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X-AnyLabeling开源程序借助 Segment Anything 和其他出色模型的 AI 支持轻松进行数据标记。

news 来源：原创 2025/4/20 14:45:14

一、软件介绍

文末提供源码和程序下载学习

使用 X-AnyLabeling开源程序可以导入、管理和保存数据。用户可以通过多种方式导入图像和视频文件，包括快捷方式或菜单选项。此外，它还涵盖数据删除、图像切换以及标签和图像数据的保存，以确保高效的注释过程和安全的数据管理。

二、详细使用

1.1 Data Import 1.1 数据导入
After opening the GUI, users can select the corresponding task type for import from the File dropdown menu at the top of the interface or use shortcuts.
打开 GUI 后，用户可以从界面顶部的 File 下拉菜单中选择相应的任务类型进行导入，也可以使用快捷方式。

X-AnyLabeling currently supports three data import formats:
X-AnyLabeling 目前支持三种数据导入格式：

Image File Directory (Ctrl+U): Supports importing multiple files with multi-level directory nesting.
Image File Directory （Ctrl+U）：支持多级目录嵌套导入多个文件。
Single Image File (Ctrl+I): Supports importing various formats such as *.jpg, *.png, *.bmp, *.webp, and *.tif.
单个图像文件（Ctrl+I）：支持导入 *.jpg、*.png、*.bmp、*.webp 和 *.tif 等各种格式。
Single Video File (Ctrl+O): Supports importing video formats such as *.mp4, *.avi, *.mov, *.mkv, *.wmv, and *.flv.
单个视频文件（Ctrl+O）：支持导入 *.mp4、*.avi、*.mov、*.mkv、*.wmv 和 *.flv 等视频格式。
1.2 Data Deletion 1.2 数据删除
X-AnyLabeling provides data deletion functionalities as follows:
X-AnyLabeling 提供如下数据删除功能：

Delete Label File (Ctrl+Delete): Deletes the current annotation file. This operation cannot be undone, so please proceed with caution.
删除标签文件（Ctrl+Delete）：删除当前注释文件。此作无法撤消，因此请谨慎作。
Delete Image File (Ctrl+Shift+Delete): Deletes the current image file, moving it to the _delete_ folder within the current image directory.
删除图像文件（Ctrl+Shift+Delete）：删除当前图像文件，将其移动到当前图像目录中的 _delete_ 文件夹。
1.3 Image Switching 1.3 图像切换
In X-AnyLabeling, in addition to regular image switching operations, the following methods are also supported:
在 X-AnyLabeling 中，除了常规的图片切换作外，还支持以下方法：

Shortcut 捷径   switch_to_checked   Description 描述
Ctrl+Shift+A Ctrl + Shift + A 组合键   true 真   Jump to the previous annotated image
跳转到上一个带注释的图像
Ctrl+Shift+D Ctrl+Shift+D 组合键   true 真   Jump to the next annotated image
跳至下一个带注释的图像
Ctrl+Shift+A Ctrl + Shift + A 组合键   false 假   Jump to the previous unannotated image
跳转到上一个未注释的图像
Ctrl+Shift+D Ctrl+Shift+D 组合键   false 假   Jump to the next unannotated image
跳转到下一个未注释的图像
You can determine the switching mode by modifying the switch_to_checked field in the user configuration file.
您可以通过修改用户配置文件中的 switch_to_checked 字段来确定切换模式。

Additionally, you can jump to a specific image by entering the image name in the file search bar at the bottom right of the interface and pressing Enter.
此外，您可以通过在界面右下角的文件搜索栏中输入图像名称并按 Enter 键来跳转到特定图像。

1.4 Saving Label Data 1.4 保存标签数据
X-AnyLabeling has an auto-save feature enabled by default. Upon initial startup, users can check if the Auto Save option is selected from the File dropdown menu.
X-AnyLabeling 默认启用自动保存功能。初始启动时，用户可以检查是否从 File 下拉菜单中选择了 Auto Save 选项。

Label files are saved in the current image directory in *.json format, with the following template:
标签文件以 *.json 格式保存在当前图像目录中，模板如下：

{
"version": "${version}",
"flags": {},
"shapes": [
{
"label": "${label}",
"score": null,
"points": [...],
"group_id": null,
"description": null,
"difficult": false,
"shape_type": "${shape_type}",
"flags": null,
"attributes": {}
}
],
"imagePath": "${filename}",
"imageData": null, // base64
"imageHeight": -1,
"imageWidth": -1
}
⚠️ To change the label save path, select the Change Output Directory option from the File dropdown menu and set the desired save path.
⚠️ 要更改标签保存路径，请选择更改输出目录选项从文件下拉菜单并设置所需的保存路径。

1.5 Saving Image Data 1.5 保存图像数据
If you want to save the current image data (default base64 encoded) during annotation, you can enable the Save Image Data option from the File dropdown menu.
如果要在注释期间保存当前图像数据（默认为 base64 编码），则可以启用保存图像数据下拉菜单中的选项文件 .

