@spec create({number(), number()}) :: t() | {:error, String.t()}

create

Positional Arguments

• monoImgSize: Size

Keyword Arguments

• paramFilepath: String.

Return

• retval: cv::Ptr<QuasiDenseStereo>

Python prototype (for reference only):

create(monoImgSize[, paramFilepath]) -> retval

@spec create(
  {number(), number()},
  [{atom(), term()}, ...] | nil
) :: t() | {:error, String.t()}

create

Positional Arguments

• monoImgSize: Size

Keyword Arguments

• paramFilepath: String.

Return

• retval: cv::Ptr<QuasiDenseStereo>

Python prototype (for reference only):

create(monoImgSize[, paramFilepath]) -> retval

@spec getDenseMatches(t()) ::
  [Evision.Stereo.MatchQuasiDense.t()] | {:error, String.t()}

Get The dense corresponding points.

Positional Arguments

• self: Evision.Stereo.QuasiDenseStereo.t()

Return

• denseMatches: [MatchQuasiDense].

  A vector containing all dense matches.

Note: The method clears the denseMatches vector. Note: The returned Match elements inside the sMatches vector, do not use corr member.

Python prototype (for reference only):

getDenseMatches() -> denseMatches

@spec getDisparity(t()) :: Evision.Mat.t() | {:error, String.t()}

Compute and return the disparity map based on the correspondences found in the "process" method.

Positional Arguments

• self: Evision.Stereo.QuasiDenseStereo.t()

Return

• retval: Evision.Mat.t()

Note: Default level is 50 @return cv::Mat containing a the disparity image in grayscale. @sa computeDisparity @sa quantizeDisparity

Python prototype (for reference only):

getDisparity() -> retval

@spec getMatch(t(), integer(), integer()) ::
  {number(), number()} | {:error, String.t()}

Specify pixel coordinates in the left image and get its corresponding location in the right image.

Positional Arguments

• self: Evision.Stereo.QuasiDenseStereo.t()

• x: int.

  The x pixel coordinate in the left image channel.

• y: int.

  The y pixel coordinate in the left image channel.

Return

• retval: cv::Point2f

@retval cv::Point(x, y) The location of the corresponding pixel in the right image. @retval cv::Point(0, 0) (NO_MATCH) if no match is found in the right image for the specified pixel location in the left image. Note: This method should be always called after process, otherwise the matches will not be correct.

Python prototype (for reference only):

getMatch(x, y) -> retval

@spec getSparseMatches(t()) ::
  [Evision.Stereo.MatchQuasiDense.t()] | {:error, String.t()}

Get The sparse corresponding points.

Positional Arguments

• self: Evision.Stereo.QuasiDenseStereo.t()

Return

• sMatches: [MatchQuasiDense].

  A vector containing all sparse correspondences.

Note: The method clears the sMatches vector. Note: The returned Match elements inside the sMatches vector, do not use corr member.

Python prototype (for reference only):

getSparseMatches() -> sMatches

@spec loadParameters(t(), binary()) :: integer() | {:error, String.t()}

Load a file containing the configuration parameters of the class.

Positional Arguments

• self: Evision.Stereo.QuasiDenseStereo.t()

• filepath: String.

  The location of the .YAML file containing the configuration parameters.

Return

• retval: int

Note: default value is an empty string in which case the default parameters will be loaded. @retval 1: If the path is not empty and the program loaded the parameters successfully. @retval 0: If the path is empty and the program loaded default parameters. @retval -1: If the file location is not valid or the program could not open the file and loaded default parameters from defaults.hpp. Note: The method is automatically called in the constructor and configures the class. Note: Loading different parameters will have an effect on the output. This is useful for tuning in case of video processing. @sa loadParameters

Python prototype (for reference only):

loadParameters(filepath) -> retval

@spec process(t(), Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in()) ::
  t() | {:error, String.t()}

Main process of the algorithm. This method computes the sparse seeds and then densifies them.

Positional Arguments

• self: Evision.Stereo.QuasiDenseStereo.t()

• imgLeft: Evision.Mat.t().

  The left Channel of a stereo image pair.

• imgRight: Evision.Mat.t().

  The right Channel of a stereo image pair.

Initially input images are converted to gray-scale and then the sparseMatching method is called to obtain the sparse stereo. Finally quasiDenseMatching is called to densify the corresponding points. Note: If input images are in color, the method assumes that are BGR and converts them to grayscale. @sa sparseMatching @sa quasiDenseMatching

Python prototype (for reference only):

process(imgLeft, imgRight) -> None

@spec saveParameters(t(), binary()) :: integer() | {:error, String.t()}

Save a file containing all the configuration parameters the class is currently set to.

Positional Arguments

• self: Evision.Stereo.QuasiDenseStereo.t()

• filepath: String.

  The location to store the parameters file.

Return

• retval: int

Note: Calling this method with no arguments will result in storing class parameters to a file names "qds_parameters.yaml" in the root project folder. Note: This method can be used to generate a template file for tuning the class. @sa loadParameters

Python prototype (for reference only):

saveParameters(filepath) -> retval