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diff --git a/docs/posts/2020-01-16-Image-Classifier-Using-Turicreate.html b/docs/posts/2020-01-16-Image-Classifier-Using-Turicreate.html deleted file mode 100644 index 70fe244..0000000 --- a/docs/posts/2020-01-16-Image-Classifier-Using-Turicreate.html +++ /dev/null @@ -1,360 +0,0 @@ -<!DOCTYPE html> -<html lang="en"> -<head> - - <meta http-equiv="X-UA-Compatible" content="IE=edge"> - <meta http-equiv="content-type" content="text/html; charset=utf-8"> - <meta name="viewport" content="width=device-width, initial-scale=1.0"> - <meta name="theme-color" content="#6a9fb5"> - - <title>Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire</title> - - <!-- - <link rel="stylesheet" href="https://unpkg.com/latex.css/style.min.css" /> - --> - - <link rel="stylesheet" href="/assets/c-hyde.css"> - - <link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Abril+Fatface"> - <link rel="stylesheet" href="https://fonts.googleapis.com/css?family=PT+Sans:400,400italic,700"> - - <link rel="stylesheet" href="/assets/main.css"> - <meta name="viewport" content="width=device-width, initial-scale=1.0"> - <meta name="og:site_name" content="Navan Chauhan"> - <link rel="canonical" href="https://web.navan.dev/posts/2020-01-16-Image-Classifier-Using-Turicreate.html"> - <meta name="twitter:url" content="https://web.navan.dev/posts/2020-01-16-Image-Classifier-Using-Turicreate.html"> - <meta name="og:url" content="https://web.navan.dev/posts/2020-01-16-Image-Classifier-Using-Turicreate.html"> - <meta name="twitter:title" content="Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire"> - <meta name="og:title" content="Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire"> - <meta name="description" content="Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle"> - <meta name="twitter:description" content="Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle"> - <meta name="og:description" content="Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle"> - <meta name="twitter:card" content="summary_large_image"> - <meta name="viewport" content="width=device-width, initial-scale=1.0"> - <link rel="shortcut icon" href="/images/favicon.png" type="image/png"> - <link href="/feed.rss" type="application/atom+xml" rel="alternate" title="Sitewide Atom feed"> - <meta name="twitter:image" content="https://web.navan.dev/images/opengraph/posts/2020-01-16-Image-Classifier-Using-Turicreate.png"> - <meta name="og:image" content="https://web.navan.dev/images/opengraph/posts/2020-01-16-Image-Classifier-Using-Turicreate.png"> - <meta name="google-site-verification" content="LVeSZxz-QskhbEjHxOi7-BM5dDxTg53x2TwrjFxfL0k"> - <script data-goatcounter="https://navanchauhan.goatcounter.com/count" - async src="//gc.zgo.at/count.js"></script> - <script defer data-domain="web.navan.dev" src="https://plausible.io/js/plausible.js"></script> - <link rel="manifest" href="/manifest.json"> - -</head> -<body class="theme-base-0d"> - <div class="sidebar"> - <div class="container sidebar-sticky"> - <div class="sidebar-about"> - <h1><a href="/">Navan</a></h1> - <p class="lead" id="random-lead">Alea iacta est.</p> - </div> - - <ul class="sidebar-nav"> - <li><a class="sidebar-nav-item" href="/about/">about/links</a></li> - <li><a class="sidebar-nav-item" href="/posts/">posts</a></li> - <li><a class="sidebar-nav-item" href="/3D-Designs/">3D designs</a></li> - <li><a class="sidebar-nav-item" href="/feed.rss">RSS Feed</a></li> - <li><a class="sidebar-nav-item" href="/colophon/">colophon</a></li> - </ul> - <div class="copyright"><p>© 2019-2024. Navan Chauhan <br> <a href="/feed.rss">RSS</a></p></div> - </div> -</div> - -<script> -let phrases = [ - "Something Funny", "Veni, vidi, vici", "Alea iacta est", "In vino veritas", "Acta, non verba", "Castigat ridendo mores", - "Cui bono?", "Memento vivere", "अहम् ब्रह्मास्मि", "अनुगच्छतु प्रवाहं", "चरन्मार्गान्विजानाति", "coq de cheval", "我愛啤酒" - ]; - -let new_phrase = phrases[Math.floor(Math.random()*phrases.length)]; - -let lead = document.getElementById("random-lead"); -lead.innerText = new_phrase; -</script> - <div class="content container"> - - <div class="post"> - <h1 id="creating-a-custom-image-classifier-using-turicreate-to-detect-smoke-and-fire">Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire</h1> - -<p><em>For setting up Kaggle with Google Colab, please refer to <a rel="noopener" target="_blank" href="/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab"> my previous post</a></em></p> - -<h2 id="dataset">Dataset</h2> - -<h3 id="mounting-google-drive">Mounting Google Drive</h3> - -<div class="codehilite"> -<pre><span></span><code><span class="kn">import</span> <span class="nn">os</span> -<span class="kn">from</span> <span class="nn">google.colab</span> <span class="kn">import</span> <span class="n">drive</span> -<span class="n">drive</span><span class="o">.