2. Editing 2. 编辑
This section guides you on creating, editing, and managing various types of annotation objects and their label information in X-AnyLabeling. It covers everything from basic operations to advanced features, ensuring comprehensive guidance.
本节将指导您在 X-AnyLabeling 中创建、编辑和管理各种类型的标注对象及其标签信息。它涵盖了从基本作到高级功能的所有内容，确保全面的指导。

2.1 Creating Objects 2.1 创建对象
In X-AnyLabeling, each distinct annotated object is referred to as a shape, with key properties such as:
在 X-AnyLabeling 中，每个不同的注释对象都称为一个形状，其关键属性如下：

Field 田   Type 类型   Description 描述
label 标签   String 字符串   The category label of the object.
对象的类别标签。
score 得分   Float 浮   The confidence score of the object, typically used in AI inference. If unavailable, it is null.
对象的置信度分数，通常用于 AI 推理。如果不可用，则为 null。
points 点   Array 数组   List of vertices' coordinates, depending on the shape_type.
顶点坐标列表，具体取决于 shape_type。
group_id   Integer 整数   Group ID to associate multiple objects within the same group; null if not available.
Group ID 关联同一组中的多个对象;如果不可用，则为 null。
description 描述   String 字符串   Description of the object; null if not available.
对象的描述;如果不可用，则为 null。
difficult 难   Boolean 布尔   Indicates if the object is difficult to identify; true means difficult.
指示对象是否难以识别;true 表示困难。
shape_type   String 字符串   The shape type, such as "rectangle", "polygon", etc.
形状类型，如 “rectangle”、“polygon” 等。
flags 标志   Dictionary 字典   Additional flag information for extra state or attributes; null if not available.
额外状态或属性的其他标志信息;如果不可用，则为 null。
attributes 属性   Dictionary 字典   Object's attribute information; an empty dictionary {} if not available.
对象的属性信息;如果不可用，则为空字典 {}。
kie_linking   List 列表   Connection information between objects, e.g., [[1,2],[3,4]]; an empty list [] if not available.
对象之间的连接信息，例如 [[1,2]，[3,4]];如果不可用，则为空列表 []。
For more details on additional fields, refer to shape.py.
有关其他字段的更多详细信息，请参阅 shape.py。

X-AnyLabeling supports creating the following types of shape objects:
X-AnyLabeling 支持创建以下类型的形状对象：

Rectangle (R): Start drawing by left-clicking, move the cursor, and click again to finish the rectangle.
矩形（R）：通过左键单击开始绘制，移动光标，然后再次单击以完成矩形。
Rotation (O): Start drawing by left-clicking, move the cursor, and click again to finish the rotated box.
旋转（O）：通过左键单击开始绘制，移动光标，然后再次单击以完成旋转的框。
Polygon (P): Start drawing by left-clicking along the object's edge, adding segmentation points. Click on the starting point to finish. A minimum of 3 points is required.
多边形（P）：通过沿对象的边缘左键单击开始绘制，并添加分段点。单击起点以完成。至少需要 3 分。
Point: Left-click to create a key point.
点：左键单击可创建关键点。
Line: Start drawing by left-clicking, move the cursor, and click again to finish the line segment.
线条：通过左键单击开始绘制，移动光标，然后再次单击以完成线段。
Line Strip: Start drawing by left-clicking, move the cursor, click to add line segments, and double-click to finish.
线带：通过左键单击开始绘制，移动光标，单击以添加线段，然后双击以完成。
Circle: Start drawing by left-clicking, move the cursor to define the radius, and click again to finish.
圆：通过左键单击开始绘制，移动光标以定义半径，然后再次单击以完成。
Users can operate through the corresponding options in the left menu, right-click, or use shortcuts.
用户可以通过左侧菜单中的相应选项进行作，右键单击或使用快捷方式。

2.2 Editing Objects 2.2 编辑对象
X-AnyLabeling has two modes: Drawing Mode and Editing Mode.
X-AnyLabeling 有两种模式：Drawing Mode 和 Editing Mode。

