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            <h1 id="seo-header">LSTM应用于验证码识别</h1>
            
            
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<p> <a target="_blank" rel="noopener" href="https://sourceforge.net/projects/vietocr/files/jTessBoxEditor/">jTessBoxEditorFX-2.3.0</a></p>
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src="data:image/png;base64,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" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload></a></p>
<p><a target="_blank" rel="noopener" href="https://tesseract-ocr.github.io/tessdoc/Data-Files">预训练数据</a></p>
<figure class="highlight awk"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br></pre></td><td class="code"><pre><code class="hljs awk"><span class="hljs-comment">#For CentOS 7 run the following as root to install Tesseract with English language traineddata:</span><br>yum -y install yum-utils<br>yum-config-manager --add-repo https:<span class="hljs-regexp">//</span>download.opensuse.org<span class="hljs-regexp">/repositories/</span>home:<span class="hljs-regexp">/Alexander_Pozdnyakov/</span>CentOS_7/<br>sudo rpm --import https:<span class="hljs-regexp">//</span>build.opensuse.org<span class="hljs-regexp">/projects/</span>home:Alexander_Pozdnyakov/public_key<br>yum update<br>yum install tesseract <br>yum install tesseract-langpack-eng<br></code></pre></td></tr></table></figure>

<figure class="highlight livescript"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><code class="hljs livescript"><span class="hljs-comment">#For Win10 to install Tesseract:</span><br><span class="hljs-number">1.</span>下载解压 jTessBoxEditor<br><span class="hljs-number">2.</span>将 &#123;解压目录&#125;<span class="hljs-string">\jTessBoxEditorFX\tesseract-ocr</span> 添加到 Path<br><span class="hljs-number">3.</span>下载解压预训练数据到当前目录<br><span class="hljs-number">4.</span>新建环境变量 TESSDATA_PREFIX ,值为 &#123;解压目录&#125;<span class="hljs-string">\tessdata</span><br></code></pre></td></tr></table></figure>

<p><img src="https://img-cdn.limour.top/blog_wp/2020/07/%E5%BE%AE%E4%BF%A1%E5%9B%BE%E7%89%87_20200710090821.png" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload></p>
<p>终端中运行命令 tesseract –help-extra 显示如上信息表示安装成功</p>
<p><a target="_blank" rel="noopener" href="https://limour.lanzous.com/icIheeh321c"><img src="data:image/png;base64,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" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload></a></p>
<p>自行获取训练所需的验证码</p>
<p>按照<a target="_blank" rel="noopener" href="https://blog.csdn.net/qq_40147863/article/details/82290015">肖鹏伟的《Tesseract-OCR-04-使用 jTessBoxEditor提高文字识别准确率》</a>中的方法生成<code>fdu.ufont.exp0.tif</code>文件</p>
<figure class="highlight stylus"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><code class="hljs stylus">#通过此命令生成fdu<span class="hljs-selector-class">.ufont</span><span class="hljs-selector-class">.exp0</span>.box文件<br>tesseract fdu<span class="hljs-selector-class">.ufont</span><span class="hljs-selector-class">.exp0</span><span class="hljs-selector-class">.tif</span> fdu<span class="hljs-selector-class">.ufont</span><span class="hljs-selector-class">.exp0</span> -l eng <span class="hljs-attr">--psm</span> <span class="hljs-number">8</span> <span class="hljs-attr">--oem</span> <span class="hljs-number">0</span> nobatch box<span class="hljs-selector-class">.train</span> -c tessedit_char_whitelist=abcdefghijklmnopqrstuvwxyzAT-<br></code></pre></td></tr></table></figure>

