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‎content/docs/SupportConversions/labelimg_to_yolov5.md‎

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date: "2022-09-30"
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draft: false
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author: "SWHL"
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title: "labelImg → YOLOV5"
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title: "labelImg → YOLOv5"
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icon: "circle"
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toc: true
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description: ""

‎content/docs/SupportConversions/yolov5_to_coco.md‎

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date: "2022-09-30T"
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draft: false
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author: "SWHL"
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title: "YOLOV5 → COCO"
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title: "YOLOv5 → COCO"
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icon: "circle"
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toc: true
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description: ""
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支持标注格式为矩形框和多边形框。
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#### YOLOV5数据结构如下
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#### YOLOv5数据结构如下
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{{< alert text="具体结构示例文件，可移步：[yolov5_dataset](https://github.com/RapidAI/LabelConvert/tree/main/tests/test_files/yolov5_dataset)" />}}
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‎content/docs/SupportConversions/yolov5_to_yolov8.md‎

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---
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weight: 31
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date: "2024-04-23"
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draft: false
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author: "SWHL"
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title: "YOLOv5 → YOLOv8"
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icon: "circle"
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toc: true
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description: ""
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publishdate: "2024-04-23"
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---
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#### 简介
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将YOLOv5格式数据集转换为YOLOv8格式。
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支持标注格式为矩形框和多边形框。
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#### YOLOv5数据结构如下
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{{< alert text="具体结构示例文件，可移步：[yolov5_dataset](https://github.com/RapidAI/LabelConvert/tree/main/tests/test_files/yolov5_dataset)" />}}
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```text {linenos=table}
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yolov5_dataset
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├── classes.txt
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├── non_labels # 通常用来放负样本
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│ └── bg1.jpeg
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├── images
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│ ├── images(13).jpg
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│ └── images(3).jpg
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├── labels
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│ ├── images(13).txt
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│ └── images(3).txt
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├── train.txt
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└── val.txt
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```
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#### 转换
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```bash {linenos=table}
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yolov5_to_yolov8 --data_dir dataset/yolov5_dataset --mode_list train,val
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```
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- `--data_dir`: 数据集所在目录。示例为`dataset/yolov5_dataset`
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- `--save_dir`: 保存转换后的数据集目录。默认为`dataset/yolov5_dataset_yolov8`
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- `--mode_list`: 指定划分的数据集种类。 (例如：`train,val,test` / `train,val`)
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#### 转换后结构如下：
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{{< alert text="具体结构示例文件，可移步：[yolov8_dataset](https://github.com/RapidAI/LabelConvert/tree/main/tests/test_files/yolov8_dataset)" />}}
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```text {linenos=table}
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yolov8_dataset
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├── images
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│ ├── train
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│ │ ├── 0dcddf72.jpg
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│ │ └── images(3).jpg
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│ └── val
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│ ├── 8ae4af51.jpg
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│ └── images(13).jpg
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└── labels
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├── train
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│ ├── 0dcddf72.txt
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│ └── images(3).txt
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└── val
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├── 8ae4af51.txt
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└── images(13).txt
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```

‎content/docs/SupportConversions/yolov5_yaml_to_coco.md‎

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date: "2022-09-30T"
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draft: false
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author: "SWHL"
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title: "YOLOV5 YAML → COCO"
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title: "YOLOv5 YAML → COCO"
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icon: "circle"
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toc: true
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description: ""

‎content/docs/SupportConversions/yolov8_to_yolov5.md‎

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---
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weight: 32
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date: "2024-04-23"
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draft: false
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author: "SWHL"
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title: "YOLOv8 → YOLOv5"
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icon: "circle"
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toc: true
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description: ""
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publishdate: "2024-04-23"
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---
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#### 简介
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将YOLOv8格式数据集转换为YOLOv5格式。
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支持标注格式为矩形框和多边形框。
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#### YOLOv5数据结构如下
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{{< alert text="具体结构示例文件，可移步：[yolov8_dataset](https://github.com/RapidAI/LabelConvert/tree/main/tests/test_files/yolov8_dataset)" />}}
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```text {linenos=table}
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yolov8_dataset
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├── images
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│ ├── train
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│ │ ├── 0dcddf72.jpg
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│ │ └── images(3).jpg
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│ └── val
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│ ├── 8ae4af51.jpg
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│ └── images(13).jpg
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└── labels
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├── train
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│ ├── 0dcddf72.txt
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│ └── images(3).txt
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└── val
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├── 8ae4af51.txt
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└── images(13).txt
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```
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#### 转换
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```bash {linenos=table}
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yolov8_to_yolov5 --data_dir dataset/yolov5_dataset --mode_list train,val
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```
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- `--data_dir`: 数据集所在目录。示例为`dataset/yolov5_dataset`
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- `--save_dir`: 保存转换后的数据集目录。默认为`dataset/yolov8_dataset_yolov5`
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- `--mode_list`: 指定划分的数据集种类。 (例如：`train,val,test` / `train,val`)
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- `--yaml_path`: 指定的yaml配置文件，用于读取其中`names`类名
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#### 转换后结构如下：
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{{< alert text="具体结构示例文件，可移步：[yolov5_dataset](https://github.com/RapidAI/LabelConvert/tree/main/tests/test_files/yolov5_dataset)" />}}
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```text {linenos=table}
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yolov5_dataset
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├── classes.txt
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├── images
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│ ├── images(13).jpg
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│ └── images(3).jpg
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├── labels
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│ ├── images(13).txt
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│ └── images(3).txt
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├── train.txt
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└── val.txt
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```

‎content/docs/overview.md‎

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B --> F(labelImg)
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F --> G(PubLayNet)
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F --> J(YOLOv5)
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J --> H(YOLOv8)
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H --> J
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```
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### 安装

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