</span><span class="n">mount</span><span class="p">(</span><span class="s1">'/content/drive'</span><span class="p">)</span> -</code></pre> -</div> - -<h3 id="downloading-dataset-from-kaggle">Downloading Dataset from Kaggle</h3> - -<div class="codehilite"> -<pre><span></span><code><span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s1">'KAGGLE_CONFIG_DIR'</span><span class="p">]</span> <span class="o">=</span> <span class="s2">"/content/drive/My Drive/"</span> -<span class="err">!</span><span class="n">kaggle</span> <span class="n">datasets</span> <span class="n">download</span> <span class="n">ashutosh69</span><span class="o">/</span><span class="n">fire</span><span class="o">-</span><span class="ow">and</span><span class="o">-</span><span class="n">smoke</span><span class="o">-</span><span class="n">dataset</span> -<span class="err">!</span><span class="n">unzip</span> <span class="s2">"fire-and-smoke-dataset.zip"</span> -</code></pre> -</div> - -<h2 id="pre-processing">Pre-Processing</h2> - -<div class="codehilite"> -<pre><span></span><code><span class="nt">!mkdir</span><span class="na"> default smoke fire</span> -</code></pre> -</div> - -<p>\</p> - -<div class="codehilite"> -<pre><span></span><code><span class="nt">!ls</span><span class="na"> data/data/img_data/train/default/*.jpg</span> -</code></pre> -</div> - -<p>\</p> - -<div class="codehilite"> -<pre><span></span><code><span class="nt">img_1002.jpg</span><span class="na"> img_20.jpg img_519.jpg img_604.jpg img_80.jpg</span> -<span class="na">img_1003.jpg img_21.jpg img_51.jpg img_60.jpg img_8.jpg</span> -<span class="na">img_1007.jpg img_22.jpg img_520.jpg img_61.jpg img_900.jpg</span> -<span class="na">img_100.jpg img_23.jpg img_521.jpg 'img_62 (2).jpg' img_920.jpg</span> -<span class="na">img_1014.jpg img_24.jpg 'img_52 (2).jpg' img_62.jpg img_921.jpg</span> -<span class="na">img_1018.jpg img_29.jpg img_522.jpg 'img_63 (2).jpg' img_922.jpg</span> -<span class="na">img_101.jpg img_3000.jpg img_523.jpg img_63.jpg img_923.jpg</span> -<span class="na">img_1027.jpg img_335.jpg img_524.jpg img_66.jpg img_924.jpg</span> -<span class="na">img_102.jpg img_336.jpg img_52.jpg img_67.jpg img_925.jpg</span> -<span class="na">img_1042.jpg img_337.jpg img_530.jpg img_68.jpg img_926.jpg</span> -<span class="na">img_1043.jpg img_338.jpg img_531.jpg img_700.jpg img_927.jpg</span> -<span class="na">img_1046.jpg img_339.jpg 'img_53 (2).jpg' img_701.jpg img_928.jpg</span> -<span class="na">img_1052.jpg img_340.jpg img_532.jpg img_702.jpg img_929.jpg</span> -<span class="na">img_107.jpg img_341.jpg img_533.jpg img_703.jpg img_930.jpg</span> -<span class="na">img_108.jpg img_3.jpg img_537.jpg img_704.jpg img_931.jpg</span> -<span class="na">img_109.jpg img_400.jpg img_538.jpg img_705.jpg img_932.jpg</span> -<span class="na">img_10.jpg img_471.jpg img_539.jpg img_706.jpg img_933.jpg</span> -<span class="na">img_118.jpg img_472.jpg img_53.jpg img_707.jpg img_934.jpg</span> -<span class="na">img_12.jpg img_473.jpg img_540.jpg img_708.jpg img_935.jpg</span> -<span class="na">img_14.jpg img_488.jpg img_541.jpg img_709.jpg img_938.jpg</span> -<span class="na">img_15.jpg img_489.jpg 'img_54 (2).jpg' img_70.jpg img_958.jpg</span> -<span class="na">img_16.jpg img_490.jpg img_542.jpg img_710.jpg img_971.jpg</span> -<span class="na">img_17.jpg img_491.jpg img_543.jpg 'img_71 (2).jpg' img_972.jpg</span> -<span class="na">img_18.jpg img_492.jpg img_54.jpg img_71.jpg img_973.jpg</span> -<span class="na">img_19.jpg img_493.jpg 'img_55 (2).jpg' img_72.jpg img_974.jpg</span> -<span class="na">img_1.jpg img_494.jpg img_55.jpg img_73.jpg img_975.jpg</span> -<span class="na">img_200.jpg img_495.jpg img_56.jpg img_74.jpg img_980.jpg</span> -<span class="na">img_201.jpg img_496.jpg img_57.jpg img_75.jpg img_988.jpg</span> -<span class="na">img_202.jpg img_497.jpg img_58.jpg img_76.jpg img_9.jpg</span> -<span class="na">img_203.jpg img_4.jpg img_59.jpg img_77.jpg</span> -<span class="na">img_204.jpg img_501.jpg img_601.jpg img_78.jpg</span> -<span class="na">img_205.jpg img_502.jpg img_602.jpg img_79.jpg</span> -<span class="na">img_206.jpg img_50.jpg img_603.jpg img_7.jpg</span> -</code></pre> -</div> - -<p>The image files are not actually JPEG, thus we first need to save them in the correct format for Turicreate</p> - -<div class="codehilite"> -<pre><span></span><code><span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span> -<span class="kn">import</span> <span class="nn">glob</span> - - -<span class="n">folders</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"default"</span><span class="p">,</span><span class="s2">"smoke"</span><span class="p">,</span><span class="s2">"fire"</span><span class="p">]</span> -<span class="k">for</span> <span class="n">folder</span> <span class="ow">in</span> <span class="n">folders</span><span class="p">:</span> - <span class="n">n</span> <span class="o">=</span> <span class="mi">1</span> - <span class="k">for</span> <span class="n">file</span> <span class="ow">in</span> <span class="n">glob</span><span class="o">.