<p>继续按照肖鹏伟的方法修正<code>.box</code>文件</p>
<figure class="highlight stylus"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br></pre></td><td class="code"><pre><code class="hljs stylus">#将fdu<span class="hljs-selector-class">.ufont</span><span class="hljs-selector-class">.exp0</span>.tif文件、修正后的fdu<span class="hljs-selector-class">.ufont</span><span class="hljs-selector-class">.exp0</span>.box文件一起保存到独立的同一新文件夹下，同目录下运行此.ps1文件即可得到fdu<span class="hljs-selector-class">.traineddata</span><br>tesseract fdu<span class="hljs-selector-class">.ufont</span><span class="hljs-selector-class">.exp0</span><span class="hljs-selector-class">.tif</span> fdu<span class="hljs-selector-class">.ufont</span><span class="hljs-selector-class">.exp0</span> -l enb <span class="hljs-attr">--psm</span> <span class="hljs-number">8</span> lstm<span class="hljs-selector-class">.train</span><br>combine_tessdata -e <span class="hljs-string">&quot;$env:TESSDATA_PREFIX\enb.traineddata&quot;</span> enb<span class="hljs-selector-class">.lstm</span><br><span class="hljs-variable">$PSroot</span> = Get-ChildItem<br><span class="hljs-variable">$PSroot</span> = Split-Path <span class="hljs-variable">$PSroot</span><span class="hljs-selector-class">.Get</span>(<span class="hljs-number">0</span>)<span class="hljs-selector-class">.FullName</span><br><span class="hljs-variable">$fso</span>=New-Object -ComObject Scripting<span class="hljs-selector-class">.FileSystemObject</span><br><span class="hljs-variable">$fso</span><span class="hljs-selector-class">.CreateTextFile</span>(<span class="hljs-string">&#x27;fdu.training_files.txt&#x27;</span>,<span class="hljs-number">2</span>)<span class="hljs-selector-class">.Write</span>(<span class="hljs-string">&quot;$PSroot\fdu.ufont.exp0.lstmf&quot;</span> )<br><span class="hljs-keyword">if</span> (-not (Test-Path -Path output))&#123;mkdir output&#125;<br>lstmtraining <span class="hljs-attr">--model_output</span>=<span class="hljs-string">&quot;$PSroot\output\output&quot;</span> <span class="hljs-attr">--continue_from</span>=<span class="hljs-string">&quot;$PSroot\enb.lstm&quot;</span> <span class="hljs-attr">--train_listfile</span>=<span class="hljs-string">&quot;$PSroot\fdu.training_files.txt&quot;</span> <span class="hljs-attr">--traineddata</span>=<span class="hljs-string">&quot;$env:TESSDATA_PREFIX\enb.traineddata&quot;</span> <span class="hljs-attr">--debug_interval</span> -<span class="hljs-number">1</span> <span class="hljs-attr">--target_error_rate</span> <span class="hljs-number">0.001</span><br>lstmtraining <span class="hljs-attr">--stop_training</span> <span class="hljs-attr">--continue_from</span>=<span class="hljs-string">&quot;$PSroot\output\output_checkpoint&quot;</span> <span class="hljs-attr">--traineddata</span>=<span class="hljs-string">&quot;$env:TESSDATA_PREFIX\enb.traineddata&quot;</span> <span class="hljs-attr">--model_output</span>=<span class="hljs-string">&quot;$PSroot\fdu.traineddata&quot;</span><br></code></pre></td></tr></table></figure>

