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RapidAI · Mar 28, 2024 · cbcf238 · cbcf238
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diff --git a/content/docs/SupportConversions/coco_to_labelimg.md b/content/docs/SupportConversions/coco_to_labelimg.md
@@ -10,43 +10,57 @@ description: ""
 publishdate: "2022-09-30T05:33:22+01:00"
 ---
 
-- One-click conversion of COCO format data to labelImg labeled yolo format data.
-- COCO format directory structure（see `dataset/COCO_format` for details）：
-    ```text {linenos=table}
-    COCO_format
-    ├── annotations
-    │   ├── instances_train2017.json
-    │   └── instances_val2017.json
-    ├── train2017
-    │   ├── 000000000001.jpg
-    │   └── 000000000002.jpg
-    └── val2017
-        └── 000000000001.jpg
-    ```
-- Convert
-    ```bash {linenos=table}
-    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):
-  ```text {linenos=table}
-  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](https://github.com/tzutalin/labelImg)  library to open it directly and change the label. The specific commands are as follows:
-  ```bash {linenos=table}
-  $ cd dataset/labelImg_format
-  $ labelImg train train/classes.txt
-
-  # or
-  $ labelImg val val/classes.txt
-  ```
+#### 简介
+将COCO格式数据集转换为可以直接用[labelImg](https://github.com/HumanSignal/labelImg)工具可视化标注的YOLO格式。
+
+
+#### COCO格式如下：
+
+{{< alert text="具体结构示例文件，可移步：[COCO_dataset](https://github.com/RapidAI/LabelConvert/tree/main/tests/test_files/COCO_dataset)" />}}
+
+```text {linenos=table}
+COCO_format
+├── annotations
+│   ├── instances_train2017.json
+│   └── instances_val2017.json
+├── train2017
+│   ├── 000000000001.jpg
+│   └── 000000000002.jpg
+└── val2017
+    └── 000000000001.jpg
+```
+
+#### 转换
+```bash {linenos=table}
+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：
+
+{{< alert text="具体结构示例文件，可移步：[labelImg_dataset](https://github.com/RapidAI/LabelConvert/tree/main/tests/test_files/labelImg_dataset)" />}}
+
+
+```text {linenos=table}
+labelImg_format
+  ├── train
+  │   ├── 000000000001.jpg
+  │   ├── 000000000001.txt
+  │   ├── 000000000002.jpg
+  │   └── classes.txt
+  └── val
+      ├── 000000000001.jpg
+      ├── 000000000001.txt
+      └── classes.txt
+```
+
+#### labelImg可视化
+```bash {linenos=table}
+$ cd dataset/labelImg_format
+$ labelImg train train/classes.txt
+
+# or
+$ labelImg val val/classes.txt
+```
diff --git a/content/docs/SupportConversions/coco_visual.md b/content/docs/SupportConversions/coco_visual.md
@@ -3,7 +3,7 @@ weight: 60
 date: "2022-09-30T05:33:22+01:00"
 draft: false
 author: "SWHL"
-title: "Visualize COCO image"
+title: "可视化COCO数据集"
 icon: "bike_scooter"
 toc: true
 description: ""

diff --git a/content/docs/changelog.md b/content/docs/changelog.md
@@ -10,6 +10,11 @@ description: ""
 publishdate: "2023-09-08"
 ---
 
+#### 2024-03-28 v0.0.8 update:
+- 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:
 - 修复[Issue #9](https://github.com/RapidAI/LabelConvert/issues/9)
 

diff --git a/content/docs/overview.md b/content/docs/overview.md
@@ -10,29 +10,28 @@ description: ""
 publishdate: "2023-09-08"
 ---
 
-
 <div align="center">
-  <img src="https://github.com/RapidAI/LabelConvert/releases/download/v0/LabelConvertv3.png" width="55%" height="55%"/>
-</div>
-
-## Label Convert
+  <div align="center">
+    <img src="https://github.com/RapidAI/LabelConvert/releases/download/v0/LabelConvertv3.png" width="55%" height="55%"/>
+  </div>
+  <br/>
+
+  <a href=""><img src="https://img.shields.io/badge/Python->=3.6,<3.12-aff.svg"></a>
+  <a href=""><img src="https://img.shields.io/badge/OS-Linux%2C%20Win%2C%20Mac-pink.svg"></a>
+  <a href="https://github.com/RapidAI/LabelConvert/graphs/contributors"><img src="https://img.shields.io/github/contributors/RapidAI/LabelConvert?color=9ea"></a>
+  <a href="https://github.com/RapidAI/LabelConvert/stargazers"><img src="https://img.shields.io/github/stars/RapidAI/LabelConvert?color=ccf" ></a>
+  <a href="https://pepy.tech/project/label_convert"><img src="https://static.pepy.tech/badge/label_convert?period=total&units=abbreviation&left_color=grey&right_color=blue&left_text=Downloads"></a>
+  <a href="https://pypi.org/project/label_convert/"><img alt="PyPI" src="https://img.shields.io/pypi/v/label_convert"></a>
+  <a href="https://choosealicense.com/licenses/apache-2.0/"><img src="https://img.shields.io/badge/License-Apache%202-dfd.svg"></a>
+  <a href="https://semver.org/"><img alt="SemVer2.0" src="https://img.shields.io/badge/SemVer-2.0-brightgreen"></a>
+  <a href="https://github.com/psf/black"><img src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
 
-<p align="left">
-    <a href=""><img src="https://img.shields.io/badge/Python->=3.6,<3.12-aff.svg"></a>
-    <a href=""><img src="https://img.shields.io/badge/OS-Linux%2C%20Win%2C%20Mac-pink.svg"></a>
-    <a href="https://github.com/RapidAI/LabelConvert/graphs/contributors"><img src="https://img.shields.io/github/contributors/RapidAI/LabelConvert?color=9ea"></a>
-    <a href="https://github.com/RapidAI/LabelConvert/stargazers"><img src="https://img.shields.io/github/stars/RapidAI/LabelConvert?color=ccf" ></a>
-    <a href="https://pepy.tech/project/label_convert"><img src="https://static.pepy.tech/badge/label_convert?period=total&units=abbreviation&left_color=grey&right_color=blue&left_text=Downloads"></a>
-    <a href="https://pypi.org/project/label_convert/"><img alt="PyPI" src="https://img.shields.io/pypi/v/label_convert"></a>
-    <a href="https://choosealicense.com/licenses/apache-2.0/"><img src="https://img.shields.io/badge/License-Apache%202-dfd.svg"></a>
-    <a href="https://semver.org/"><img alt="SemVer2.0" src="https://img.shields.io/badge/SemVer-2.0-brightgreen"></a>
-    <a href="https://github.com/psf/black"><img src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
-</p>
+</div>
 
-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.
+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。
 
 
-### Supported conversions
+### 支持的转换
 ```mermaid
 flowchart LR
 
@@ -45,13 +44,8 @@ F(darknet) --> D
 G(labelme) --> D
 ```
 
-### Installation
+### 安装
 ```bash {linenos=table}
 pip install label_convert
 ```
 
-### Contributing
-Pull requests are welcome. For major changes, please open an issue first
-to discuss what you would like to change.
-
-Please make sure to update tests as appropriate.