</span><span class="n">glob</span><span class="p">(</span><span class="s2">"./data/data/img_data/train/"</span> <span class="o">+</span> <span class="n">folder</span> <span class="o">+</span> <span class="s2">"/*.jpg"</span><span class="p">):</span> - <span class="n">im</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">file</span><span class="p">)</span> - <span class="n">rgb_im</span> <span class="o">=</span> <span class="n">im</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s1">'RGB'</span><span class="p">)</span> - <span class="n">rgb_im</span><span class="o">.</span><span class="n">save</span><span class="p">((</span><span class="n">folder</span> <span class="o">+</span> <span class="s2">"/"</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">n</span><span class="p">)</span> <span class="o">+</span> <span class="s2">".jpg"</span><span class="p">),</span> <span class="n">quality</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span> - <span class="n">n</span> <span class="o">+=</span><span class="mi">1</span> - <span class="k">for</span> <span class="n">file</span> <span class="ow">in</span> <span class="n">glob</span><span class="o">.</span><span class="n">glob</span><span class="p">(</span><span class="s2">"./data/data/img_data/train/"</span> <span class="o">+</span> <span class="n">folder</span> <span class="o">+</span> <span class="s2">"/*.jpg"</span><span class="p">):</span> - <span class="n">im</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">file</span><span class="p">)</span> - <span class="n">rgb_im</span> <span class="o">=</span> <span class="n">im</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s1">'RGB'</span><span class="p">)</span> - <span class="n">rgb_im</span><span class="o">.</span><span class="n">save</span><span class="p">((</span><span class="n">folder</span> <span class="o">+</span> <span class="s2">"/"</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">n</span><span class="p">)</span> <span class="o">+</span> <span class="s2">".jpg"</span><span class="p">),</span> <span class="n">quality</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span> - <span class="n">n</span> <span class="o">+=</span><span class="mi">1</span> -</code></pre> -</div> - -<p>\</p> - -<div class="codehilite"> -<pre><span></span><code><span class="nt">!mkdir</span><span class="na"> train</span> -<span class="na">!mv default ./train</span> -<span class="na">!mv smoke ./train</span> -<span class="na">!mv fire ./train</span> -</code></pre> -</div> - -<h2 id="making-the-image-classifier">Making the Image Classifier</h2> - -<h3 id="making-an-sframe">Making an SFrame</h3> - -<div class="codehilite"> -<pre><span></span><code><span class="nt">!pip</span><span class="na"> install turicreate</span> -</code></pre> -</div> - -<p>\</p> - -<div class="codehilite"> -<pre><span></span><code><span class="kn">import</span> <span class="nn">turicreate</span> <span class="k">as</span> <span class="nn">tc</span> -<span class="kn">import</span> <span class="nn">os</span> - -<span class="n">data</span> <span class="o">=</span> <span class="n">tc</span><span class="o">.</span><span class="n">image_analysis</span><span class="o">.</span><span class="n">load_images</span><span class="p">(</span><span class="s2">"./train"</span><span class="p">,</span> <span class="n">with_path</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> - -<span class="n">data</span><span class="p">[</span><span class="s2">"label"</span><span class="p">]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="s2">"path"</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">path</span><span class="p">:</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">basename</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">dirname</span><span class="p">(</span><span class="n">path</span><span class="p">)))</span> - -<span class="nb">print</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> - -<span class="n">data</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="s1">'fire-smoke.sframe'</span><span class="p">)</span> -</code></pre> -</div> - -<p>\</p> - -<div class="codehilite"> -<pre><span></span><code><span class="nt">+-------------------------+------------------------+</span> -<span class="err">|</span><span class="w"> </span><span class="err">path</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">image</span><span class="w"> </span><span class="err">|</span> -<span class="nt">+-------------------------+------------------------+</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/1.