Drawing Mode: Users can create multiple objects continuously.
绘图模式：用户可以连续创建多个对象。
Editing Mode: Users can edit objects (Ctrl+E), undo (Ctrl+Z), copy (Ctrl+C), paste (Ctrl+V), delete (Delete), move, scale, rotate, etc.
编辑模式：用户可以编辑对象（Ctrl+E）、撤消（Ctrl+Z）、复制（Ctrl+C）、粘贴（Ctrl+V）、删除（Delete）、移动、缩放、旋转等。
Users can quickly switch between drawing and editing modes using the Ctrl+J shortcut or the corresponding options mentioned in section 2.1.
用户可以使用 Ctrl+J 快捷键或第 2.1 节中提到的相应选项在绘图和编辑模式之间快速切换。

Specific operations include:
具体作包括：

For rectangular objects, besides resizing by corner points, users can select multiple objects and merge them into a bounding rectangle by right-clicking and selecting "Merge Selected Objects."
对于矩形对象，除了按角点调整大小外，用户还可以选择多个对象，并通过右键单击并选择“合并所选对象”来将它们合并为一个边界矩形。
For polygon objects, in editing mode, users can drag on an edge to add a new vertex or remove a selected vertex by holding the Shift key and left-clicking.
对于多边形对象，在编辑模式下，用户可以通过按住 Shift 键并左键单击来拖动边缘以添加新顶点或删除所选顶点。
For rotation box objects, users can control the rotation angle and direction by selecting the target and using Z, X, C, V. Real-time rotation angles can also be displayed.
对于旋转框对象，用户可以通过选择目标并使用 Z、X、C、V 来控制旋转角度和方向。还可以显示实时旋转角度。
2.3 Editing Labels 2.3 编辑标签
When creating or editing an object, a label editing box pops up for editing the object's label information.
在创建或编辑对象时，会弹出一个标签编辑框，用于编辑对象的标签信息。

Field 田   Description 描述
Object Label 对象标签   Enter the object's category label, supporting fuzzy search.
输入对象的类别标签，支持模糊搜索。
Group ID 组 ID   For specific tasks like keypoint detection and multi-object tracking.
用于关键点检测和多对象跟踪等特定任务。
Difficult Label 困难标签   Indicates if the object is difficult to recognize.
指示对象是否难以识别。
Label List 标签列表   Shows the list of added labels, sorted alphabetically by default.
显示添加的标签列表，默认情况下按字母顺序排序。
Label Description 标签描述   Additional flag information for extra states or attributes, `null` if not available.
额外状态或属性的其他标志信息，如果不可用，则为 'null'。
Label Linking 标签链接   For linking fields in tasks like key information extraction and relationship extraction.
用于链接关键信息提取和关系提取等任务中的字段。
2.4 Editing Images 2.4 编辑图像

Currently, X-AnyLabeling supports adding a Caption description to the current image. To do this, enter editing mode, click on the blank area of the image, and fill in the image description in the Description area on the right.
目前 X-AnyLabeling 支持为当前图片添加 Caption 描述。为此，请进入编辑模式，单击图像的空白区域，然后在右侧的 Description 区域填写图像描述。

3. View 3. 视图
This section demonstrates how to optimize and customize the display of images and annotation objects in X-AnyLabeling, including visual adjustments of the canvas and images, as well as object information visualization settings, ensuring an efficient and intuitive annotation workflow.
本节演示了如何在 X-AnyLabeling 中优化和自定义图像和注释对象的显示，包括画布和图像的视觉调整，以及对象信息可视化设置，确保高效、直观的注释工作流程。

3.1 Canvas Visualization 3.1 画布可视化
X-AnyLabeling currently supports the following canvas operations:
X-AnyLabeling 目前支持以下 canvas 作：

Zoom In (Ctrl++)
放大（Ctrl++）
Zoom Out (Ctrl+-)
缩小（Ctrl+-）
Reset (Ctrl+0) 重置（Ctrl+0）
Besides setting the zoom ratio in the left window and using shortcuts, users can also zoom in on specific areas by holding the Ctrl key and using the mouse scroll wheel for precise annotation and small object labeling. To apply this change globally, ensure to select the Keep Previous Zoom Ratio option from the View dropdown menu.
除了在左侧窗口中设置缩放比例和使用快捷方式外，用户还可以通过按住 Ctrl 键和使用鼠标滚轮来放大特定区域，以进行精确注释和小对象标记。要全局应用此更改，请确保从 View 下拉菜单中选择 Keep Previous Zoom Ratio 选项。

