docs: Newly exported html after update to .ipynb file

Author: informramiz

OpenCV-Face-Recognition-Python.html

@@ -11952,7 +11952,7 @@ <h3 id="Code-Dependencies">Code Dependencies<a class="anchor-link" href="#Code-D
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 <li><a href="http://opencv.org/releases.html">OpenCV 3.2.0</a>.</li>
 <li><a href="https://www.python.org/downloads/">Python v3.5</a>.</li>
-<li><a href="http://www.numpy.org/">NumPy</a></li>
+<li><a href="http://www.numpy.org/">NumPy</a> Numpy makes computing in Python easy. Amont other things it contains a powerful implementation of N-dimensional arrays which we will use for feeding data as input to OpenCV functions.</li>
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@@ -12093,7 +12093,6 @@ <h3 id="Prepare-training-data">Prepare training data<a class="anchor-link" href=
 <li>Read all the images of the subject, detect face from each image.</li>
 <li>Add each face to faces vector with corresponding subject label (extracted in above step) added to labels vector. </li>
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-<p><strong>[There should be a visualization for above steps here]</strong></p>
 
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@@ -16563,11 +16562,24 @@ <h2 id="End-Notes">End Notes<a class="anchor-link" href="#End-Notes">&#182;</a><
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 <p>You can download the complete code and relevant files from this Github <a href="https://github.com/informramiz/opencv-face-recognition-python">repo</a>.</p>
-<p>Face Recognition is a fascinating idea to work on and OpenCV has made it extremely simple and easy for us to code it. It just takes a few lines of code to have a fully working face recognition application and we can switch between all three face recognizers with a single line of code change. It's that simple.</p>
+<p>Face Recognition is a fascinating idea to work on and OpenCV has made it extremely simple and easy for us to code it. It takes just a few lines of code to have a fully working face recognition application and we can switch between all three face recognizers with a single line of code change. It's that simple.</p>
 <p>Although EigenFaces, FisherFaces and LBPH face recognizers are good but there are even better ways to perform face recognition like using Histogram of Oriented Gradients (HOGs) and Neural Networks. So the more advanced face recognition algorithms are now a days implemented using a combination of OpenCV and Machine learning. I have plans to write some articles on those more advanced methods as well, so stay tuned!</p>
 
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