add blog post

1 files changed, 28 insertions, 14 deletions

diff --git a/docs/posts/2019-12-10-TensorFlow-Model-Prediction.html b/docs/posts/2019-12-10-TensorFlow-Model-Prediction.html
index 7187fe8..97ad373 100644
--- a/docs/posts/2019-12-10-TensorFlow-Model-Prediction.html
+++ b/docs/posts/2019-12-10-TensorFlow-Model-Prediction.html
@@ -51,39 +51,53 @@
 
 <p>First we import the following if we have not imported these before</p>
 
-<div class="codehilite"><pre><span></span><code><span class="kn">import</span> <span class="nn">cv2</span>
+<div class="codehilite">
+<pre><span></span><code><span class="kn">import</span> <span class="nn">cv2</span>
 <span class="kn">import</span> <span class="nn">os</span>
-</code></pre></div>
+</code></pre>
+</div>
 
 <p>Then we read the file using OpenCV.</p>
 
-<div class="codehilite"><pre><span></span><code><span class="n">image</span><span class="o">=</span><span class="n">cv2</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="n">imagePath</span><span class="p">)</span>
-</code></pre></div>
+<div class="codehilite">
+<pre><span></span><code><span class="n">image</span><span class="o">=</span><span class="n">cv2</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="n">imagePath</span><span class="p">)</span>
+</code></pre>
+</div>
 
 <p>The cv2. imread() function returns a NumPy array representing the image. Therefore, we need to convert it before we can use it.</p>
 
-<div class="codehilite"><pre><span></span><code><span class="n">image_from_array</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">fromarray</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="s1">&#39;RGB&#39;</span><span class="p">)</span>
-</code></pre></div>
+<div class="codehilite">
+<pre><span></span><code><span class="n">image_from_array</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">fromarray</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="s1">&#39;RGB&#39;</span><span class="p">)</span>
+</code></pre>
+</div>
 
 <p>Then we resize the image</p>
 
-<div class="codehilite"><pre><span></span><code><span class="n">size_image</span> <span class="o">=</span> <span class="n">image_from_array</span><span class="o">.</span><span class="n">resize</span><span class="p">((</span><span class="mi">50</span><span class="p">,</span><span class="mi">50</span><span class="p">))</span>
-</code></pre></div>
+<div class="codehilite">
+<pre><span></span><code><span class="n">size_image</span> <span class="o">=</span> <span class="n">image_from_array</span><span class="o">.</span><span class="n">resize</span><span class="p">((</span><span class="mi">50</span><span class="p">,</span><span class="mi">50</span><span class="p">))</span>
+</code></pre>
+</div>
 
 <p>After this we create a batch consisting of only one image</p>
 
-<div class="codehilite"><pre><span></span><code><span class="n">p</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">expand_dims</span><span class="p">(</span><span class="n">size_image</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
-</code></pre></div>
+<div class="codehilite">
+<pre><span></span><code><span class="n">p</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">expand_dims</span><span class="p">(</span><span class="n">size_image</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
+</code></pre>
+</div>
 
 <p>We then convert this uint8 datatype to a float32 datatype</p>
 
-<div class="codehilite"><pre><span></span><code><span class="n">img</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
-</code></pre></div>
+<div class="codehilite">
+<pre><span></span><code><span class="n">img</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
+</code></pre>
+</div>
 
 <p>Finally we make the prediction</p>
 
-<div class="codehilite"><pre><span></span><code><span class="nb">print</span><span class="p">([</span><span class="s1">&#39;Infected&#39;</span><span class="p">,</span><span class="s1">&#39;Uninfected&#39;</span><span class="p">][</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">img</span><span class="p">))])</span>
-</code></pre></div>
+<div class="codehilite">
+<pre><span></span><code><span class="nb">print</span><span class="p">([</span><span class="s1">&#39;Infected&#39;</span><span class="p">,</span><span class="s1">&#39;Uninfected&#39;</span><span class="p">][</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">img</span><span class="p">))])</span>
+</code></pre>
+</div>
 
 <p><code>Infected</code></p>