3.2 Image Visualization 3.2 图像可视化

X-AnyLabeling supports color adjustment for the current image. Operations include:
X-AnyLabeling 支持对当前图片进行颜色调整。作包括：

Select Brightness Contrast from the View dropdown menu at the top of the interface to adjust the brightness and contrast for better visual effects.
选择亮度对比度来自查看界面顶部的下拉菜单来调整亮度和对比度以获得更好的视觉效果。
To apply this change globally, select Keep Current Brightness and Keep Current Contrast from the View dropdown menu.
要全局应用此更改，请从 View 下拉菜单中选择 Keep Current Brightness 和 Keep Current Contrast 。
Additionally, as the cursor moves, the information bar at the bottom of the GUI displays the current image's filename and annotation progress in real time.
此外，当光标移动时，GUI 底部的信息栏会实时显示当前图像的文件名和注释进度。

3.3 Shape Visualization 3.3 形状可视化
Shape visualization features display text descriptions of labeled shapes (Ctrl+T), label names (Ctrl+L), group IDs, rotation angles, prediction scores, and more.
形状可视化功能显示标记形状的文本描述（Ctrl+T）、标签名称（Ctrl+L）、组 ID、旋转角度、预测分数等。

Configure these display options using the indicated keyboard shortcuts or by selecting them in the View dropdown menu at the top.
使用指示的键盘快捷键或在顶部的 View 下拉菜单中选择它们来配置这些显示选项。

Hovering your cursor over a shape will dynamically display its width and height in the GUI's bottom information bar.
将光标悬停在形状上将在 GUI 的底部信息栏中动态显示其宽度和高度。

3.4 Crosshair 3.4 准星

对于十字准线，用户可以通过选择设置十字准线界面顶部的下拉菜单中的选项。

Moreover, as the cursor moves, the information bar at the bottom of the GUI displays real-time position coordinates.
此外，当光标移动时，GUI 底部的信息栏会显示实时位置坐标。

4. Annotation Import and Export
4. 注释导入和导出
At present, X-AnyLabeling provides functionalities for importing and exporting a variety of mainstream label file formats. Below is a brief guide on how to use these features.
目前 X-AnyLabeling 提供了多种主流标签文件格式的导入和导出功能。以下是有关如何使用这些功能的简要指南。

4.1 YOLO Annotation 4.1 YOLO 注释
The latest version of X-AnyLabeling supports one-click import/export for YOLOv5/v8 label files (*.txt) for object detection, instance segmentation, rotated bounding box detection, and keypoint detection tasks.
最新版本的 X-AnyLabeling 支持一键导入/导出 YOLOv5/v8 标签文件（*.txt），用于对象检测、实例分割、旋转边界框检测和关键点检测任务。

Before importing/exporting YOLO label files, you need to prepare a label configuration file:
在导入/导出 YOLO 标签文件之前，您需要准备一个标签配置文件：

For YOLO object detection, instance segmentation, and rotated bounding box detection tasks, refer to classes.txt. Each line represents a class, with numbers incrementing from 0.
有关 YOLO 对象检测、实例分割和旋转边界框检测任务，请参阅 classes.txt。每行代表一个类，数字从 0 开始递增。
For YOLO keypoint detection tasks, refer to yolov8_pose.yaml. For the has_visible parameter, please refer to the official definition.
YOLO 关键点检测任务请参考 yolov8_pose.yaml。has_visible 参数请参考官方定义。
To export in YOLO-Pose format, you need to assign a group_id to each set (bounding box and its keypoints) during annotation so that X-AnyLabeling can understand their relationships during export.
要以 YOLO-Pose 格式导出，您需要在注释过程中为每组（边界框及其关键点）分配一个 group_id，以便 X-AnyLabeling 在导出过程中可以理解它们之间的关系。

Import Task: 导入任务：

Click the Upload button in the top menu bar.
点击上传顶部菜单栏中的按钮。
Select the corresponding task.
选择相应的任务。
Upload the prepared configuration file.
上传准备好的配置文件。
Choose the directory where the label files are located and click OK.
选择标签文件所在的目录，然后单击 OK。
Export Task: 导出任务：

Click the Export button in the top menu bar.
点击出口顶部菜单栏中的按钮。
Upload the prepared configuration file.
上传准备好的配置文件。
Check the appropriate options as needed and click OK.
根据需要检查相应的选项，然后单击 OK。
The export path defaults to the labels folder in the same directory as the current image directory.
导出路径默认为当前镜像目录下同目录下的 labels 文件夹。