<p><a target="_blank" rel="noopener" href="https://limour.lanzous.com/ifW3jeireib"><img src="data:image/png;base64,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" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload></a></p>
<p>最终得到如上结果</p>
<p>将得到的<code>fdu.traineddata</code>文件移动到<code>tessdata</code>文件夹下即可通过参数<code>-l fdu</code>进行使用</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br><span class="line">46</span><br><span class="line">47</span><br><span class="line">48</span><br><span class="line">49</span><br><span class="line">50</span><br><span class="line">51</span><br><span class="line">52</span><br><span class="line">53</span><br><span class="line">54</span><br><span class="line">55</span><br><span class="line">56</span><br><span class="line">57</span><br></pre></td><td class="code"><pre><code class="hljs python"><span class="hljs-comment">#此程序用于简单判断训练效果</span><br><span class="hljs-keyword">from</span> PIL <span class="hljs-keyword">import</span> Image<br><span class="hljs-comment">#from itertools import cycle</span><br><span class="hljs-keyword">import</span> os, random, re<br><span class="hljs-keyword">import</span> pytesseract<br>fl = re.<span class="hljs-built_in">compile</span>(<span class="hljs-string">r&#x27;[a-zA-Z-]+&#x27;</span>)<br><span class="hljs-keyword">def</span> <span class="hljs-title function_">clearStr</span>(<span class="hljs-params"><span class="hljs-built_in">str</span></span>):<br>    <span class="hljs-keyword">return</span> <span class="hljs-string">&#x27;&#x27;</span>.join(fl.findall(<span class="hljs-built_in">str</span>))<br><br><span class="hljs-keyword">class</span> <span class="hljs-title class_">Fileset</span>(<span class="hljs-title class_ inherited__">list</span>):<br>    <span class="hljs-keyword">def</span> <span class="hljs-title function_">__init__</span>(<span class="hljs-params">self, name,  ext=<span class="hljs-string">&#x27;&#x27;</span>, _read=<span class="hljs-literal">None</span>, root=<span class="hljs-literal">None</span></span>):<br>        <span class="hljs-keyword">if</span> <span class="hljs-built_in">isinstance</span>(name, <span class="hljs-built_in">str</span>)  :<br>            self.root = os.path.join(root <span class="hljs-keyword">or</span> os.getcwd(), name)<br>            self.extend(f <span class="hljs-keyword">for</span> f <span class="hljs-keyword">in</span> os.listdir(self.root) <span class="hljs-keyword">if</span> f.endswith(ext))<br>            self._read = _read<br>    <span class="hljs-keyword">def</span> <span class="hljs-title function_">__getitem__</span>(<span class="hljs-params">self, index</span>):<br>        <span class="hljs-keyword">if</span> <span class="hljs-built_in">isinstance</span>(index, <span class="hljs-built_in">int</span>):<span class="hljs-comment"># index是索引</span><br>            <span class="hljs-keyword">return</span> os.path.join(self.root, <span class="hljs-built_in">super</span>().__getitem__(index))<br>        <span class="hljs-keyword">else</span>:<span class="hljs-comment"># index是切片</span><br>            fileset = Fileset(<span class="hljs-literal">None</span>)<br>            fileset.root = self.root<br>            fileset._read = self._read<br>            fileset.extend(<span class="hljs-built_in">super</span>().__getitem__(index))<br>            <span class="hljs-keyword">return</span> fileset<br>    <span class="hljs-keyword">def</span> <span class="hljs-title function_">getFileName</span>(<span class="hljs-params">self, index</span>):<br>        fname, ext = os.path.splitext(<span class="hljs-built_in">super</span>().__getitem__(index))<br>        <span class="hljs-keyword">return</span> fname<br>    <span class="hljs-keyword">def</span> <span class="hljs-title function_">__iter__</span>(<span class="hljs-params">self</span>):<br>        <span class="hljs-keyword">if</span> self._read: <span class="hljs-keyword">return</span> (self._read(os.path.join(self.root, f)) <span class="hljs-keyword">for</span> f <span class="hljs-keyword">in</span> <span class="hljs-built_in">super</span>().__iter__())<br>        <span class="hljs-keyword">else</span>: <span class="hljs-keyword">return</span> (os.path.join(self.root, f) <span class="hljs-keyword">for</span> f <span class="hljs-keyword">in</span> <span class="hljs-built_in">super</span>().__iter__())<br>    <span class="hljs-keyword">def</span> <span class="hljs-title function_">__call__</span>(<span class="hljs-params">self</span>):<br>        retn = random.choice(self)<br>        <span class="hljs-keyword">if</span> self._read: <span class="hljs-keyword">return</span> self._read(retn)<br>        <span class="hljs-keyword">else</span>: <span class="hljs-keyword">return</span> retn<br><br><span class="hljs-comment"># def fopen(path):</span><br>    <span class="hljs-comment"># with open(path, &#x27;rb&#x27;) as f:</span><br>        <span class="hljs-comment"># return f.read()</span><br><span class="hljs-comment"># #from tesOCR import tesOCR as OCR1</span><br><span class="hljs-comment"># sample = Fileset(&#x27;Captcha&#x27;, &#x27;.jpg&#x27;, fopen)</span><br>sample = Fileset(<span class="hljs-string">&#x27;Captcha&#x27;</span>, <span class="hljs-string">&#x27;.jpg&#x27;</span>, Image.<span class="hljs-built_in">open</span>)<br><br>config1 = <span class="hljs-string">&#x27;--psm 8&#x27;</span><br><span class="hljs-keyword">def</span> <span class="hljs-title function_">OCR1</span>(<span class="hljs-params">img</span>):<br>     <span class="hljs-keyword">return</span> pytesseract.image_to_string(img, lang=<span class="hljs-string">&#x27;fdu&#x27;</span>, config=config1)<br><br>config2 = <span class="hljs-string">&quot;--psm 8 --oem 0 -c tessedit_char_whitelist=abcdefghijklmnopqrstuvwxyzAT-&quot;</span><br><span class="hljs-keyword">def</span> <span class="hljs-title function_">OCR2</span>(<span class="hljs-params">img</span>):<br>     <span class="hljs-keyword">return</span> pytesseract.image_to_string(img, lang=<span class="hljs-string">&#x27;eng&#x27;</span>, config=config2)<br><br><span class="hljs-keyword">for</span> a <span class="hljs-keyword">in</span> sample:<br>    b = a.convert(<span class="hljs-string">&quot;L&quot;</span>)<br>    x = clearStr(OCR1(b))<br>    y = clearStr(OCR2(b))<br>    <span class="hljs-keyword">if</span> x != y:<br>        display(a)<br>        <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;LSTM is <span class="hljs-subst">&#123;x&#125;</span> ; Legacy is <span class="hljs-subst">&#123;y&#125;</span>&quot;</span>)<br></code></pre></td></tr></table></figure>

