Package org.opencv.features2d

Class AKAZE

java.lang.Object
org.opencv.core.Algorithm
org.opencv.features2d.Feature2D
org.opencv.features2d.AKAZE
public class AKAZE extends Feature2D
Class implementing the AKAZE keypoint detector and descriptor extractor, described in CITE: ANB13. AKAZE descriptors can only be used with KAZE or AKAZE keypoints. This class is thread-safe. Note: When you need descriptors use Feature2D::detectAndCompute, which provides better performance. When using Feature2D::detect followed by Feature2D::compute scale space pyramid is computed twice. Note: AKAZE implements T-API. When image is passed as UMat some parts of the algorithm will use OpenCL. Note: [ANB13] Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces. Pablo F. Alcantarilla, Jesús Nuevo and Adrien Bartoli. In British Machine Vision Conference (BMVC), Bristol, UK, September 2013.

  • Field Details

  • Method Details

    • __fromPtr__

      public static AKAZE __fromPtr__(long addr)

    • create

      public static AKAZE create(int descriptor_type, int descriptor_size, int descriptor_channels, float threshold, int nOctaves, int nOctaveLayers, int diffusivity, int max_points)
      The AKAZE constructor
      Parameters:
      descriptor_type - Type of the extracted descriptor: DESCRIPTOR_KAZE, DESCRIPTOR_KAZE_UPRIGHT, DESCRIPTOR_MLDB or DESCRIPTOR_MLDB_UPRIGHT.
      descriptor_size - Size of the descriptor in bits. 0 -> Full size
      descriptor_channels - Number of channels in the descriptor (1, 2, 3)
      threshold - Detector response threshold to accept point
      nOctaves - Maximum octave evolution of the image
      nOctaveLayers - Default number of sublevels per scale level
      diffusivity - Diffusivity type. DIFF_PM_G1, DIFF_PM_G2, DIFF_WEICKERT or DIFF_CHARBONNIER
      max_points - Maximum amount of returned points. In case if image contains more features, then the features with highest response are returned. Negative value means no limitation.
      Returns:
      automatically generated

    • create

      public static AKAZE create(int descriptor_type, int descriptor_size, int descriptor_channels, float threshold, int nOctaves, int nOctaveLayers, int diffusivity)
      The AKAZE constructor
      Parameters:
      descriptor_type - Type of the extracted descriptor: DESCRIPTOR_KAZE, DESCRIPTOR_KAZE_UPRIGHT, DESCRIPTOR_MLDB or DESCRIPTOR_MLDB_UPRIGHT.
      descriptor_size - Size of the descriptor in bits. 0 -> Full size
      descriptor_channels - Number of channels in the descriptor (1, 2, 3)
      threshold - Detector response threshold to accept point
      nOctaves - Maximum octave evolution of the image
      nOctaveLayers - Default number of sublevels per scale level
      diffusivity - Diffusivity type. DIFF_PM_G1, DIFF_PM_G2, DIFF_WEICKERT or DIFF_CHARBONNIER more features, then the features with highest response are returned. Negative value means no limitation.
      Returns:
      automatically generated

    • create

      public static AKAZE create(int descriptor_type, int descriptor_size, int descriptor_channels, float threshold, int nOctaves, int nOctaveLayers)
      The AKAZE constructor
      Parameters:
      descriptor_type - Type of the extracted descriptor: DESCRIPTOR_KAZE, DESCRIPTOR_KAZE_UPRIGHT, DESCRIPTOR_MLDB or DESCRIPTOR_MLDB_UPRIGHT.
      descriptor_size - Size of the descriptor in bits. 0 -> Full size
      descriptor_channels - Number of channels in the descriptor (1, 2, 3)
      threshold - Detector response threshold to accept point
      nOctaves - Maximum octave evolution of the image
      nOctaveLayers - Default number of sublevels per scale level DIFF_CHARBONNIER more features, then the features with highest response are returned. Negative value means no limitation.
      Returns:
      automatically generated

