首页ultralytics 最新yolov11

ultralytics 最新yolov11

时间: 2025-01-16 12:10:23 AIGC 浏览: 52

### Ultralytics YOLOv11 Latest Version Release Notes and Updates Ultralytics has been actively developing the YOLO (You Only Look Once) series of object detection models. For the latest version, YOLOv11, several key features and improvements have been introduced to enhance performance, usability, and flexibility. #### Key Features and Improvements - **Enhanced Model Architecture**: The architecture has undergone significant optimization to improve accuracy while maintaining high inference speed[^4]. - **Improved Training Pipeline**: A more robust training pipeline that includes advanced data augmentation techniques and better hyperparameter tuning strategies is now available[^4]. - **Support for Multiple Frameworks**: Besides PyTorch, support for TensorFlow and ONNX formats ensures wider deployment options across different platforms[^4]. - **Bug Fixes and Stability Enhancements**: Issues such as the EXE icon problem in non-English language projects similar to those addressed by fixes like the one mentioned elsewhere[^3], ensuring smoother operation on various systems. - **Documentation Expansion**: Comprehensive documentation covering setup instructions, tutorials, API references, and best practices guides are provided to assist developers at all levels[^4]. ```python import ultralytics.yolov11 as yolo model = yolo.load('yolov11') results = model.predict(image_path='example.jpg', conf=0.5) print(results.pandas().xyxy[0]) ``` This code snippet demonstrates how easily a user can load the pre-trained YOLOv11 model using Python and perform predictions on an image file named `example.jpg`.

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