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<!DOCTYPE html>
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anaconda 配置 yolov3 环境
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<a class="article-category-link" href="/categories/python/">python</a> / <a class="article-category-link" href="/categories/python/%E6%9C%BA%E5%99%A8%E8%A7%86%E8%A7%89/">机器视觉</a>
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<h2 id="1、-使用清华镜像创建环境"><a href="#1、-使用清华镜像创建环境" class="headerlink" title="1、 使用清华镜像创建环境"></a>1、 使用清华镜像创建环境</h2><p>输入：</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></pre></td><td class="code"><pre><span class="line">conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/</span><br><span class="line">conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/</span><br><span class="line">conda config --set show_channel_urls yes</span><br><span class="line">conda create -n yolo python=<span class="number">3.6</span></span><br></pre></td></tr></table></figure>
<p>(忽略图中因为打错字母导致的报错…)</p>
<p><img src="https://img-blog.csdnimg.cn/20200316001002423.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ1NTA0MTE5,size_16,color_FFFFFF,t_70" alt="在这里插入图片描述"></p>
<a id="more"></a>
<h2 id="2、进入yolo环境"><a href="#2、进入yolo环境" class="headerlink" title="2、进入yolo环境"></a>2、进入yolo环境</h2><p>输入：</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">conda activate yolo</span><br></pre></td></tr></table></figure>
<p><img src="https://img-blog.csdnimg.cn/20200316001211529.png" alt="在这里插入图片描述"></p>
<h2 id="3、更换pip源下载"><a href="#3、更换pip源下载" class="headerlink" title="3、更换pip源下载"></a>3、更换pip源下载</h2><p>** 1、下载keras：**</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></pre></td><td class="code"><pre><span class="line"><span class="comment"># 不更换国内源的命令</span></span><br><span class="line"><span class="comment"># 超时失败是常有的事</span></span><br><span class="line">pip install keras==<span class="number">2.1</span><span class="number">.5</span> </span><br><span class="line"><span class="comment"># 更换国内源</span></span><br><span class="line">pip install -i https://pypi.tuna.tsinghua.edu.cn/simple keras==<span class="number">2.1</span><span class="number">.5</span></span><br><span class="line"><span class="comment"># pip install -i// + 链接 + //keras==2.1.5（keras的版本）</span></span><br></pre></td></tr></table></figure>
<p><img src="https://img-blog.csdnimg.cn/20200316003557394.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ1NTA0MTE5,size_16,color_FFFFFF,t_70" alt="在这里插入图片描述"><br><strong>2、下载 tensorflow ：</strong></p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">pip install -i https://pypi.tuna.tsinghua.edu.cn/simple tensorflow-gpu==<span class="number">1.6</span><span class="number">.0</span></span><br></pre></td></tr></table></figure>
<p><img src="https://img-blog.csdnimg.cn/20200316004333255.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ1NTA0MTE5,size_16,color_FFFFFF,t_70" alt="在这里插入图片描述"></p>
<p><strong>3、下载 Pillow</strong></p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">pip install -i https://pypi.tuna.tsinghua.edu.cn/simple Pillow</span><br></pre></td></tr></table></figure>
<p><img src="https://img-blog.csdnimg.cn/2020031600472232.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ1NTA0MTE5,size_16,color_FFFFFF,t_70" alt="在这里插入图片描述"><br><strong>4、安装 matplotlib</strong></p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">pip install -i https://pypi.tuna.tsinghua.edu.cn/simple matplotlib</span><br></pre></td></tr></table></figure>
<p><img src="https://img-blog.csdnimg.cn/20200316004849304.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ1NTA0MTE5,size_16,color_FFFFFF,t_70" alt="在这里插入图片描述"><br><strong>5、下载 ffmpeg</strong></p>
<figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">pip install -i https://pypi.tuna.tsinghua.edu.cn/simple ffmpeg</span><br></pre></td></tr></table></figure>
<p>或</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></pre></td><td class="code"><pre><span class="line">conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free</span><br><span class="line">conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main</span><br><span class="line">conda config --set show_channel_urls yes</span><br><span class="line">conda install ffmpeg</span><br></pre></td></tr></table></figure>
<p><img src="https://img-blog.csdnimg.cn/20200316005227363.png" alt="在这里插入图片描述"><br><strong>6、安装 opencv</strong></p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">pip install -i https://pypi.tuna.tsinghua.edu.cn/simple opencv-contrib-python</span><br></pre></td></tr></table></figure>
<p><img src="https://img-blog.csdnimg.cn/20200316005544144.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ1NTA0MTE5,size_16,color_FFFFFF,t_70" alt="在这里插入图片描述"></p>
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var grt= new Date("06/01/2020 00:00:00");//在此处修改你的建站时间，格式：月/日/年 时:分:秒
now.setTime(now.getTime()+250);
days = (now - grt ) / 1000 / 60 / 60 / 24; dnum = Math.floor(days);
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seconds = (now - grt ) / 1000 - (24 * 60 * 60 * dnum) - (60 * 60 * hnum) - (60 * mnum);
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