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/10.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/100.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/101.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/102.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/103.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/104.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/105.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/106.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/107.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span> -<span class="nt">+-------------------------+------------------------+</span> -<span class="nt">[2028</span><span class="na"> rows x 2 columns]</span> -<span class="na">Note</span><span class="p">:</span><span class="err"> </span><span class="nc">Only</span><span class="err"> </span><span class="nc">the</span><span class="err"> </span><span class="nc">head</span><span class="err"> </span><span class="nc">of</span><span class="err"> </span><span class="nc">the</span><span class="err"> </span><span class="nc">SFrame</span><span class="err"> </span><span class="nc">is</span><span class="err"> </span><span class="nc">printed.</span> -<span class="nt">You</span><span class="na"> can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.</span> -<span class="na">+-------------------------+------------------------+---------+</span> -<span class="p">|</span><span class="na"> path </span><span class="p">|</span><span class="na"> image </span><span class="p">|</span><span class="na"> label </span><span class="p">|</span> -<span class="nt">+-------------------------+------------------------+---------+</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/1.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">default</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/10.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">default</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/100.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">default</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/101.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">default</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/102.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">default</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/103.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">default</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/104.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">default</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/105.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">default</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/106.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">default</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">./train/default/107.jpg</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">Height:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">Width:</span><span class="w"> </span><span class="err">224</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">default</span><span class="w"> </span><span class="err">|</span> -<span class="nt">+-------------------------+------------------------+---------+</span> -<span class="nt">[2028</span><span class="na"> rows x 3 columns]</span> -<span class="na">Note</span><span class="p">:</span><span class="err"> </span><span class="nc">Only</span><span class="err"> </span><span class="nc">the</span><span class="err"> </span><span class="nc">head</span><span class="err"> </span><span class="nc">of</span><span class="err"> </span><span class="nc">the</span><span class="err"> </span><span class="nc">SFrame</span><span class="err"> </span><span class="nc">is</span><span class="err"> </span><span class="nc">printed.</span> -<span class="nt">You</span><span class="na"> can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.</span> -</code></pre> -</div> - -<h3 id="making-the-model">Making the Model</h3> - -<div class="codehilite"> -<pre><span></span><code><span class="kn">import</span> <span class="nn">turicreate</span> <span class="k">as</span> <span class="nn">tc</span> - -<span class="c1"># Load the data</span> -<span class="n">data</span> <span class="o">=</span> <span class="n">tc</span><span class="o">.</span><span class="n">SFrame</span><span class="p">(</span><span class="s1">'fire-smoke.sframe'</span><span class="p">)</span> - -<span class="c1"># Make a train-test split</span> -<span class="n">train_data</span><span class="p">,</span> <span class="n">test_data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">random_split</span><span class="p">(</span><span class="mf">0.8</span><span class="p">)</span> - -<span class="c1"># Create the model</span> -<span class="n">model</span> <span class="o">=</span> <span class="n">tc</span><span class="o">.