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<html lang="en-us" dir="ltr"><head>
<meta charset="utf-8" />
<title>Label Convert Documentation</title>
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© 2023 SWHL. Built with <a href="https://github.com/colinwilson/lotusdocs"><strong>Lotus Docs</strong></a>
© 2024 SWHL. Built with <a href="https://github.com/colinwilson/lotusdocs"><strong>Lotus Docs</strong></a>
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39 changes: 23 additions & 16 deletions docs/changelog/index.html

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<li class=" "><a class="sidebar-nested-link" href="https://rapidai.github.io/LabelConvert/docs/supportconversions/coco_visual/">Visualize COCO image</a></li>
<li class=" "><a class="sidebar-nested-link" href="https://rapidai.github.io/LabelConvert/docs/supportconversions/coco_visual/">可视化COCO数据集</a></li>



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© 2023 SWHL. Built with <a href="https://github.com/colinwilson/lotusdocs"><strong>Lotus Docs</strong></a>
© 2024 SWHL. Built with <a href="https://github.com/colinwilson/lotusdocs"><strong>Lotus Docs</strong></a>
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id: 3 ,
href: "\/LabelConvert\/docs\/supportconversions\/coco_to_labelimg\/",
title: "COCO → labelImg yolo",
description: "One-click conversion of COCO format data to labelImg labeled yolo format data. COCO format directory structure(see dataset/COCO_format for details): COCO_format ├── annotations │ ├── instances_train2017.json │ └── instances_val2017.json ├── train2017 │ ├── 000000000001.jpg │ └── 000000000002.jpg └── val2017 └── 000000000001.jpg Convert coco_to_labelImg --data_dir dataset/COCO_format --save_dir dataset/labelImg_format --data_dir: the directory where the COCO format dataset is located. Default is dataset/COCO_format. --save_dir: Path to save the converted dataset. Default is f\"{data_dir.name}_labelImg_format\" Converted directory structure (see dataset/labelImg_format for details): labelImg_format ├── train │ ├── 000000000001.",
content: " One-click conversion of COCO format data to labelImg labeled yolo format data. COCO format directory structure(see dataset/COCO_format for details): COCO_format ├── annotations │ ├── instances_train2017.json │ └── instances_val2017.json ├── train2017 │ ├── 000000000001.jpg │ └── 000000000002.jpg └── val2017 └── 000000000001.jpg Convert coco_to_labelImg --data_dir dataset/COCO_format --save_dir dataset/labelImg_format --data_dir: the directory where the COCO format dataset is located. Default is dataset/COCO_format. --save_dir: Path to save the converted dataset. Default is f\"{data_dir.name}_labelImg_format\" Converted directory structure (see dataset/labelImg_format for details): labelImg_format ├── train │ ├── 000000000001.jpg │ ├── 000000000001.txt │ ├── 000000000002.jpg │ └── classes.txt └── val ├── 000000000001.jpg ├── 000000000001.txt └── classes.txt For the converted directory, you can directly use the labelImg library to open it directly and change the label. The specific commands are as follows: $ cd dataset/labelImg_format $ labelImg train train/classes.txt # or $ labelImg val val/classes.txt "
description: "简介 link将COCO格式数据集转换为可以直接用labelImg工具可视化标注的YOLO格式。\nCOCO格式如下: link notifications 具体结构示例文件,可移步:COCO_dataset\nCOCO_format ├── annotations │ ├── instances_train2017.json │ └── instances_val2017.json ├── train2017 │ ├── 000000000001.jpg │ └── 000000000002.jpg └── val2017 └── 000000000001.jpg 转换 link coco_to_labelImg --data_dir dataset/COCO_format --save_dir dataset/labelImg_format --data_dir: COCO格式数据集所在目录。默认是dataset/COCO_format --save_dir: 保存转换后的数据集目录。默认是COCO数据集同级目录下 转换后结构如下: link notifications 具体结构示例文件,可移步:labelImg_dataset\nlabelImg_format ├── train │ ├── 000000000001.jpg │ ├── 000000000001.txt │ ├── 000000000002.jpg │ └── classes.txt └── val ├── 000000000001.jpg ├── 000000000001.txt └── classes.txt labelImg可视化 link $ cd dataset/labelImg_format $ labelImg train train/classes.",
content: "简介 link将COCO格式数据集转换为可以直接用labelImg工具可视化标注的YOLO格式。\nCOCO格式如下: link notifications 具体结构示例文件,可移步:COCO_dataset\nCOCO_format ├── annotations │ ├── instances_train2017.json │ └── instances_val2017.json ├── train2017 │ ├── 000000000001.jpg │ └── 000000000002.jpg └── val2017 └── 000000000001.jpg 转换 link coco_to_labelImg --data_dir dataset/COCO_format --save_dir dataset/labelImg_format --data_dir: COCO格式数据集所在目录。默认是dataset/COCO_format --save_dir: 保存转换后的数据集目录。默认是COCO数据集同级目录下 转换后结构如下: link notifications 具体结构示例文件,可移步:labelImg_dataset\nlabelImg_format ├── train │ ├── 000000000001.jpg │ ├── 000000000001.txt │ ├── 000000000002.jpg │ └── classes.txt └── val ├── 000000000001.jpg ├── 000000000001.txt └── classes.txt labelImg可视化 link $ cd dataset/labelImg_format $ labelImg train train/classes.txt # or $ labelImg val val/classes.txt "
