OpenCvSharp.Face Namespace

base for two FaceRecognizer classes

Training and prediction must be done on grayscale images, use cvtColor to convert between the color spaces. - **THE EIGENFACES METHOD MAKES THE ASSUMPTION, THAT THE TRAINING AND TEST IMAGES ARE OF EQUAL SIZE. ** (caps-lock, because I got so many mails asking for this). You have to make sure your input data has the correct shape, else a meaningful exception is thrown.Use resize to resize the images. - This model does not support updating.

Abstract base class for all facemark models. All facemark models in OpenCV are derived from the abstract base class Facemark, which provides a unified access to all facemark algorithms in OpenCV. To utilize this API in your program, please take a look at the @ref tutorial_table_of_content_facemark

Abstract base class for all face recognition models. All face recognition models in OpenCV are derived from the abstract base class FaceRecognizer, which provides a unified access to all face recongition algorithms in OpenCV.

Training and prediction must be done on grayscale images, use cvtColor to convert between the color spaces. - **THE FISHERFACES METHOD MAKES THE ASSUMPTION, THAT THE TRAINING AND TEST IMAGES ARE OF EQUAL SIZE. ** (caps-lock, because I got so many mails asking for this). You have to make sure your input data has the correct shape, else a meaningful exception is thrown.Use resize to resize the images. - This model does not support updating.

The Circular Local Binary Patterns (used in training and prediction) expect the data given as grayscale images, use cvtColor to convert between the color spaces. This model supports updating.