For a sample YOLO label file, refer to demo.txt.
有关 YOLO 标签文件示例，请参阅 demo.txt。

4.2 VOC Annotation 4.2 VOC 注释
The latest version of X-AnyLabeling supports one-click import/export for Pascal-VOC label files (*.xml) for detection and segmentation tasks.
最新版本的 X-AnyLabeling 支持一键导入/导出 Pascal-VOC 标签文件（*.xml），用于检测和分割任务。

Import Task: 导入任务：

Click the Upload button in the top menu bar.
点击上传顶部菜单栏中的按钮。
Select the corresponding task.
选择相应的任务。
Choose the directory where the label files are located and click OK.
选择标签文件所在的目录，然后单击 OK。
Export Task: 导出任务：

Click the Export button in the top menu bar.
点击出口顶部菜单栏中的按钮。
Check the appropriate options as needed and click OK.
根据需要检查相应的选项，然后单击 OK。
The export path defaults to the Annotations folder in the same directory as the current image directory.
导出路径默认为当前镜像目录下同目录下的 Annotations 文件夹。

For a sample VOC label file, refer to demo.xml.
有关 VOC 标签文件示例，请参阅 demo.xml。

4.3 COCO Annotation 4.3 COCO 注解
The latest version of X-AnyLabeling supports one-click import/export for COCO label files (*.json) related to object detection, instance segmentation, and keypoint detection tasks.
最新版本的 X-AnyLabeling 支持一键导入/导出与对象检测、实例分割和关键点检测任务相关的 COCO 标签文件（*.json）。

Before importing or exporting COCO label files, ensure you have a label configuration file prepared. For object detection and instance segmentation tasks, refer to classes.txt, and for keypoint detection tasks, refer to yolov8_pose.yaml.
在导入或导出 COCO 标签文件之前，请确保您已准备好标签配置文件。对象检测和实例分割任务请参考 classes.txt，关键点检测任务请参考 yolov8_pose.yaml。

Import Task: 导入任务：

Click the Export button in the top menu bar.
点击出口顶部菜单栏中的按钮。
Select the corresponding task.
选择相应的任务。
Upload the prepared configuration file.
上传准备好的配置文件。
Click OK. 单击 OK（确定）。
The export path defaults to the annotations folder in the same directory as the current image directory.
导出路径默认为与当前镜像目录位于同一目录下的 annotations 文件夹。

For a sample COCO label file, refer to instances_default.json.
有关 COCO 标签文件示例，请参阅 instances_default.json。

4.4 DOTA Annotation 4.4 DOTA 注解
The latest version of X-AnyLabeling supports one-click import/export for DOTA label files (*.txt). The label format is defined as:
最新版本的 X-AnyLabeling 支持一键导入/导出 DOTA 标签文件（*.txt）。标签格式定义为：

x1 y1 x2 y2 x3 y3 x4 y4 class_name difficult
x1 y1 x2 y2 x3 y3 x4 y4 class_name 困难

Import Task: 导入任务：

Click the Export button in the top menu bar.
点击出口顶部菜单栏中的按钮。
Click OK. 单击 OK（确定）。
The export path defaults to the labelTxt folder in the same directory as the current image directory.
导出路径默认为当前镜像目录下同目录下的 labelTxt 文件夹。

For a sample DOTA label file, refer to demo_obb.txt.
有关 DOTA 标签文件示例，请参阅 demo_obb.txt。

4.5 MASK Annotation 4.5 MASK 注释
The latest version of X-AnyLabeling supports one-click import/export for semantic segmentation mask label files (*.png).
最新版本的 X-AnyLabeling 支持一键导入/导出语义分割掩码标签文件（*.png）。

Before importing/exporting mask label files, prepare the configuration file as follows:
在导入/导出蒙版标签文件之前，请准备如下配置文件：

For color images, refer to mask_color_map.json.
有关彩色图像，请参阅 mask_color_map.json。
For grayscale images, refer to mask_grayscale_map.json.
对于灰度图像，请参阅 mask_grayscale_map.json。
Import Task: 导入任务：

Click the Export button in the top menu bar.
点击出口顶部菜单栏中的按钮。
Upload the prepared configuration file.
上传准备好的配置文件。
Click OK. 单击 OK（确定）。
The export path defaults to the mask folder in the same directory as the current image directory.
导出路径默认为与当前 image 目录位于同一目录下的 mask 文件夹。