}
);
index.add(
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id: 6 ,
href: "\/LabelConvert\/docs\/overview\/",
title: "Overview",
description: "Label Convert link A dataset format conversion tool for object detection and image segmentation, which supports mutual conversion between labelme, labelImg tools and YOLO, VOC, and COCO dataset formats. Supported conversions linkflowchart LR A(labelImg) --\u003e B(YOLOv5) A --\u003e C(PubLayNet) D(COCO) --\u003e A B --\u003e D E(YOLOv5 YAML) --\u003e D F(darknet) --\u003e D G(labelme) --\u003e D Installation link pip install label_convert Contributing linkPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.",
content: " Label Convert link A dataset format conversion tool for object detection and image segmentation, which supports mutual conversion between labelme, labelImg tools and YOLO, VOC, and COCO dataset formats.\nSupported conversions linkflowchart LR A(labelImg) --\u003e B(YOLOv5) A --\u003e C(PubLayNet) D(COCO) --\u003e A B --\u003e D E(YOLOv5 YAML) --\u003e D F(darknet) --\u003e D G(labelme) --\u003e D Installation link pip install label_convert Contributing linkPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.\nPlease make sure to update tests as appropriate.\n"
description: " 目标检测和图像分割的数据集格式转换工具,支持labelme、labelImg与YOLO、VOC和COCO 数据集格式之间的相互转换。 支持的转换 linkflowchart LR A(labelImg) --\u003e B(YOLOv5) A --\u003e C(PubLayNet) D(COCO) --\u003e A B --\u003e D E(YOLOv5 YAML) --\u003e D F(darknet) --\u003e D G(labelme) --\u003e D 安装 link pip install label_convert ",
content: " 目标检测和图像分割的数据集格式转换工具,支持labelme、labelImg与YOLO、VOC和COCO 数据集格式之间的相互转换。\n支持的转换 linkflowchart LR A(labelImg) --\u003e B(YOLOv5) A --\u003e C(PubLayNet) D(COCO) --\u003e A B --\u003e D E(YOLOv5 YAML) --\u003e D F(darknet) --\u003e D G(labelme) --\u003e D 安装 link pip install label_convert "
}
);
index.add(
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id: 9 ,
href: "\/LabelConvert\/docs\/changelog\/",
title: "Changelog",
description: "2023-11-01 v0.0.7 update: link 修复Issue #9 2023-11-01 v0.0.6 update: link 添加labelme_to_coco的支持,详情参见:labelme_to_coco 2023-10-25 v0.0.4~v0.0.5 update: link 修复命令行模式下,参数类型错误 更新文档内容,优化文档表达 2023-09-15 v0.0.3 update: link Add labelImg to publaynet format. ",
content: "2023-11-01 v0.0.7 update: link 修复Issue #9 2023-11-01 v0.0.6 update: link 添加labelme_to_coco的支持,详情参见:labelme_to_coco 2023-10-25 v0.0.4~v0.0.5 update: link 修复命令行模式下,参数类型错误 更新文档内容,优化文档表达 2023-09-15 v0.0.3 update: link Add labelImg to publaynet format. "
description: "2024-03-28 v0.0.8 update: link 优化各个模块代码 添加单元测试 去除无效数据集文件 2023-11-01 v0.0.7 update: link 修复Issue #9 2023-11-01 v0.0.6 update: link 添加labelme_to_coco的支持,详情参见:labelme_to_coco 2023-10-25 v0.0.4~v0.0.5 update: link 修复命令行模式下,参数类型错误 更新文档内容,优化文档表达 2023-09-15 v0.0.3 update: link Add labelImg to publaynet format. ",
content: "2024-03-28 v0.0.8 update: link 优化各个模块代码 添加单元测试 去除无效数据集文件 2023-11-01 v0.0.7 update: link 修复Issue #9 2023-11-01 v0.0.6 update: link 添加labelme_to_coco的支持,详情参见:labelme_to_coco 2023-10-25 v0.0.4~v0.0.5 update: link 修复命令行模式下,参数类型错误 更新文档内容,优化文档表达 2023-09-15 v0.0.3 update: link Add labelImg to publaynet format. "
}
);
index.add(
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{
id: 11 ,
href: "\/LabelConvert\/docs\/supportconversions\/coco_visual\/",
title: "Visualize COCO image",
title: "可视化COCO数据集",
description: " coco_visual --vis_num 1 \\ --json_path dataset/COCO_format/annotations/instances_train2017.json \\ --img_dir dataset/COCO_format/train2017 --vis_num: specify the index of the image to be viewed --json_path: path to the json file of the image to view --img_dir: view the directory where the image is located ",
content: " coco_visual --vis_num 1 \\ --json_path dataset/COCO_format/annotations/instances_train2017.json \\ --img_dir dataset/COCO_format/train2017 --vis_num: specify the index of the image to be viewed --json_path: path to the json file of the image to view --img_dir: view the directory where the image is located "
}
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<pubDate>Fri, 08 Sep 2023 00:00:00 +0000</pubDate>

