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

apply

Positional Arguments

• self: Evision.RgbdNormals.t()

• points: Evision.Mat.

  a rows x cols x 3 matrix of CV_32F/CV64F or a rows x cols x 1 CV_U16S

Return

• normals: Evision.Mat.t().

  a rows x cols x 3 matrix

Given a set of 3d points in a depth image, compute the normals at each point.

Python prototype (for reference only):

apply(points[, normals]) -> normals

@spec apply(t(), Evision.Mat.maybe_mat_in(), [{atom(), term()}, ...] | nil) ::
  Evision.Mat.t() | {:error, String.t()}

apply

Positional Arguments

• self: Evision.RgbdNormals.t()

• points: Evision.Mat.

  a rows x cols x 3 matrix of CV_32F/CV64F or a rows x cols x 1 CV_U16S

Return

• normals: Evision.Mat.t().

  a rows x cols x 3 matrix

Given a set of 3d points in a depth image, compute the normals at each point.

Python prototype (for reference only):

apply(points[, normals]) -> normals

@spec cache(Keyword.t()) :: any() | {:error, String.t()}

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

cache

Positional Arguments

• self: Evision.RgbdNormals.t()

Prepares cached data required for calculation If not called by user, called automatically at first calculation

Python prototype (for reference only):

cache() -> None

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

create

Keyword Arguments

• rows: integer().

  the number of rows of the depth image normals will be computed on

• cols: integer().

  the number of cols of the depth image normals will be computed on

• depth: integer().

  the depth of the normals (only CV_32F or CV_64F)

• k: Evision.Mat.

  the calibration matrix to use

• window_size: integer().

  the window size to compute the normals: can only be 1,3,5 or 7

• diff_threshold: float.

  threshold in depth difference, used in LINEMOD algirithm

• method: RgbdNormals_RgbdNormalsMethod.

  one of the methods to use: RGBD_NORMALS_METHOD_SRI, RGBD_NORMALS_METHOD_FALS

Return

• retval: Evision.RgbdNormals.t()

Creates new RgbdNormals object

Python prototype (for reference only):

create([, rows[, cols[, depth[, K[, window_size[, diff_threshold[, method]]]]]]]) -> retval

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

@spec create(
  [
    cols: term(),
    depth: term(),
    diff_threshold: term(),
    k: term(),
    method: term(),
    rows: term(),
    window_size: term()
  ]
  | nil
) :: t() | {:error, String.t()}

create

Keyword Arguments

• rows: integer().

  the number of rows of the depth image normals will be computed on

• cols: integer().

  the number of cols of the depth image normals will be computed on

• depth: integer().

  the depth of the normals (only CV_32F or CV_64F)

• k: Evision.Mat.

  the calibration matrix to use

• window_size: integer().

  the window size to compute the normals: can only be 1,3,5 or 7

• diff_threshold: float.

  threshold in depth difference, used in LINEMOD algirithm

• method: RgbdNormals_RgbdNormalsMethod.

  one of the methods to use: RGBD_NORMALS_METHOD_SRI, RGBD_NORMALS_METHOD_FALS

Return

• retval: Evision.RgbdNormals.t()

Creates new RgbdNormals object

Python prototype (for reference only):

create([, rows[, cols[, depth[, K[, window_size[, diff_threshold[, method]]]]]]]) -> retval

@spec getCols(Keyword.t()) :: any() | {:error, String.t()}

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

getCols

Positional Arguments

• self: Evision.RgbdNormals.t()

Return

• retval: integer()

Python prototype (for reference only):

getCols() -> retval

@spec getDepth(Keyword.t()) :: any() | {:error, String.t()}

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

getDepth

Positional Arguments

• self: Evision.RgbdNormals.t()

Return

• retval: integer()

Python prototype (for reference only):

getDepth() -> retval

@spec getK(Keyword.t()) :: any() | {:error, String.t()}

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

getK

Positional Arguments

• self: Evision.RgbdNormals.t()

Return

• val: Evision.Mat.t().

Python prototype (for reference only):

getK([, val]) -> val

@spec getK(t(), [{atom(), term()}, ...] | nil) ::
  Evision.Mat.t() | {:error, String.t()}

getK

Positional Arguments

• self: Evision.RgbdNormals.t()

Return

• val: Evision.Mat.t().

Python prototype (for reference only):

getK([, val]) -> val

@spec getMethod(Keyword.t()) :: any() | {:error, String.t()}

@spec getMethod(t()) :: term() | {:error, String.t()}

getMethod

Positional Arguments

• self: Evision.RgbdNormals.t()

Return

• retval: RgbdNormals::RgbdNormalsMethod

Python prototype (for reference only):

getMethod() -> retval

@spec getRows(Keyword.t()) :: any() | {:error, String.t()}

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

getRows

Positional Arguments

• self: Evision.RgbdNormals.t()

Return

• retval: integer()

Python prototype (for reference only):

getRows() -> retval

@spec getWindowSize(Keyword.t()) :: any() | {:error, String.t()}

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

getWindowSize

Positional Arguments

• self: Evision.RgbdNormals.t()

Return

• retval: integer()

Python prototype (for reference only):

getWindowSize() -> retval

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

setCols

Positional Arguments

• self: Evision.RgbdNormals.t()
• val: integer()

Python prototype (for reference only):

setCols(val) -> None

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

setK

Positional Arguments

• self: Evision.RgbdNormals.t()
• val: Evision.Mat

Python prototype (for reference only):

setK(val) -> None

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

setRows

Positional Arguments

• self: Evision.RgbdNormals.t()
• val: integer()

Python prototype (for reference only):

setRows(val) -> None

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

setWindowSize

Positional Arguments

• self: Evision.RgbdNormals.t()
• val: integer()

Python prototype (for reference only):

setWindowSize(val) -> None