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TM&B Edits #11

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TM&B Edits #11

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4 changes: 2 additions & 2 deletions app/views/labs/analytics-opencvface/index.html
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Expand Up @@ -46,7 +46,7 @@ <h5>Lab Overview</h5>
<h5>The first step is load the Haar-like features classifer cascade file, which is a file create through machine learning to contain the esstential features of a face. In OpenCV, you can detect different types of objects by changing the classifier file.</h5>

<p>Download the haar cascade file, named <a href="../views/labs/analytics-opencvface/downloads/haarcascade_frontalface_default.xml">haarcascade_frontalface_default.xml</a>face, and save it into the same directory as your python script.</p>
<p>Create a new Python file named <b>face_detect.py</b></p>
<p>Create a new Python\* file named <b>face_detect.py</b></p>
<p>Paste the following line</p>
<ui-codemirror ui-codemirror-opts="editorOptions"><pre class="brush:jscript;">import cv2</pre></ui-codemirror>
</div>
Expand All @@ -56,7 +56,7 @@ <h5>The first step is load the Haar-like features classifer cascade file, which
<ui-codemirror ui-codemirror-opts="editorOptions"><pre class="brush:jscript;"># Create a Haar-like feature cascade classifier object
faceCascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")

# Set the camera to the first camera detected by the NUC
# Set the camera to the first camera detected by the Intel® NUC
cap = cv2.VideoCapture(0)</pre></ui-codemirror>
</div>

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