyperparameters
    • Mutate Hyperparameters
    • Train Model
    • Evaluate Model
    • Log Results
    • Repeat
  • Usage Example
  • Results
    • File Structure
    • File Descriptions
      • best_hyperparameters.yaml
      • best_fitness.png
      • tune_results.csv
      • tune_scatter_plots.png
      • weights/
  • Conclusion
    • Further Reading
  • FAQ
    • How do I optimize the learning rate for Ultralytics YOLO during hyperparameter tuning?
    • What are the benefits of using genetic algorithms for hyperparameter tuning in YOLO11?
    • How long does the hyperparameter tuning process take for Ultralytics YOLO?
    • What metrics should I use to evaluate model performance during hyperparameter tuning in YOLO?
    • Can I use Ultralytics HUB for hyperparameter tuning of YOLO models?
• Ultralytics Docs: Using YOLO11 with SAHI for Sliced Inference
  • Introduction to SAHI
    • Key Features of SAHI
  • What is Sliced Inference?
    • Benefits of Sliced Inference
  • Installation and Preparation
    • Installation
    • Import Modules and Download Resources
  • Standard Inference with YOLO11
    • Instantiate the Model
    • Perform Standard Prediction
    • Visualize Results
  • Sliced Inference with YOLO11
  • Handling Prediction Results
  • Batch Prediction
  • Citations and Acknowledgments
  • FAQ
    • How can I integrate YOLO11 with SAHI for sliced inference in object detection?
    • Why should I use SAHI with YOLO11 for object detection on large images?
    • Can I visualize prediction results when using YOLO11 with SAHI?
    • What features does SAHI offer for improving YOLO11 object detection?
    • How do I handle large-scale inference projects using YOLO11 and SAHI?
• YOLO11 🚀 on AzureML
  • What is Azure?
  • What is Azure Machine Learning (AzureML)?
  • How Does AzureML Benefit YOLO Users?
  • Prerequisites
  • Create a compute instance
  • Quickstart from Terminal
    • Create virtualenv
    • Perform YOLO11 tasks
  • Quickstart from a Notebook
    • Create a new IPython kernel
  • Explore More with AzureML
  • FAQ
    • How do I run YOLO11 on AzureML for model training?
    • What are the benefits of using AzureML for YOLO11 training?
    • How do I troubleshoot common issues when running YOLO11 on AzureML?
    • Can I use both the Ultralytics CLI and Python interface on AzureML?
    • What is the advantage of using Ultralytics YOLO11 over other object detection models?
• Conda Quickstart Guide for Ultralytics
  • What You Will Learn
  • Prerequisites
  • Setting up a Conda Environment
  • Installing Ultralytics
    • Note on CUDA Environment
  • Using Ultralytics
  • Ultralytics Conda Docker Image
  • Speeding Up Installation with Libmamba
    • How to Enable Libmamba
  • FAQ
    • What is the process for setting up a Conda environment for Ultralytics projects?
    • Why should I use Conda over pip for managing dependencies in Ultralytics projects?
    • Can I use Ultralytics YOLO in a CUDA-enabled environment for faster performance?
    • What are the benefits of using Ultralytics Docker images with a Conda environment?
    • How can I speed up Conda package installation in my Ultralytics environment?
• Docker Quickstart Guide for Ultralytics
  • What You Will Learn
  • Prerequisites
  • Setting up Docker with NVIDIA Support
    • Installing NVIDIA Docker Runtime
    • Verify NVIDIA Runtime with Docker
  • Installing Ultralytics Docker Images
  • Running Ultralytics in Docker Container
    • Using only the CPU
    • Using GPUs
  • Running Ultralytics in Docker Container
    • Using only the CPU
    • Using GPUs
    • Note on File Accessibility
  • Run graphical user interface (GUI) applications in a Docker Container
    • Running a Docker Container with a GUI
    • Using Docker with a GUI
    • When finished with Docker GUI
  • FAQ
    • How do I set up Ultralytics with Docker?
    • What are the benefits of using Ultralytics Docker images for machine learning projects?
