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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 index 4235b29..5056a82 100644 --- a/docs/posts/2020-01-16-Image-Classifier-Using-Turicreate.html +++ b/docs/posts/2020-01-16-Image-Classifier-Using-Turicreate.html @@ -49,31 +49,40 @@ <h3>Mounting Google Drive</h3> -<div class="codehilite"><pre><span></span><code><span class="kn">import</span> <span class="nn">os</span> +<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> +</code></pre> +</div> <h3>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> +<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> +</code></pre> +</div> <h2>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> +<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> +<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> +<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> @@ -106,11 +115,13 @@ <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> +</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> +<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> @@ -127,26 +138,32 @@ <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> +</code></pre> +</div> <p>\</p> -<div class="codehilite"><pre><span></span><code><span class="nt">!mkdir</span><span class="na"> train</span> +<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> +</code></pre> +</div> <h2>Making the Image Classifier</h2> <h3>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> +<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> +<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> @@ -156,11 +173,13 @@ <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> +</code></pre> +</div> <p>\</p> -<div class="codehilite"><pre><span></span><code><span class="nt">+-------------------------+------------------------+</span><span class="w"></span> +<div class="codehilite"> +<pre><span></span><code><span class="nt">+-------------------------+------------------------+</span><span class="w"></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="w"></span> <span class="nt">+-------------------------+------------------------+</span><span class="w"></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> @@ -194,11 +213,13 @@ <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="w"></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> +</code></pre> +</div> <h3>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> +<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> @@ -221,11 +242,13 @@ <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> +</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> +<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> @@ -283,7 +306,8 @@ <span class="na">Completed 384/395</span> <span class="na">Completed 395/395</span> <span class="na">0.9316455696202531</span> -</code></pre></div> +</code></pre> +</div> <p>We just got an accuracy of 94% on Training Data and 97% on Validation Data!</p> |