    • create

      public static AKAZE create(int descriptor_type, int descriptor_size, int descriptor_channels, float threshold, int nOctaves)
      The AKAZE constructor
      Parameters:
      descriptor_type - Type of the extracted descriptor: DESCRIPTOR_KAZE, DESCRIPTOR_KAZE_UPRIGHT, DESCRIPTOR_MLDB or DESCRIPTOR_MLDB_UPRIGHT.
      descriptor_size - Size of the descriptor in bits. 0 -> Full size
      descriptor_channels - Number of channels in the descriptor (1, 2, 3)
      threshold - Detector response threshold to accept point
      nOctaves - Maximum octave evolution of the image DIFF_CHARBONNIER more features, then the features with highest response are returned. Negative value means no limitation.
      Returns:
      automatically generated

    • create

      public static AKAZE create(int descriptor_type, int descriptor_size, int descriptor_channels, float threshold)
      The AKAZE constructor
      Parameters:
      descriptor_type - Type of the extracted descriptor: DESCRIPTOR_KAZE, DESCRIPTOR_KAZE_UPRIGHT, DESCRIPTOR_MLDB or DESCRIPTOR_MLDB_UPRIGHT.
      descriptor_size - Size of the descriptor in bits. 0 -> Full size
      descriptor_channels - Number of channels in the descriptor (1, 2, 3)
      threshold - Detector response threshold to accept point DIFF_CHARBONNIER more features, then the features with highest response are returned. Negative value means no limitation.
      Returns:
      automatically generated

    • create

      public static AKAZE create(int descriptor_type, int descriptor_size, int descriptor_channels)
      The AKAZE constructor
      Parameters:
      descriptor_type - Type of the extracted descriptor: DESCRIPTOR_KAZE, DESCRIPTOR_KAZE_UPRIGHT, DESCRIPTOR_MLDB or DESCRIPTOR_MLDB_UPRIGHT.
      descriptor_size - Size of the descriptor in bits. 0 -> Full size
      descriptor_channels - Number of channels in the descriptor (1, 2, 3) DIFF_CHARBONNIER more features, then the features with highest response are returned. Negative value means no limitation.
      Returns:
      automatically generated

    • create

      public static AKAZE create(int descriptor_type, int descriptor_size)
      The AKAZE constructor
      Parameters:
      descriptor_type - Type of the extracted descriptor: DESCRIPTOR_KAZE, DESCRIPTOR_KAZE_UPRIGHT, DESCRIPTOR_MLDB or DESCRIPTOR_MLDB_UPRIGHT.
      descriptor_size - Size of the descriptor in bits. 0 -> Full size DIFF_CHARBONNIER more features, then the features with highest response are returned. Negative value means no limitation.
      Returns:
      automatically generated

    • create

      public static AKAZE create(int descriptor_type)
      The AKAZE constructor
      Parameters:
      descriptor_type - Type of the extracted descriptor: DESCRIPTOR_KAZE, DESCRIPTOR_KAZE_UPRIGHT, DESCRIPTOR_MLDB or DESCRIPTOR_MLDB_UPRIGHT. DIFF_CHARBONNIER more features, then the features with highest response are returned. Negative value means no limitation.
      Returns:
      automatically generated

    • create

      public static AKAZE create()
      The AKAZE constructor DESCRIPTOR_KAZE_UPRIGHT, DESCRIPTOR_MLDB or DESCRIPTOR_MLDB_UPRIGHT. DIFF_CHARBONNIER more features, then the features with highest response are returned. Negative value means no limitation.
      Returns:
      automatically generated

    • setDescriptorType

      public void setDescriptorType(int dtype)

    • getDescriptorType

      public int getDescriptorType()

    • setDescriptorSize

      public void setDescriptorSize(int dsize)

    • getDescriptorSize

      public int getDescriptorSize()

    • setDescriptorChannels

      public void setDescriptorChannels(int dch)

    • getDescriptorChannels

      public int getDescriptorChannels()

    • setThreshold

      public void setThreshold(double threshold)

    • getThreshold

      public double getThreshold()

    • setNOctaves

      public void setNOctaves(int octaves)

    • getNOctaves

      public int getNOctaves()

    • setNOctaveLayers

      public void setNOctaveLayers(int octaveLayers)

    • getNOctaveLayers

      public int getNOctaveLayers()

    • setDiffusivity

      public void setDiffusivity(int diff)

    • getDiffusivity

      public int getDiffusivity()

    • getDefaultName

      public String getDefaultName()
      Description copied from class: Algorithm
      Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.
      Overrides:
      getDefaultName in class Feature2D
      Returns:
      automatically generated

    • setMaxPoints

      public void setMaxPoints(int max_points)

    • getMaxPoints

      public int getMaxPoints()