Ultralytics YOLO11 Tasks

YOLO11 is an AI framework that supports multiple computer vision tasks. The framework can be used to perform detection, segmentation, obb, classification, and pose estimation. Each of these tasks has a different objective and use case.

观看： Explore Ultralytics YOLO Tasks: 物体检测, Segmentation, OBB, Tracking, and Pose Estimation.

检测

Detection is the primary task supported by YOLO11. It involves detecting objects in an image or video frame and drawing bounding boxes around them. The detected objects are classified into different categories based on their features. YOLO11 can detect multiple objects in a single image or video frame with high accuracy and speed.

检测实例

细分

Segmentation is a task that involves segmenting an image into different regions based on the content of the image. Each region is assigned a label based on its content. This task is useful in applications such as image segmentation and medical imaging. YOLO11 uses a variant of the U-Net architecture to perform segmentation.

细分示例

分类

Classification is a task that involves classifying an image into different categories. YOLO11 can be used to classify images based on their content. It uses a variant of the EfficientNet architecture to perform classification.

分类示例

姿势

Pose/keypoint detection is a task that involves detecting specific points in an image or video frame. These points are referred to as keypoints and are used to track movement or pose estimation. YOLO11 can detect keypoints in an image or video frame with high accuracy and speed.

姿势示例

OBB

Oriented object detection goes a step further than regular object detection with introducing an extra angle to locate objects more accurate in an image. YOLO11 can detect rotated objects in an image or video frame with high accuracy and speed.

定向检测

结论

YOLO11 supports multiple tasks, including detection, segmentation, classification, oriented object detection and keypoints detection. Each of these tasks has different objectives and use cases. By understanding the differences between these tasks, you can choose the appropriate task for your computer vision application.

常见问题

What tasks can Ultralytics YOLO11 perform?

Ultralytics YOLO11 is a versatile AI framework capable of performing various computer vision tasks with high accuracy and speed. These tasks include:

检测通过绘制图像或视频帧周围的边界框来识别和定位图像或视频帧中的物体。
分割：根据图像内容将图像分割成不同区域，适用于医学成像等应用。
分类：利用 EfficientNet 架构的变体，根据图像内容对整个图像进行分类。
姿势估计：检测图像或视频帧中的特定关键点，以跟踪运动或姿势。
方向物体检测 (OBB)：检测旋转物体时增加一个方向角，以提高准确性。

How do I use Ultralytics YOLO11 for object detection?

To use Ultralytics YOLO11 for object detection, follow these steps:

以适当的格式准备数据集。
Train the YOLO11 model using the detection task.
通过输入新图像或视频帧，利用模型进行预测。

示例

PythonCLI

from ultralytics import YOLO

# Load a pre-trained YOLO model (adjust model type as needed)
model = YOLO("yolo11n.pt")  # n, s, m, l, x versions available

# Perform object detection on an image
results = model.predict(source="image.jpg")  # Can also use video, directory, URL, etc.

# Display the results
results[0].show()  # Show the first image results

# Run YOLO detection from the command line
yolo detect model=yolo11n.pt source="image.jpg"  # Adjust model and source as needed

有关更详细的说明，请查看我们的检测示例。

What are the benefits of using YOLO11 for segmentation tasks?

Using YOLO11 for segmentation tasks provides several advantages:

高精确度：分割任务利用 U-Net 架构的变体实现精确分割。
Speed: YOLO11 is optimized for real-time applications, offering quick processing even for high-resolution images.
多种应用：它是医疗成像、自动驾驶和其他需要详细图像分割的应用的理想选择。

Learn more about the benefits and use cases of YOLO11 for segmentation in the segmentation section.

Can Ultralytics YOLO11 handle pose estimation and keypoint detection?

Yes, Ultralytics YOLO11 can effectively perform pose estimation and keypoint detection with high accuracy and speed. This feature is particularly useful for tracking movements in sports analytics, healthcare, and human-computer interaction applications. YOLO11 detects keypoints in an image or video frame, allowing for precise pose estimation.

有关详细信息和实施技巧，请访问我们的姿势估计示例。

Why should I choose Ultralytics YOLO11 for oriented object detection (OBB)?

Oriented Object Detection (OBB) with YOLO11 provides enhanced precision by detecting objects with an additional angle parameter. This feature is beneficial for applications requiring accurate localization of rotated objects, such as aerial imagery analysis and warehouse automation.