标注工具的安装

本文介绍如何使用pip升级Python包,并安装labelme和labelImg等图像标注工具。完成标注后,标注文件将以.json格式保存,文件名与图片名一致。通过解析.json文件,可以获取标注的类别和坐标。

 升级pip

pip install --upgrade pip
pip install labelme

 

pip install labelImg

 

 标注完成后,标注文件保存为.json文件,且文件名与图片的名称一样

{
  "version": "3.16.7",
  "flags": {},
  "shapes": [
    {
      "label": "people",
      "line_color": null,
      "fill_color": null,
      "points": [
        [
          39.86784140969163,
          55.10572687224669
        ],
        [
          99.55947136563877,
          244.9735682819383
        ]
      ],
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "people",
      "line_color": null,
      "fill_color": null,
      "points": [
        [
          90.7488986784141,
          57.969162995594715
        ],
        [
          130.61674008810573,
          239.24669603524228
        ]
      ],
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "people",
      "line_color": null,
      "fill_color": null,
      "points": [
        [
          126.431718061674,
          54.44493392070484
        ],
        [
          189.4273127753304,
          239.90748898678413
        ]
      ],
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "people",
      "line_color": null,
      "fill_color": null,
      "points": [
        [
          381.4977973568282,
          76.47136563876651
        ],
        [
          488.9867841409692,
          266.5594713656388
        ]
      ],
      "shape_type": "rectangle",
      "flags": {}
    },
    {
      "label": "car",
      "line_color": null,
      "fill_color": null,
      "points": [
        [
          193.6123348017621,
          49.37885462555066
        ],
        [
          364.9779735682819,
          225.37004405286342
        ]
      ],
      "shape_type": "rectangle",
      "flags": {}
    }
  ],
  "lineColor": [
    0,
    255,
    0,
    128
  ],
  "fillColor": [
    255,
    0,
    0,
    128
  ],
  "imagePath": "timg.jpg",
  "imageData": 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",
  "imageHeight": 285,
  "imageWidth": 500
}

其中“shapes”是一个列表,列表中的每一个元素也是一个字典(该字典包括类别名称和目标物的坐标)

# -*- coding: utf-8 -*-
import json
#只读模式
with open("C:/Users/zhangping/Desktop/labelMe/timg.json",'r') as f:
    #将json文件转换为Python的字典类
    j_to_d=json.load(f)
    #图像的宽和高
    height = j_to_d['imageHeight']
    width = j_to_d['imageWidth']
    #提取每一个目标物
    for obj in j_to_d['shapes']:
        #类别
        label = obj['label']
        print(label)
        #四个坐标点(左上角的坐标点、右下角的坐标点)
        xmin = obj['points'][0][0]
        ymin = obj['points'][0][1]
        xmax = obj['points'][1][0]
        ymax = obj['points'][1][1]
        print((xmin,ymin,xmax,ymax))

 打印结果如下:

people
(39.86784140969163, 55.10572687224669, 99.55947136563877, 244.9735682819383)
people
(90.7488986784141, 57.969162995594715, 130.61674008810573, 239.24669603524228)
people
(126.431718061674, 54.44493392070484, 189.4273127753304, 239.90748898678413)
people
(381.4977973568282, 76.47136563876651, 488.9867841409692, 266.5594713656388)
car
(193.6123348017621, 49.37885462555066, 364.9779735682819, 225.37004405286342)

 

 

