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<!DOCTYPE html>
<!--[if !IE]><!--> <html lang="en"> <!--<![endif]-->
<head>
<title>Home</title>
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</head>
<body>
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<div class="wrapper">
<!-- Start Header-->
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</a>
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<div class="collapse navbar-collapse mega-menu navbar-responsive-collapse">
<ul class="nav navbar-nav">
<li><a href="#home">首页</a></li>
<li><a href="#function">简介</a></li>
<li><a href="#service">服务</a></li>
<li><a href="#gallery">成果</a></li>
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<div class="carousel-inner" role="listbox">
<div class="item active beactive">
<!-- http://download.imagepy.org/image/banner/cell2.jpg -->
<img src="http://download.imagepy.org/image/banner/jingxiang.jpg" alt="...">
<div class="carousel-caption">
<h2>社区活跃</h2>
<p>专业的支持团队，活跃的社区氛围，为大家提供良好的学习环境</p>
</div>
</div>
<div class="item">
<img src="http://download.imagepy.org/image/banner/cell.jpg" alt="...">
<div class="carousel-caption">
<h2>功能丰富</h2>
<p>交互友好，简单易用，集成丰富的图像处理功能，解决常规科研问题游刃有余</p>
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<img src="http://download.imagepy.org/image/banner/ice.jpg" alt="...">
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<h2>免费试用</h2>
<p>致力于为生物，材料，医学等科研工作者提供专业的科研图像处理工具</p>
</div>
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</div>
<div class="col-md-6">
<div class="mb30"></div>
<h5>欢迎使用</h5>
<h2 class="mb15"><strong>ImagePy</strong></h2>
<p>ImagePy 是一款科学图像处理软件，软件具有丰富的图像处理功能和数据分析功能，尤其适合有一定专业知识的非计算机专业任意使用。软件可免费试用，支持功能扩展，任何人可以下载，安装，使用。也欢迎广大爱好者加入社区共同学习，共同为图像处理在科学研究中的应用做出贡献。</p><br>
<p class="mb15">软件可以运行在Windows，Mac，Linux系统上，我们为广大用户准备了绿色安装报，解压后，运行ImagePy.bat即可。</p><br>
<a class="btn btn-product" href="http://download.imagepy.org/ImagePy-64.rar">Win-64 下载</a>
<a class="btn btn-product" href="http://download.imagepy.org/ImagePy-32.rar">Win-32 下载</a>
<!-- <a class="btn btn-product" href="http://download.imagepy.org/ImagePy-Plant.rar">Mac版下载</a> -->
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</div>
<div class="service-desc">
<h5>Github </h5>
<p>https://github.com/Image-Py/imagepy，ImagePy 的源代码在 Github上托管，基于BSD协议，由国内外自由软件工作者共同维护，也欢迎图像编程爱好者学习并参与开发。</p>
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<h5>IMAGE.SC</h5>
<p>image.sc 是 ImagePy 的合作伙伴，是国内外顶尖的科学图像处理软件共同搭建的相互学习，交流平台。 任何 ImagePy 的使用问题都可以在上面讨论，但注意根据论坛的规范，请使用英文交流。</p>
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<h5>QQ:596310256</h5>
<p>ImagePy 官方 QQ群，用于讨论，交流 ImagePy 的常规使用问题，也讨论程序设计及算法问题。 里面汇集了机器视觉，生物，材料等领域颇有热情与建树的科研工作者。</p>
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<div class="headline-left mb30">
<h2 class="headline-brd">功能介绍</h2>
<p>ImagePy具有丰富的图像处理和分析功能，并且依然在快速发展，吸纳行业内最新的成果，在应用与实践中不断成长。简单概括概括如下：</p>
</div>
<ul class="lists-item mb30">
<li><i class="fa fa-check"></i> 常用图上格式数据打开，批量导入，图像浏览，支持 Dicom, Nii 等医学数据格式 </li>
<li><i class="fa fa-check"></i> 友好的界面交互体验，支持图像缩放，伪彩色设定。滤镜支持实时预览，选区，撤销</li>
<li><i class="fa fa-check"></i> 支持色阶，对比度，色相调整，直方图匹配，图像增强，图像滤波，形态学处理</li>
<li><i class="fa fa-check"></i> 角点检测，边缘算子，分水岭，色彩聚类等常用经典算法，应有尽有，开箱即用</li>
<li><i class="fa fa-check"></i> 支持批处理，录制宏，定制工作流，从繁琐的操作中解放劳动力</li>
<li><i class="fa fa-check"></i> 图像处理，数据分析，结果统计，成果报表，全栈功能集成</li>
<li><i class="fa fa-check"></i> 紧跟行业前沿，了解行业动态，吸纳最新的开源成果，动态更新，不断完善</li>
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<div class="counter-item text-center">
<i class="fa fa-users fa-3x" aria-hidden="true"></i>
<h1 class="secondary-color count">6666</h1>
<h4>Clients Worked With</h4>
</div>
</div>
<div class="col-md-3 col-sm-6 col-xs-12">
<div class="counter-item text-center">
<i class="fa fa-leaf fa-3x" aria-hidden="true"></i>
<h1 class="secondary-color count">800</h1>
<h4>Completed Projects</h4>
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<i class="fa fa-trophy fa-3x" aria-hidden="true"></i>
<h1 class="secondary-color count">555</h1>
<h4>Winning Awards</h4>
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<h1 class="secondary-color count">1100</h1>
<h4>Cups of coffee</h4>
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END COUNTER-->
<div class="page-heading">
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<h1 class="title"><span>我们在做什么</span></h1>
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<p class="current">生物图像，材料图像，遥感图像，数据分析，知识分享，技术培训</p>
</div>
</div>
</div>
</div>
</div>
<!--START SERVICE-->
<section class="home-main-contant-style bg-white" id="service">
<div class="cd-home-title">
<h2>商业服务</h2>
<p>在ImagePy成长过程中，也积累了相当的经验，我们愿意与高校，科研机构，企业进行项目合作，共同进步</p>
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<h5>技能培训</h5>
<p>图像处理基础理论，图像处理经典算法讲解。图像软件操作及使用技巧，针对您的研究领域及遇到的问题针对性的分析。</p>
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<h5>生物图像</h5>
<p>显微镜图像分析，细胞特征提取，形态分析，CT，MRI影像处理，血管提取，拓扑结构分析，几何结构测量，密度分析，三维重建。</p>
</div>
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