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    <title>DEV Community: Ayush Bathrey</title>
    <description>The latest articles on DEV Community by Ayush Bathrey (@ayushbathrey).</description>
    <link>https://dev.to/ayushbathrey</link>
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      <title>DEV Community: Ayush Bathrey</title>
      <link>https://dev.to/ayushbathrey</link>
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    <item>
      <title>Kirana automated invoice generator</title>
      <dc:creator>Ayush Bathrey</dc:creator>
      <pubDate>Sat, 23 May 2020 08:35:40 +0000</pubDate>
      <link>https://dev.to/ayushbathrey/kirana-automated-invoice-generator-4ael</link>
      <guid>https://dev.to/ayushbathrey/kirana-automated-invoice-generator-4ael</guid>
      <description>&lt;h2&gt;
  
  
  My Final Project
&lt;/h2&gt;

&lt;p&gt;Edge computing-based invoice generator and can differentiate up to 46 classes with respect to the size of the product.&lt;/p&gt;

&lt;h2&gt;
  
  
  Demo Link
&lt;/h2&gt;

&lt;p&gt;&lt;a href="https://www.youtube.com/embed/xyTsDTEi42E"&gt;https://www.youtube.com/embed/xyTsDTEi42E&lt;/a&gt;&lt;/p&gt;

&lt;h2&gt;
  
  
  Link to Code
&lt;/h2&gt;

&lt;p&gt;[Note]: # &lt;/p&gt;
&lt;div class="ltag-github-readme-tag"&gt;
  &lt;div class="readme-overview"&gt;
    &lt;h2&gt;
      &lt;img src="https://res.cloudinary.com/practicaldev/image/fetch/s--vJ70wriM--/c_limit%2Cf_auto%2Cfl_progressive%2Cq_auto%2Cw_880/https://practicaldev-herokuapp-com.freetls.fastly.net/assets/github-logo-ba8488d21cd8ee1fee097b8410db9deaa41d0ca30b004c0c63de0a479114156f.svg" alt="GitHub logo"&gt;
      &lt;a href="https://github.com/ayushbathrey"&gt;
        ayushbathrey
      &lt;/a&gt; / &lt;a href="https://github.com/ayushbathrey/Kirana-Web-App"&gt;
        Kirana-Web-App
      &lt;/a&gt;
    &lt;/h2&gt;
    &lt;h3&gt;
      
    &lt;/h3&gt;
  &lt;/div&gt;
  &lt;div class="ltag-github-body"&gt;
    
&lt;div id="readme" class="md"&gt;
&lt;h1&gt;
How To Test Object Detection Classifier for Multiple Objects Using TensorFlow (GPU) on Windows 10&lt;/h1&gt;
&lt;h2&gt;
Brief Summary&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Last updated: 10/18/2019 with TensorFlow v1.14&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;What this model can predict/detect ?&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt; It can check upto 46 different items , which may have brand but different size
    &lt;/p&gt;
&lt;h2&gt;
Brands it can detect:&lt;/h2&gt;
    &lt;ul&gt;
    &lt;li&gt; 1. Coke Glass bottle , Can , Plastic bottle 300ml to 2L.&lt;/li&gt;
    &lt;li&gt; 2. Colgate Small , Medium , Size , Plax.&lt;/li&gt;
    &lt;li&gt; 3. Nescafe Cappuccino , Gold , Classic availabe in small and medium size.&lt;/li&gt;
    &lt;li&gt; 4. Toothbush.&lt;/li&gt;
    &lt;li&gt; 5. Gooday biscuit small , medium , large.&lt;/li&gt;
    &lt;li&gt; 6. Lays small , medium , large/family.&lt;/li&gt;
    &lt;li&gt; 7. Brittania Toast small , medium, large.&lt;/li&gt;
    &lt;ul&gt;
I also made a YouTube video that walks through this tutorial. Any discrepancies between the video and this written tutorial are due to updates required for using newer versions of TensorFlow
&lt;p&gt;&lt;strong&gt;If there are differences between this written tutorial and the video, follow the&lt;/strong&gt;…&lt;/p&gt;
&lt;/ul&gt;
&lt;/ul&gt;
&lt;/div&gt;
  &lt;/div&gt;
  &lt;div class="gh-btn-container"&gt;&lt;a class="gh-btn" href="https://github.com/ayushbathrey/Kirana-Web-App"&gt;View on GitHub&lt;/a&gt;&lt;/div&gt;
&lt;/div&gt;


&lt;h2&gt;
  
  
  How I built it (what's the stack? did I run into issues or discover something new along the way?)
&lt;/h2&gt;

&lt;ol&gt;
&lt;li&gt;Tensorflow object detection API.&lt;/li&gt;
&lt;li&gt;Flask Web development Framework.&lt;/li&gt;
&lt;li&gt;HTML, CSS, JavaScript, Bootstrap, Jquery.&lt;/li&gt;
&lt;/ol&gt;

&lt;h2&gt;
  
  
  Experience
&lt;/h2&gt;

&lt;p&gt;This was project was pretty exciting to work, the most time-consuming part of the development was dataset collection (as no official dataset was present) and image labeling part.&lt;/p&gt;

&lt;p&gt;[Final Note]: # Finally my hard work paid off and was called for an interview via this project.&lt;/p&gt;

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      <category>octograd2020</category>
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