April 2020
Intermediate to advanced
438 pages
12h 2m
English
Content preview from Python Image Processing Cookbook
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How it works...
The get_frontal_face_detector() function (histogram of oriented gradients (HOG) feature-based) from the dlib library was used to detect the faces. The shape_predictor() function from dlib was invoked with the serialized pre-trained facial landmark detector (the data file) to estimate the (x, y) coordinates of sixty-eight key points that map to facial landmarks (structures) from a given detected face (the dlib shape predictor internally implements Kazemi and Sullivan's algorithm, which uses an ensemble of regression trees to estimate the facial landmarks directly from input face pixels without any feature extraction). The landmarks extracted from a face look like as shown in the following screenshot:
An object of the FaceAligner ...
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