    • How can I run Ultralytics YOLO in a Docker container with GPU support?
    • How do I visualize YOLO prediction results in a Docker container with a display server?
    • Can I mount local directories into the Ultralytics Docker container?
• 边缘计算
  • Quick Start Guide: Raspberry Pi with Ultralytics YOLO11
    • What is Raspberry Pi?
    • Raspberry Pi Series Comparison
    • What is Raspberry Pi OS?
    • Flash Raspberry Pi OS to Raspberry Pi
    • Set Up Ultralytics
      • Start with Docker
      • Start without Docker
        • Install Ultralytics Package
    • Use NCNN on Raspberry Pi
    • Convert Model to NCNN and Run Inference
    • Raspberry Pi 5 YOLO11 Benchmarks
      • Comparison Chart
      • Detailed Comparison Table
    • Reproduce Our Results
    • Use Raspberry Pi Camera
      • Test the Camera
      • Inference with Camera
    • Best Practices when using Raspberry Pi
    • Next Steps
    • Acknowledgements and Citations
    • FAQ
      • How do I set up Ultralytics YOLO11 on a Raspberry Pi without using Docker?
      • Why should I use Ultralytics YOLO11’s NCNN format on Raspberry Pi for AI tasks?
      • How can I convert a YOLO11 model to NCNN format for use on Raspberry Pi?
      • What are the hardware differences between Raspberry Pi 4 and Raspberry Pi 5 relevant to running YOLO11?
      • How can I set up a Raspberry Pi Camera Module to work with Ultralytics YOLO11?
  • Quick Start Guide: NVIDIA Jetson with Ultralytics YOLO11
    • What is NVIDIA Jetson?
    • NVIDIA Jetson Series Comparison
    • What is NVIDIA JetPack?
    • Flash JetPack to NVIDIA Jetson
    • JetPack Support Based on Jetson Device
    • Quick Start with Docker
    • Start with Native Installation
      • Run on JetPack 6.x
        • Install Ultralytics Package
        • Install PyTorch and Torchvision
        • Install onnxruntime-gpu
      • Run on JetPack 5.x
        • Install Ultralytics Package
        • Install PyTorch and Torchvision
        • Install onnxruntime-gpu
    • Use TensorRT on NVIDIA Jetson
      • Convert Model to TensorRT and Run Inference
      • Use NVIDIA Deep Learning Accelerator (DLA)
    • NVIDIA Jetson Orin YOLO11 Benchmarks
      • Comparison Chart
      • Detailed Comparison Table
    • Reproduce Our Results
    • Best Practices when using NVIDIA Jetson
    • Next Steps
    • FAQ
      • How do I deploy Ultralytics YOLO11 on NVIDIA Jetson devices?
      • What performance benchmarks can I expect from YOLO11 models on NVIDIA Jetson devices?
      • Why should I use TensorRT for deploying YOLO11 on NVIDIA Jetson?
      • How can I install PyTorch and Torchvision on NVIDIA Jetson?
      • What are the best practices for maximizing performance on NVIDIA Jetson when using YOLO11?
  • Ultralytics YOLO11 on NVIDIA Jetson using DeepStream SDK and TensorRT
    • What is NVIDIA DeepStream?
    • Prerequisites
    • DeepStream Configuration for YOLO11
      • Run Inference
    • INT8 Calibration
      • Run Inference
    • MultiStream Setup
      • Run Inference
    • Benchmark Results
      • Acknowledgements
    • FAQ
      • How do I set up Ultralytics YOLO11 on an NVIDIA Jetson device?
      • What is the benefit of using TensorRT with YOLO11 on NVIDIA Jetson?
      • Can I run Ultralytics YOLO11 with DeepStream SDK across different NVIDIA Jetson hardware?
      • How can I convert a YOLO11 model to ONNX for DeepStream?
      • What are the performance benchmarks for YOLO on NVIDIA Jetson Orin NX?
  • Coral Edge TPU on a Raspberry Pi with Ultralytics YOLO11 🚀
    • What is a Coral Edge TPU?