4.6 MOT Annotation 4.6 AGAINST 注释
The latest version of X-AnyLabeling supports one-click import/export for multi-object tracking label files.
最新版本的 X-AnyLabeling 支持一键导入/导出多对象跟踪标签文件。

Before importing/exporting label files, prepare a label configuration file, referring to classes.txt, where each line represents a class, with numbers incrementing from 0.
在导入/导出标签文件之前，请参考 classes.txt 准备一个标签配置文件，其中每行代表一个类，数字从 0 开始递增。

Export Task: 导出任务：

Click the Export button in the top menu bar.
点击出口顶部菜单栏中的按钮。
Upload the prepared configuration file.
上传准备好的配置文件。
Choose the save path and click OK.
选择保存路径，然后单击 OK。
Import Task: 导入任务：

Click the Upload button in the top menu bar.
点击上传顶部菜单栏中的按钮。
Select the corresponding task.
选择相应的任务。
Upload the prepared configuration file.
上传准备好的配置文件。
Choose the directory containing the label file (gt.txt) and click OK.
选择包含标签文件的目录（gt.txt），然后单击 OK。
For sample label files, refer to the MOT directory, which includes three subfiles: seqinfo.ini, det.txt, and gt.txt.
有关示例标签文件，请参阅 MOT 目录，其中包括三个子文件：seqinfo.ini、det.txt 和 gt.txt。

seqinfo.ini

The seqinfo.ini file contains sequence information, describing metadata for the dataset. The file includes:
seqinfo.ini 文件包含序列信息，用于描述数据集的元数据。该文件包括：

[Sequence]
name = MOT # Sequence name
imdir = mot_label # Image directory
framerate = 30 # Frame rate
seqlength = 249 # Sequence length (number of frames)
imwidth = 1280 # Image width
imheight = 720 # Image height
imext = .jpg # Image file extension
det.txt

The det.txt file contains detection results, with each line representing a detection box. The file includes:
det.txt 文件包含检测结果，每行代表一个检测框。该文件包括：

Frame number, Track ID, Top-left x-coordinate, Top-left y-coordinate, Width, Height, Confidence, <x>, <y>, <z>
The last three fields are for the MOT3D task and are set to -1 by default.
最后三个字段用于 MOT3D 任务，默认情况下设置为 -1。

gt.txt

The gt.txt file contains tracking annotation information, with each line representing an annotation box. The file includes:
gt.txt 文件包含跟踪注释信息，每行代表一个注释框。该文件包括：

Frame number, Track ID, Top-left x-coordinate, Top-left y-coordinate, Width, Height, Validity flag, Class ID, Visibility ratio
The validity flag indicates whether the current trajectory is valid, with 0 for invalid data (ignore) and 1 for valid data (activate). Users can set this using the useDifficult flag in the label manager, where ☑️ indicates an invalid trajectory.
有效性标志指示当前轨迹是否有效，其中 0 表示无效数据（ignore），1 表示有效数据（activate）。用户可以使用标签管理器中的 useDifficult 标志进行设置，其中☑️表示无效的轨迹。

Additionally, for the MOTS dataset format, the v2.4.0+ version offers corresponding export settings. The specific steps for implementation are as follows:
此外，对于 MOTS 数据集格式，v2.4.0+ 版本提供了相应的导出设置。具体实施步骤如下：

Click on the Export - Export MOTS Annotations button in the top menu bar.
单击顶部菜单栏中的 Export - Export MOTS Annotations 按钮。
Upload the prepared configuration file.
上传准备好的配置文件。
Select the save path and click 'OK' to proceed.
选择保存路径，然后单击“确定”继续。
It is important to note that the default exported mots labels are not in the final official dataset format. Here, we provide the corresponding conversion code for reference:
请务必注意，默认导出的 mots 标签不是最终的官方数据集格式。这里，我们提供相应的转换码供参考：

python3 tools/label_converter.py --task mots --mode custom_to_gt --src_path /path/to/your/custom_gt.txt
Note
注意

Before executing the conversion, you need to install the pycocotools library first.
在执行转换之前，您需要先安装 pycocotools 库。

4.7 PPOCR Annotation 4.7 PPOCR 注释
The latest version of X-AnyLabeling (v2.4.0+) supports one-click import/export for the following two PPOCR tasks:
最新版本的 X-AnyLabeling （v2.4.0+）支持一键导入/导出以下两个 PPOCR 任务：

