Class FacemarkTrain

  • Direct Known Subclasses:
    FacemarkAAM, FacemarkLBF

    public class FacemarkTrain
    extends Facemark
    Abstract base class for trainable facemark models To utilize this API in your program, please take a look at the REF: tutorial_table_of_content_facemark ### Description The AAM and LBF facemark models in OpenCV are derived from the abstract base class FacemarkTrain, which provides a unified access to those facemark algorithms in OpenCV. Here is an example on how to declare facemark algorithm: // Using Facemark in your code: Ptr<Facemark> facemark = FacemarkLBF::create(); The typical pipeline for facemark detection is listed as follows:
    • (Non-mandatory) Set a user defined face detection using FacemarkTrain::setFaceDetector. The facemark algorithms are designed to fit the facial points into a face. Therefore, the face information should be provided to the facemark algorithm. Some algorithms might provides a default face recognition function. However, the users might prefer to use their own face detector to obtains the best possible detection result.
    • (Non-mandatory) Training the model for a specific algorithm using FacemarkTrain::training. In this case, the model should be automatically saved by the algorithm. If the user already have a trained model, then this part can be omitted.
    • Load the trained model using Facemark::loadModel.
    • Perform the fitting via the Facemark::fit.
    • Constructor Detail

      • FacemarkTrain

        protected FacemarkTrain​(long addr)
    • Method Detail

      • __fromPtr__

        public static FacemarkTrain __fromPtr__​(long addr)
      • finalize

        protected void finalize()
                         throws java.lang.Throwable
        finalize in class Facemark