<think>我们被要求安装Labelme图像标注工具。根据引用内容,安装Labelme通常需要先安装Anaconda(一个Python发行版),然后使用conda或pip来安装Labelme。安装步骤因操作系统而异,主要分为Windows和Ubuntu(Linux)两种。从引用中我们可以总结出以下步骤: 对于Windows系统: 1.下载并安装Anaconda(选择适合的Python版本)。 2.打开AnacondaPrompt(在开始菜单中可以找到)。3.创建一个新的conda环境(可选,但推荐):```condacreate --name=labelmepython=3.6#这里python版本根据自己安装的Anaconda版本选择```4.激活该环境:```activate labelme```5.安装PyQt5(Labelme的依赖):```condainstall pyqt5```或者使用pip:```pip installpyqt5```6.安装labelme:```pipinstall labelme```7.安装完成后,输入以下命令启动labelme:```labelme```对于Ubuntu系统(引用中提供了两种Python版本): -Python2:```sudo apt-get installpython-qt4#安装PyQt4(或者安装PyQt5)sudopip installlabelme``` -Python3:```sudo apt-get installpython3-pyqt5sudopip3install labelme```注意:在Windows系统中,如果遇到网络问题导致安装失败(如超时),可以尝试增加超时时间(如`pip--default-timeout=100install labelme`)或切换网络环境。根据上述引用,我们给出安装步骤: ###安装Labelme图像标注工具####在Windows系统上安装1.**安装Anaconda**如果你还没有安装Anaconda,请先到[Anaconda官网](https://www.anaconda.com/products/individual)下载并安装适合你操作系统的版本。安装时注意选择Python版本(推荐Python3.6或更高版本)。2.**打开Anaconda Prompt**在开始菜单中找到并打开“Anaconda Prompt”。 3. **创建并激活环境(可选但推荐)**为了避免与其他项目环境冲突,建议创建一个独立的环境。在AnacondaPrompt中输入以下命令(以Python3.6为例):```bashconda create--namelabelme python=3.6```然后激活环境:```bashcondaactivate labelme```4.**安装PyQt5**在激活的环境中,输入以下命令安装PyQt5:```bashconda installpyqt5```或者使用pip:```bashpip installpyqt5```5.**安装Labelme**在同一个环境中,使用pip安装Labelme:```bashpip installlabelme``` 6. **启动Labelme**安装完成后,输入以下命令启动Labelme:```bashlabelme```如果出现Labelme的图形界面,则说明安装成功。 ####在Ubuntu系统上安装对于Ubuntu系统(以Python3为例): 1.安装PyQt5:```bashsudo apt-get installpython3-pyqt5```2.安装Labelme:```bashsudo pip3 installlabelme```或者使用`--user`选项安装到用户目录(不需要sudo):```bashpip3install labelme --user```3.启动Labelme:```bashlabelme``` ####常见问题- **网络问题**:如果在安装过程中出现网络超时,可以尝试增加超时时间,例如:```bashpip--default-timeout=100install labelme```或者更换网络环境(如使用手机热点)[^3]。 -**环境变量问题**:在Ubuntu中,如果安装后无法运行`labelme`命令,可能是因为用户安装的脚本目录不在PATH中,可以尝试将`~/.local/bin`添加到PATH中。###相关问题1.如何验证Labelme是否安装成功?2.使用Labelme进行图像标注的基本步骤是什么?3.Labelme支持哪些类型的图像标注?4.如何将Labelme标注的数据转换成其他格式(如COCO)?</think>### 安装Labelme图像标注工具指南 #### 一、Windows系统安装步骤 1. **安装Anaconda** - 下载对应Python版本的Anaconda安装包(推荐Python 3.6+) - 运行安装程序,勾选"Add Anaconda to PATH"选项 2. **创建虚拟环境** 打开`Anaconda Prompt`,执行: ```bash conda create --name=labelme python=3.6 # 创建环境 conda activate labelme # 激活环境 ``` 3. **安装依赖库** ```bash conda install pyqt5 # 安装界面依赖 pip install labelme # 安装Labelme核心 ``` 4. **验证安装** ```bash labelme # 若弹出标注界面即成功 ``` [^2][^4] #### 二、Ubuntu系统安装步骤 ```bash # Python3环境 sudo apt-get install python3-pyqt5 # 安装Qt界面库 sudo pip3 install labelme # 安装Labelme # 验证安装 labelme ``` [^1] #### 三、常见问题解决 1. **网络超时** 安装时添加超时参数: ```bash pip --default-timeout=100 install labelme ``` [^3] 2. **环境冲突** 建议使用虚拟环境(conda或venv)隔离安装 3. **启动失败** 检查PyQt5是否安装成功: ```bash python -c "from PyQt5 import QtWidgets; print(&#39;Success&#39;)" ``` #### 四、首次使用示例 1. 终端输入`labelme`启动 2. 点击`Open`加载图像 3. 使用多边形工具(Polygon)标注目标 4. 保存生成JSON标注文件 ![标注界面示意图](https://example.com/labelme-ui.png) *标注界面示意图(图源:Labelme官方文档)* > **注意**:标注前建议创建专门的项目目录存放图像和标注文件,避免文件路径混乱[^3]。 ### 相关问题 1. Labelme标注的JSON文件如何转换为COCO数据集格式? 2. 使用Labelme进行语义分割标注时有哪些最佳实践? 3. 如何批量处理Labelme生成的JSON标注文件? 4. Labelme与其他标注工具(如LabelImg)相比有哪些优势? 5. 在无GUI界面的服务器上如何使用Labelme进行标注
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