Update icons, README. Add zh-CN locale
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tzutalin
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README.rst
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README.rst
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LabelImg
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========
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.. image:: logo/logomark.png
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:width: 250px
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:align: center
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========
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.. image:: https://img.shields.io/pypi/v/labelimg.svg
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:target: https://pypi.python.org/pypi/labelimg
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.. image:: https://img.shields.io/travis/tzutalin/labelImg.svg
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:target: https://travis-ci.org/tzutalin/labelImg
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.. image:: /resources/icons/app.png
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:width: 200px
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:align: center
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LabelImg is a graphical image annotation tool.
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It is written in Python and uses Qt for its graphical interface.
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@ -58,7 +56,7 @@ Python 2 + Qt4
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python labelImg.py
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python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
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Python 3 + Qt5
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Python 3 + Qt5 (Recommanded)
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.. code::
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@ -80,28 +78,29 @@ Python 2 + Qt4
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python labelImg.py
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python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
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Python 3 + Qt5 (Works on macOS High Sierra)
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Python 3 + Qt5 (Recommanded)
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.. code::
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brew install qt # will install qt-5.x.x
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brew install qt # Install qt-5.x.x by Homebrew
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brew install libxml2
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or
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pip3 install pyqt5 lxml # Install qt and lxml by pip
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make qt5py3
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python3 labelImg.py
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python3 labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
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As a side note, if mssing pyrcc5 or lxml, try
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pip3 install pyqt5 lxml
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**NEW** Python 3 Virtualenv + Binary
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This avoids a lot of the QT / Python version issues,
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and gives you a nice .app file with a new SVG Icon
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This can avoid a lot of the QT / Python version issues, and gives you a nice .app file with a new SVG Icon
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in your /Applications folder. You can consider this script: build-tools/build-for-macos.sh
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.. code::
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brew install python3
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pip install pipenv
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pipenv --three
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@ -112,25 +111,13 @@ in your /Applications folder. You can consider this script: build-tools/build-fo
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rm -rf build dist
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python setup.py py2app -A
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mv "dist/labelImg.app" /Applications
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Alternate
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Mac OS easiest way to install and run
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STEPS
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git clone https://github.com/tzutalin/labelImg
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pip install PyQt5 lxml
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cd labelImg ##(enter the labelImg directory)
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make qt5py3
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python3 labelImg.py
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Windows
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^^^^^^^
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Download and setup `Python 2.6 or
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later <https://www.python.org/downloads/windows/>`__,
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`PyQt4 <https://www.riverbankcomputing.com/software/pyqt/download>`__
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Install `Python <https://www.python.org/downloads/windows/>`__,
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`PyQt5 <https://www.riverbankcomputing.com/software/pyqt/download5>`__
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and `install lxml <http://lxml.de/installation.html>`__.
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Open cmd and go to the `labelImg <#labelimg>`__ directory
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@ -269,7 +256,7 @@ This is used when creating a dataset automatically, the user can then through al
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**Difficult:**
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The difficult field being set to 1 indicates that the object has been annotated as "difficult", for example an object which is clearly visible but difficult to recognize without substantial use of context.
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According to your deep neural network implementation, you can include or exclude difficult objects during training.
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According to your deep neural network implementation, you can include or exclude difficult objects during training.
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How to contribute
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~~~~~~~~~~~~~~~~~
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<file alias="verify">resources/icons/verify.png</file>
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<file alias="strings">resources/strings/strings.properties</file>
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<file alias="strings-zh-TW">resources/strings/strings-zh-TW.properties</file>
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<file alias="strings-zh-CN">resources/strings/strings-zh-CN.properties</file>
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</qresource>
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</RCC>
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<svg width="64" height="64" xmlns="http://www.w3.org/2000/svg">
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<defs>
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<filter id="svg_10_blur">
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<feGaussianBlur stdDeviation="0" in="SourceGraphic"/>
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</filter>
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</defs>
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<g>
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<title>background</title>
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<rect fill="none" id="canvas_background" height="402" width="582" y="-1" x="-1"/>
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</g>
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<g>
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<title>Layer 1</title>
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<g stroke="null" id="svg_19">