<guid>https://rapidai.github.io/LabelConvert/docs/overview/</guid>
<description>Label Convert link A dataset format conversion tool for object detection and image segmentation, which supports mutual conversion between labelme, labelImg tools and YOLO, VOC, and COCO dataset formats.
Supported conversions linkflowchart LR A(labelImg) --&amp;gt; B(YOLOv5) A --&amp;gt; C(PubLayNet) D(COCO) --&amp;gt; A B --&amp;gt; D E(YOLOv5 YAML) --&amp;gt; D F(darknet) --&amp;gt; D G(labelme) --&amp;gt; D Installation link pip install label_convert Contributing linkPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.</description>
<description> 目标检测和图像分割的数据集格式转换工具,支持labelme、labelImg与YOLO、VOC和COCO 数据集格式之间的相互转换。
支持的转换 linkflowchart LR A(labelImg) --&amp;gt; B(YOLOv5) A --&amp;gt; C(PubLayNet) D(COCO) --&amp;gt; A B --&amp;gt; D E(YOLOv5 YAML) --&amp;gt; D F(darknet) --&amp;gt; D G(labelme) --&amp;gt; D 安装 link pip install label_convert </description>
</item>

<item>
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<pubDate>Fri, 15 Sep 2023 00:00:00 +0000</pubDate>

<guid>https://rapidai.github.io/LabelConvert/docs/changelog/</guid>
<description>2023-11-01 v0.0.7 update: link 修复Issue #9 2023-11-01 v0.0.6 update: link 添加labelme_to_coco的支持,详情参见:labelme_to_coco 2023-10-25 v0.0.4~v0.0.5 update: link 修复命令行模式下,参数类型错误 更新文档内容,优化文档表达 2023-09-15 v0.0.3 update: link Add labelImg to publaynet format. </description>
<description>2024-03-28 v0.0.8 update: link 优化各个模块代码 添加单元测试 去除无效数据集文件 2023-11-01 v0.0.7 update: link 修复Issue #9 2023-11-01 v0.0.6 update: link 添加labelme_to_coco的支持,详情参见:labelme_to_coco 2023-10-25 v0.0.4~v0.0.5 update: link 修复命令行模式下,参数类型错误 更新文档内容,优化文档表达 2023-09-15 v0.0.3 update: link Add labelImg to publaynet format. </description>
</item>

</channel>
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