Text Detection and Recognition: Locates text areas in the input image and recognizes the text content.
文本检测和识别：在输入图像中定位文本区域并识别文本内容。
Key Information Extraction: Extracts key information from images, including semantic entity recognition and relation extraction.
关键信息提取：从图像中提取关键信息，包括语义实体识别和关系提取。
Import Task: 导入任务：

Click the Upload button in the top menu bar.
点击上传顶部菜单栏中的按钮。
Select the corresponding task.
选择相应的任务。
Choose the appropriate label file and click OK to upload.
选择适当的标签文件，然后单击 OK 上传。
Export Task: 导出任务：

Click the Export button in the top menu bar.
点击出口顶部菜单栏中的按钮。
Click OK. 单击 OK（确定）。
For the Text Detection and Recognition task, the export path defaults to the ppocr-rec folder in the same directory as the current image directory, which contains:
对于 Text Detection and Recognition 任务，导出路径默认为与当前图像目录位于同一目录中的 ppocr-rec 文件夹，其中包含：

Label.txt: Annotation results
Label.txt：注释结果
rec_gt.txt: Recognition results
rec_gt.txt：识别结果
crop_img: Images corresponding to the recognition results for training
crop_img：用于训练的识别结果对应的图像
For the Key Information Extraction task, the export path defaults to the ppocr-kie folder in the same directory as the current image directory, which contains:
对于 Key Information Extraction 任务，导出路径默认为与当前图像目录位于同一目录下的 ppocr-kie 文件夹，其中包含：

class_list.txt: List of label classes
class_list.txt：标签分类列表
ppocr_kie.json: KIE annotation results
ppocr_kie.json：KIE 注释结果
For sample label files, refer to ppocr-rec and ppocr-kie.
有关示例标签文件，请参阅 ppocr-rec 和 ppocr-kie。

4.8 ODVG Annotation 4.8 ODVG 注释
The latest version of X-AnyLabeling supports one-click import/export for Grounding task-related label files, specifically ODVG annotations.
最新版本的 X-AnyLabeling 支持一键导入/导出 Grounding 任务相关的标签文件，特别是 ODVG 注释。

Before importing/exporting ODVG label files, you need to prepare a label configuration file. For reference, see classes.txt, where each line represents a category, with the numbering incrementing from top to bottom.
在导入/导出 ODVG 标签文件之前，您需要准备一个标签配置文件。有关参考，请参阅 classes.txt，其中每行表示一个类别，编号从上到下递增。

Import Task: 导入任务：

Click the Export button in the top menu bar.
点击出口顶部菜单栏中的按钮。
Select the corresponding task.
选择相应的任务。
Upload the prepared configuration file.
上传准备好的配置文件。
Choose the save path and click OK.
选择保存路径，然后单击 OK。
For the style of ODVG label files, refer to ODVG.
有关 ODVG 标签文件的样式，请参阅 ODVG。

5. Toolbar 5. 工具栏
5.1 Data Statistics 5.1 数据统计
X-AnyLabeling includes a data statistics feature, allowing users to easily access an overview of the current task's data. By selecting Tools -> Overview in the top menu bar, users can view the current data status. It supports the following features:
X-AnyLabeling 包括数据统计功能，允许用户轻松访问当前任务数据的概览。通过选择顶部菜单栏中的工具 -> 概览，用户可以查看当前数据状态。它支持以下功能：

Data Export Functionality
数据导出功能

Export statistical reports in CSV format
以 CSV 格式导出统计报告
Automatically generate a zip file containing label information, shape statistics and class list
自动生成包含标签信息、形状统计和类列表的 zip 文件
Export files include: 导出文件包括：
label_infos.csv: Label count statistics
label_infos.csv：标签计数统计信息
shape_infos.csv: Annotation shape statistics
shape_infos.csv：注释形状统计信息
classes.txt: List of all classes
classes.txt：所有类的列表
Flexible Statistics Range
灵活的统计范围

Support selecting specific range of images for statistics
支持选择特定范围的图片进行统计
View statistics for single or multiple images
查看单个或多个图像的统计信息
Real-time statistics updates
实时统计数据更新
Multi-dimensional Data Analysis
多维度数据分析

By label category: Shows annotation count for each class
按标签类别：显示每个类的注释计数
By shape type: Including polygon, rectangle, rotated box, point, line, circle etc.
按形状类型：包括多边形、矩形、旋转框、点、线、圆等。
Overall data overview: Shows dataset distribution
整体数据概览：显示数据集分布