</span><span class="n">image_classifier</span><span class="o">.</span><span class="n">create</span><span class="p">(</span><span class="n">train_data</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="s1">'label'</span><span class="p">)</span> - -<span class="c1"># Save predictions to an SArray</span> -<span class="n">predictions</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test_data</span><span class="p">)</span> - -<span class="c1"># Evaluate the model and print the results</span> -<span class="n">metrics</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">test_data</span><span class="p">)</span> -<span class="nb">print</span><span class="p">(</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'accuracy'</span><span class="p">])</span> - -<span class="c1"># Save the model for later use in Turi Create</span> -<span class="n">model</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="s1">'fire-smoke.model'</span><span class="p">)</span> - -<span class="c1"># Export for use in Core ML</span> -<span class="n">model</span><span class="o">.</span><span class="n">export_coreml</span><span class="p">(</span><span class="s1">'fire-smoke.mlmodel'</span><span class="p">)</span> -</code></pre> -</div> - -<p>\</p> - -<div class="codehilite"> -<pre><span></span><code><span class="nt">Performing</span><span class="na"> feature extraction on resized images...</span> -<span class="na">Completed 64/1633</span> -<span class="na">Completed 128/1633</span> -<span class="na">Completed 192/1633</span> -<span class="na">Completed 256/1633</span> -<span class="na">Completed 320/1633</span> -<span class="na">Completed 384/1633</span> -<span class="na">Completed 448/1633</span> -<span class="na">Completed 512/1633</span> -<span class="na">Completed 576/1633</span> -<span class="na">Completed 640/1633</span> -<span class="na">Completed 704/1633</span> -<span class="na">Completed 768/1633</span> -<span class="na">Completed 832/1633</span> -<span class="na">Completed 896/1633</span> -<span class="na">Completed 960/1633</span> -<span class="na">Completed 1024/1633</span> -<span class="na">Completed 1088/1633</span> -<span class="na">Completed 1152/1633</span> -<span class="na">Completed 1216/1633</span> -<span class="na">Completed 1280/1633</span> -<span class="na">Completed 1344/1633</span> -<span class="na">Completed 1408/1633</span> -<span class="na">Completed 1472/1633</span> -<span class="na">Completed 1536/1633</span> -<span class="na">Completed 1600/1633</span> -<span class="na">Completed 1633/1633</span> -<span class="na">PROGRESS</span><span class="p">:</span><span class="err"> </span><span class="nc">Creating</span><span class="err"> </span><span class="nc">a</span><span class="err"> </span><span class="nc">validation</span><span class="err"> </span><span class="nc">set</span><span class="err"> </span><span class="nc">from</span><span class="err"> </span><span class="nc">5</span><span class="err"> </span><span class="nc">percent</span><span class="err"> </span><span class="nc">of</span><span class="err"> </span><span class="nc">training</span><span class="err"> </span><span class="nc">data.</span><span class="err"> </span><span class="nc">This</span><span class="err"> </span><span class="nc">may</span><span class="err"> </span><span class="nc">take</span><span class="err"> </span><span class="nc">a</span><span class="err"> </span><span class="nc">while.</span> -<span class="w"> </span><span class="err">You</span><span class="w"> </span><span class="err">can</span><span class="w"> </span><span class="err">set</span><span class="w"> </span><span class="err">``validation_set=None``</span><span class="w"> </span><span class="err">to</span><span class="w"> </span><span class="err">disable</span><span class="w"> </span><span class="err">validation</span><span class="w"> </span><span class="err">tracking.