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<path stroke="null" opacity="0.2" id="svg_5" fill="#231F20" d="m58.941458,5.713441c-0.033833,0 -0.067666,0 -0.103037,0c-0.030757,0 -0.056901,-0.003076 -0.087658,0l-23.846159,0c-0.579776,0.026144 -1.900803,0.933485 -2.071506,1.104188l-27.895362,27.904589c-1.479428,1.479428 -1.479428,3.878499 0,5.357927l21.41633,21.425557c0.744327,0.739714 1.711645,1.107264 2.678964,1.107264c0.967318,0 1.937712,-0.36755 2.677426,-1.107264l27.893824,-27.904589c0.170703,-0.170703 1.122643,-1.342558 1.122643,-2.071506l0,-23.933817c0.053825,-1.058052 -0.747403,-1.882349 -1.785463,-1.882349zm-5.900794,10.763528c-1.697805,0 -3.075733,-1.377928 -3.075733,-3.075733s1.377928,-3.075733 3.075733,-3.075733s3.075733,1.377928 3.075733,3.075733s-1.377928,3.075733 -3.075733,3.075733z"/>
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<path stroke="#00bf00" id="svg_8" fill="#2e6fd1" d="m58.941458,2.637708c-0.033833,0 -0.067666,0 -0.103037,0c-0.030757,0 -0.056901,-0.003076 -0.087658,0l-23.846159,0c-0.579776,0.026144 -1.900803,0.933485 -2.071506,1.104188l-27.895362,27.904589c-1.479428,1.479428 -1.479428,3.878499 0,5.357927l21.41633,21.425557c0.744327,0.739714 1.711645,1.107264 2.678964,1.107264c0.967318,0 1.937712,-0.36755 2.677426,-1.107264l27.893824,-27.904589c0.170703,-0.170703 1.122643,-1.342558 1.122643,-2.071506l0,-23.933817c0.053825,-1.058052 -0.747403,-1.882349 -1.785463,-1.882349zm-5.900794,10.763528c-1.697805,0 -3.075733,-1.377928 -3.075733,-3.075733s1.377928,-3.075733 3.075733,-3.075733s3.075733,1.377928 3.075733,3.075733s-1.377928,3.075733 -3.075733,3.075733z"/>
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<text filter="url(#svg_10_blur)" stroke="#000000" transform="matrix(0.5447929800652447,-0.5343019017094763,0.5343019017094763,0.5447929800652447,-3.424396520826477,36.238999138928264) " font-weight="bold" xml:space="preserve" text-anchor="start" font-family="Oswald, sans-serif" font-size="24" id="svg_10" y="36.27526" x="14.460123" stroke-width="0" fill="#ffffff">VOC</text>
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</g>
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</g>
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</svg>
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<?xml version="1.0" standalone="no"?>
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<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 20010904//EN"
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"http://www.w3.org/TR/2001/REC-SVG-20010904/DTD/svg10.dtd">
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<svg version="1.0" xmlns="http://www.w3.org/2000/svg"
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width="256.000000pt" height="256.000000pt" viewBox="0 0 256.000000 256.000000"
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preserveAspectRatio="xMidYMid meet">
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<metadata>
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Created by potrace 1.15, written by Peter Selinger 2001-2017
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</metadata>
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<g transform="translate(0.000000,256.000000) scale(0.100000,-0.100000)"
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fill="#000000" stroke="none">
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<path d="M71 986 l-1 -330 32 45 c18 24 37 47 43 51 12 8 20 381 10 476 l-7
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<path d="M284 1102 c-39 -3 -42 -5 -48 -40 -3 -20 -6 -151 -6 -291 l0 -255 24
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<path d="M415 959 c-3 -13 -4 -150 -3 -304 l3 -280 132 180 c73 99 138 187
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</svg>
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65
resources/strings/strings-zh-CN.properties
Normal file
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resources/strings/strings-zh-CN.properties
Normal file
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saveAsDetail=將标签保存到其他文件
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changeSaveDir=改变存放目录
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openFile=打开文件
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shapeLineColorDetail=更改线条颜色
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resetAll=全部重置
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crtBox=创建区块
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crtBoxDetail=创建一个新的区块
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dupBoxDetail=复制区块
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verifyImg=验证图像
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zoominDetail=放大
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verifyImgDetail=验证图像
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saveDetail=保存标签文件
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openFileDetail=打开图像文件
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fitWidthDetail=调整宽度适应到窗口宽度
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tutorial=YouTube教学
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editLabel=编辑标签
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openAnnotationDetail=打开标签文件
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quit=退出
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shapeFillColorDetail=更改填充颜色
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closeCurDetail=关闭当前文件
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closeCur=关闭文件
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fitWin=调整到窗口大小
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delBox=删除选择的区块
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boxLineColorDetail=选择线框颜色
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originalsize=原始大小
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resetAllDetail=重置所有设定
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zoomoutDetail=放大画面
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save=保存
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saveAs=另存为
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fitWinDetail=缩放到当前窗口大小
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openDir=打开目录
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showHide=显示/隐藏标签
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changeSaveFormat=更改存储格式
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shapeFillColor=填充颜色
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quitApp=退出程序
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dupBox=复制区块
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delBoxDetail=删除区块
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zoomin=放大画面
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info=信息
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openAnnotation=开启标签
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prevImgDetail=上一个图像
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fitWidth=缩放到跟当前画面一样宽
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zoomout=缩小画面
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changeSavedAnnotationDir=更改保存标签文件的预设目录
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nextImgDetail=下一个图像
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originalsizeDetail=放大到原始大小
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prevImg=上一个图像
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tutorialDetail=显示示范内容
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shapeLineColor=形状线条颜色
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boxLineColor=区块线条颜色
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editLabelDetail=修改当前所选的区块颜色
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nextImg=下一个图片
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useDefaultLabel=使用预设标签
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useDifficult=有难度的
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boxLabelText=区块的标签
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labels=标签
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autoSaveMode=自动保存模式
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singleClsMode=单一类别模式
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displayLabel=显示类别
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fileList=文件列表
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files=文件
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advancedMode=专家模式
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advancedModeDetail=切换到专家模式
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showAllBoxDetail=显示所有区块
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hideAllBoxDetail=隐藏所有区块
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