Usage Instructions: 使用说明：

Click "Tools" -> "Overview" in the top menu bar
单击顶部菜单栏中的 “Tools” -> “Overview”
View data distribution in the statistics window
在统计信息窗口中查看数据分布
Optionally select specific image range for statistics
（可选）选择特定的图像范围进行统计
Click "Export" button to save statistics as zip file
单击“导出”按钮将统计信息保存为 zip 文件
5.2 Save Sub-Images 5.2 保存子图片
To use the save sub-images feature, follow these steps:
要使用保存子图像功能，请执行以下步骤：

Prepare a custom class file. For an example, refer to classes.txt.
准备自定义类文件。有关示例，请参阅 classes.txt。
Click on the Tools -> Save Sub-Images option in the top menu bar, and upload the corresponding custom class file. A sub-image folder named x-anylabeling-crops will be generated in the current directory, containing the targets categorized by class name.
单击顶部菜单栏中的 Tools -> Save Sub-Images 选项，然后上传相应的自定义类文件。将在当前目录中生成一个名为 x-anylabeling-crops 的子图像文件夹，其中包含按类名分类的目标。
5.3 Object Manager 5.3 对象管理器
X-AnyLabeling offers global management of label objects. Users can perform the following operations:
X-AnyLabeling 提供标签对象的全局管理。用户可以执行以下作：

Delete Labels: Remove unnecessary labels.
删除标签：删除不必要的标签。
Rename Labels: Update label names to align with new classification standards.
重命名标签：更新标签名称以符合新的分类标准。
Change Label Colors: Adjust label colors to improve distinguishability.
更改标签颜色：调整标签颜色以提高可区分性。
These actions can be accessed through the Tools -> Object Manager option in the top menu bar, opening the label management window.
可以通过顶部菜单栏中的 Tools -> Object Manager 选项访问这些作，打开标签管理窗口。

Also, to quickly select all annotation shapes on the canvas, follow these steps:
此外，要快速选择画布上的所有批注形状，请执行以下步骤：

Switch to Edit Mode 切换到编辑模式
Click the corresponding icon in the left toolbar (or press Ctrl+E) to enter edit mode
单击左侧工具栏中的相应图标（或按 Ctrl+E）进入编辑模式

Activate Label List 激活标签列表
In the right shape label panel, left-click on any target label
在右侧形状标签面板中，左键单击任何目标标签

Execute Select All 执行全选
While holding down the Shift key:
按住 Shift 键时：

First press Home to select all objects above the current label
首先按 Home 键可选择当前标签上方的所有对象
Then press End to select all objects below the current label
然后按 End 键选择当前标签下的所有对象
5.4 Shape Type Conversion
5.4 形状类型转换
X-AnyLabeling provides a shape type conversion feature, allowing users to change shape types through the Tools option in the top menu bar. The supported conversions include:
X-AnyLabeling 提供了形状类型转换功能，允许用户通过顶部菜单栏中的 Tools 选项更改形状类型。支持的转换包括：

Rectangular Box to Rotated Box: Convert rectangular box labels to rotated box labels.
矩形框到旋转框：将矩形框标签转换为旋转框标签。
Rotated Box to Rectangular Box: Convert rotated box labels to rectangular box labels.
旋转框到矩形框：将旋转的框标签转换为矩形框标签。
Polygon to Bounding Box: Convert polygon labels to bounding box labels.
多边形到边界框：将多边形标签转换为边界框标签。
Note: The Rotated Box to Rectangular Box and Polygon to Bounding Box conversions use the maximum bounding rectangle by default, which may result in the loss of some label information, such as rotation angle. These actions are irreversible, so use them with caution.
注：默认情况下， Rotated Box to Rectangular Box 和 Polygon to Bounding Box 转换使用最大边界矩形，这可能会导致某些标签信息丢失，例如旋转角度。这些作是不可逆的，因此请谨慎使用。

5.5 Saving Masked Images 5.5 保存蒙版图像
To implement the masked image saving feature, follow the steps below:
要实现蒙版图像保存功能，请执行以下步骤：

For areas that require masking, they can be identified using rectangle, rotation, or polygon objects, with the label name set to __mask__;
对于需要掩膜的区域，可以使用矩形、旋转或多边形对象进行标识，并将标签名称设置为 __mask__;
Click on the Tools -> Save Masked Image option in the top menu bar to set the fill color block. The default value is (114, 114, 114). The resulting images are saved by default in the x-anylabeling-mask-image folder.
单击顶部菜单栏中的 Tools -> Save Masked Image 选项以设置填充颜色块。默认值为（114， 114， 114）。默认情况下，生成的图像保存在 x-anylabeling-mask-image 文件夹中。