    • Boost Raspberry Pi Model Performance with Coral Edge TPU
    • Edge TPU on Raspberry Pi with TensorFlow Lite (New)⭐
    • Prerequisites
    • Installation Walkthrough
      • Installing the Edge TPU runtime
    • Export your model to a Edge TPU compatible model
    • Running the model
    • FAQ
      • What is a Coral Edge TPU and how does it enhance Raspberry Pi’s performance with Ultralytics YOLO11?
      • How do I install the Coral Edge TPU runtime on a Raspberry Pi?
      • Can I export my Ultralytics YOLO11 model to be compatible with Coral Edge TPU?
      • What should I do if TensorFlow is already installed on my Raspberry Pi but I want to use tflite-runtime instead?
      • How do I run inference with an exported YOLO11 model on a Raspberry Pi using the Coral Edge TPU?
• Triton Inference Server with Ultralytics YOLO11
  • What is Triton Inference Server?
  • Prerequisites
  • Exporting YOLO11 to ONNX Format
  • Setting Up Triton Model Repository
  • Running Triton Inference Server
  • FAQ
    • How do I set up Ultralytics YOLO11 with NVIDIA Triton Inference Server?
    • What benefits does using Ultralytics YOLO11 with NVIDIA Triton Inference Server offer?
    • Why should I export my YOLO11 model to ONNX format before using Triton Inference Server?
    • Can I run inference using the Ultralytics YOLO11 model on Triton Inference Server?
    • How does Ultralytics YOLO11 compare to TensorFlow and PyTorch models for deployment?
• Thread-Safe Inference with YOLO Models
  • Understanding Python Threading
  • The Danger of Shared Model Instances
    • Non-Thread-Safe Example: Single Model Instance
    • Non-Thread-Safe Example: Multiple Model Instances
  • Thread-Safe Inference
    • Thread-Safe Example
  • Conclusion
  • FAQ
    • How can I avoid race conditions when using YOLO models in a multi-threaded Python environment?
    • What are the best practices for running multi-threaded YOLO model inference in Python?
    • Why should each thread have its own YOLO model instance?
    • How does Python’s Global Interpreter Lock (GIL) affect YOLO model inference?
    • Is it safer to use process-based parallelism instead of threading for YOLO model inference?
• Isolating Segmentation Objects
  • Recipe Walk Through
  • Full Example code
  • FAQ
    • How do I isolate objects using Ultralytics YOLO11 for segmentation tasks?
    • What options are available for saving the isolated objects after segmentation?
    • How can I crop isolated objects to their bounding boxes using Ultralytics YOLO11?
    • Why should I use Ultralytics YOLO11 for object isolation in segmentation tasks?
    • Can I save isolated objects including the background using Ultralytics YOLO11?
• Viewing Inference Results in a Terminal
  • Motivation
  • Process
  • Example Inference Results
  • Full Code Example
  • FAQ
    • How can I view YOLO inference results in a VSCode terminal on macOS or Linux?
    • Why does the sixel protocol only work on Linux and macOS?
    • What if I encounter issues with displaying images in the VSCode terminal?
    • Can YOLO display video inference results in the terminal using sixel?
    • How can I troubleshoot issues with the python-sixel library?
• Optimizing OpenVINO Inference for Ultralytics YOLO Models: A Comprehensive Guide
  • Introduction
  • Optimizing for Latency
    • Key Strategies for Latency Optimization:
    • Managing First-Inference Latency:
  • Optimizing for Throughput
    • Approaches to Throughput Optimization:
    • Designing Throughput-Oriented Applications:
    • Multi-Device Execution:
  • Conclusion
  • FAQ
    • How do I optimize Ultralytics YOLO models for low latency using OpenVINO?
    • Why should I use OpenVINO for optimizing Ultralytics YOLO throughput?
    • What is the best practice for reducing first-inference latency in OpenVINO?
    • How do I balance optimizing for latency and throughput with Ultralytics YOLO and OpenVINO?
    • Can I use Ultralytics YOLO models with other AI frameworks besides OpenVINO?