</span> - -<span class="nt">Logistic</span><span class="na"> regression</span><span class="p">:</span> -<span class="nt">--------------------------------------------------------</span> -<span class="nt">Number</span><span class="na"> of examples </span><span class="p">:</span><span class="err"> </span><span class="nc">1551</span> -<span class="nt">Number</span><span class="na"> of classes </span><span class="p">:</span><span class="err"> </span><span class="nc">3</span> -<span class="nt">Number</span><span class="na"> of feature columns </span><span class="p">:</span><span class="err"> </span><span class="nc">1</span> -<span class="nt">Number</span><span class="na"> of unpacked features </span><span class="p">:</span><span class="err"> </span><span class="nc">2048</span> -<span class="nt">Number</span><span class="na"> of coefficients </span><span class="p">:</span><span class="err"> </span><span class="nc">4098</span> -<span class="nt">Starting</span><span class="na"> L-BFGS</span> -<span class="na">--------------------------------------------------------</span> -<span class="na">+-----------+----------+-----------+--------------+-------------------+---------------------+</span> -<span class="p">|</span><span class="na"> Iteration </span><span class="p">|</span><span class="na"> Passes </span><span class="p">|</span><span class="na"> Step size </span><span class="p">|</span><span class="na"> Elapsed Time </span><span class="p">|</span><span class="na"> Training Accuracy </span><span class="p">|</span><span class="na"> Validation Accuracy </span><span class="p">|</span> -<span class="nt">+-----------+----------+-----------+--------------+-------------------+---------------------+</span> -<span class="err">|</span><span class="w"> </span><span class="err">0</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">6</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.018611</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.891830</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.553836</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.560976</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">1</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">10</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.390832</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">1.622383</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.744681</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.792683</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">2</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">11</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.488541</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">1.943987</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.733075</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.804878</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">3</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">14</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">2.442703</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">2.512545</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.727917</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.841463</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">4</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">15</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">2.442703</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">2.826964</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.861380</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.853659</span><span class="w"> </span><span class="err">|</span> -<span class="err">|</span><span class="w"> </span><span class="err">9</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">28</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">2.340435</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">5.492035</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.941328</span><span class="w"> </span><span class="err">|</span><span class="w"> </span><span class="err">0.975610</span><span class="w"> </span><span class="err">|</span> -<span class="nt">+-----------+----------+-----------+--------------+-------------------+---------------------+</span> -<span class="nt">Performing</span><span class="na"> feature extraction on resized images...</span> -<span class="na">Completed 64/395</span> -<span class="na">Completed 128/395</span> -<span class="na">Completed 192/395</span> -<span class="na">Completed 256/395</span> -<span class="na">Completed 320/395</span> -<span class="na">Completed 384/395</span> -<span class="na">Completed 395/395</span> -<span class="na">0.9316455696202531</span> -</code></pre> -</div> - -<p>We just got an accuracy of 94% on Training Data and 97% on Validation Data!</p> - - </div> - <blockquote>If you have scrolled this far, consider subscribing to my mailing list <a href="https://listmonk.navan.dev/subscription/form">here.</a> You can subscribe to either a specific type of post you are interested in, or subscribe to everything with the "Everything" list.</blockquote> - <script data-isso="https://comments.navan.dev/" - src="https://comments.navan.dev/js/embed.min.js"></script> - <div id="isso-thread"> - <noscript>Javascript needs to be activated to view comments.</noscript> - </div> - - </div> - <script src="assets/manup.min.js"></script> - <script src="/pwabuilder-sw-register.js"></script> -</body> -</html>
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