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README.html

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    <title>演示系统示例 &#8212; demo_system_algorithm 0.1 documentation</title>
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  <section id="id1">
<h1>演示系统示例<a class="headerlink" href="#id1" title="Link to this heading">¶</a></h1>
<section id="id2">
<h2>概述<a class="headerlink" href="#id2" title="Link to this heading">¶</a></h2>
<p>所有示例通过 Python 接口实现下位机推理，前处理(数据标准化/归一化、通道变换)和反量化都已经加入网络中，下位机推理结果返回PC端做后处理，结果保存在模型工程目录下。提供源码地址、权重文件、nbg文件、测试图片。</p>
<ul>
<li><p>依赖安装</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>install<span class="w"> </span>-r<span class="w"> </span>requirements.txt
</pre></div>
</div>
</li>
</ul>
</section>
<section id="deeplab-mobilnet-v3">
<h2>deeplab_mobilnet_v3<a class="headerlink" href="#deeplab-mobilnet-v3" title="Link to this heading">¶</a></h2>
<p>语义分割模型，源码地址为：<a class="reference external" href="https://github.com/bubbliiiing/deeplabv3-plus-pytorch.git">https://github.com/bubbliiiing/deeplabv3-plus-pytorch.git</a></p>
<ul>
<li><p>输入、输出信息</p>
<div class="highlight-text notranslate"><div class="highlight"><pre><span></span>INPUT:0
DATA_FORMAT:UINT8
NUM_OF_DIMENSION:4
SIZES_OF_DIMENSION:1536 512 1 1 0 0
QUANT_FORMAT:NONE
OUTPUT:0
DATA_FORMAT:FP32
NUM_OF_DIMENSION:4
SIZES_OF_DIMENSION:512 512 21 1 0 0
QUANT_FORMAT:NONE
</pre></div>
</div>
</li>
<li><p>后处理流程</p>
<ul class="simple">
<li><p>概率转换</p></li>
<li><p>预测类别生成</p></li>
<li><p>尺寸还原</p></li>
<li><p>标签映射</p></li>
</ul>
</li>
<li><p>执行</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>demo_deeplabv3.py
</pre></div>
</div>
</li>
<li><p>结果保存在test_src/models/deeplab_mobilnet_v3/result.jpg
<img alt="本地示例图" src="test_src/models/deeplab_mobilnet_v3/result.jpg" /></p></li>
</ul>
</section>
<section id="yolov5s-seg">
<h2>yolov5s-seg<a class="headerlink" href="#yolov5s-seg" title="Link to this heading">¶</a></h2>
<p>实例分割模型，源码地址：<a class="reference external" href="https://github.com/ultralytics/yolov5.git">https://github.com/ultralytics/yolov5.git</a></p>
<ul>
<li><p>输入、输出信息</p>
<div class="highlight-text notranslate"><div class="highlight"><pre><span></span>INPUT:0
DATA_FORMAT:UINT8
NUM_OF_DIMENSION:4
SIZES_OF_DIMENSION:1920 640 1 1 0 0
QUANT_FORMAT:NONE
OUTPUT:0
DATA_FORMAT:FP32
NUM_OF_DIMENSION:3
SIZES_OF_DIMENSION:117 25200 1 0 0 0
QUANT_FORMAT:NONE
OUTPUT:1
DATA_FORMAT:FP32
NUM_OF_DIMENSION:4
SIZES_OF_DIMENSION:160 160 32 1 0 0
QUANT_FORMAT:NONE
</pre></div>
</div>
</li>
<li><p>后处理流程</p>
<ul class="simple">
<li><p>NMS</p></li>
<li><p>遍历检测预测</p></li>
<li><p>颜色和掩码可视化</p></li>
<li><p>掩码叠加</p></li>
<li><p>绘制检测框和文本标签</p></li>
</ul>
</li>
<li><p>执行</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>demo_yolov5s_seg.py
</pre></div>
</div>
</li>
<li><p>结果保存在/yolov5s-seg/result.jpg
<img alt="本地示例图" src="test_src/models/yolov5s-seg/result.jpg" /></p></li>
</ul>
</section>
<section id="resnet18">
<h2>resnet18<a class="headerlink" href="#resnet18" title="Link to this heading">¶</a></h2>
<p>分类模型，源码地址：<a class="reference external" href="https://github.com/ultralytics/yolov5.git">https://github.com/ultralytics/yolov5.git</a></p>
<ul>
<li><p>输入、输出信息</p>
<div class="highlight-text notranslate"><div class="highlight"><pre><span></span>INPUT:0
 DATA_FORMAT:UINT8
 NUM_OF_DIMENSION:4
 SIZES_OF_DIMENSION:672 224 1 1 0 0
 QUANT_FORMAT:NONE
OUTPUT:0
 DATA_FORMAT:FP32
 NUM_OF_DIMENSION:2
 SIZES_OF_DIMENSION:1000 1 0 0 0 0
 QUANT_FORMAT:NONE
</pre></div>
</div>
</li>
<li><p>后处理流程</p>
<ul class="simple">
<li><p>softmax</p></li>
<li><p>topk</p></li>
</ul>
</li>
<li><p>执行</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>demo_resnet18.py
</pre></div>
</div>
</li>
<li><p>结果保存在/resnet18/result.jpg
<img alt="本地示例图" src="test_src/models/resnet18/result.jpg" /></p></li>
</ul>
<blockquote>
<div><p><em>作者 {{liangliangou}}</em></p>
</div></blockquote>
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