<p><a target="_blank" rel="noopener" href="https://limour.lanzous.com/imK6me9lurg"><img 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XQ+N04RnEKpzOkU0XlE742l+3PXdd4Sbt4B/66gAikFQ5kz4N8UmKVZwA/4T+ZJD3Ycv6PPSKtzLJoD30zn3O5CceyXa3U6OC4ZMqLY1eK2NkrXcfaomIUCICmek3frIDpzuvt7iz8hSAqjiOuKRh9WCqhkj8p81Xt0IFVqQ3Rwb7RlfMCnSp/ExfGPBVIOLSmJe7ADPlEZxAT8gA8w2Q+ZdZ26bpFWRy9xHP9As4Bf55rVh3tWbeiRcvf3H6mPrgIf3AQCAAAAAElFTkSuQmCC" 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<p>我的结果和python调用封装</p>
<p>注释:  </p>
<ol>
<li><a target="_blank" rel="noopener" href="https://sourceforge.net/projects/vietocr/files/jTessBoxEditor/">jTessBoxEditor</a>中带有FX表示支持中文<br>2.预训练数据中22.3Mb的是Legacy数据,14.6Mb的是LSTM数据,语言均为eng<br>3.”tessedit_char_whitelist&#x3D;”后面所接内容为验证码中可能出现的字符</li>
</ol>

                
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    var el = (CONFIG.anchorjs.element || 'h1,h2,h3,h4,h5,h6').split(',');
    var res = [];
    for (var item of el) {
      res.push('.markdown-body > ' + item.trim());
    }
    if (CONFIG.anchorjs.placement === 'left') {
      window.anchors.options.class = 'anchorjs-link-left';
    }
    window.anchors.add(res.join(', '));

    Fluid.events.registerRefreshCallback(function() {
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        var el = (CONFIG.anchorjs.element || 'h1,h2,h3,h4,h5,h6').split(',');
        var res = [];
        for (var item of el) {
          res.push('.markdown-body > ' + item.trim());
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        if (CONFIG.anchorjs.placement === 'left') {
          anchors.options.class = 'anchorjs-link-left';
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        anchors.add(res.join(', '));
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</script>


<script>
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  <script>Fluid.plugins.imageCaption();</script>

  <script  src="/js/local-search.js" ></script>


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  <noscript>
    <div class="noscript-warning">Blog works best with JavaScript enabled</div>
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