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

Apply a transformation, given a pre-estimated transformation parameters.

Positional Arguments

• self: Evision.ShapeTransformer.t()

• input: Evision.Mat.t().

  Contour (set of points) to apply the transformation.

Return

• retval: float

• output: Evision.Mat.t().

  Output contour.

Python prototype (for reference only):

applyTransformation(input[, output]) -> retval, output

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

Apply a transformation, given a pre-estimated transformation parameters.

Positional Arguments

• self: Evision.ShapeTransformer.t()

• input: Evision.Mat.t().

  Contour (set of points) to apply the transformation.

Return

• retval: float

• output: Evision.Mat.t().

  Output contour.

Python prototype (for reference only):

applyTransformation(input[, output]) -> retval, output

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

Clears the algorithm state

Positional Arguments

• self: Evision.ShapeTransformer.t()

Python prototype (for reference only):

clear() -> None

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

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

Positional Arguments

• self: Evision.ShapeTransformer.t()

Return

• retval: bool

Python prototype (for reference only):

empty() -> retval

@spec estimateTransformation(
  t(),
  Evision.Mat.maybe_mat_in(),
  Evision.Mat.maybe_mat_in(),
  [
    Evision.DMatch.t()
  ]
) :: t() | {:error, String.t()}

Estimate the transformation parameters of the current transformer algorithm, based on point matches.

Positional Arguments

• self: Evision.ShapeTransformer.t()

• transformingShape: Evision.Mat.t().

  Contour defining first shape.

• targetShape: Evision.Mat.t().

  Contour defining second shape (Target).

• matches: [Evision.DMatch].

  Standard vector of Matches between points.

Python prototype (for reference only):

estimateTransformation(transformingShape, targetShape, matches) -> None

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

getDefaultName

Positional Arguments

• self: Evision.ShapeTransformer.t()

Return

• retval: String

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.

Python prototype (for reference only):

getDefaultName() -> retval

@spec read(t(), Evision.FileNode.t()) :: t() | {:error, String.t()}

Reads algorithm parameters from a file storage

Positional Arguments

• self: Evision.ShapeTransformer.t()
• fn_: Evision.FileNode.t()

Python prototype (for reference only):

read(fn_) -> None

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

save

Positional Arguments

• self: Evision.ShapeTransformer.t()
• filename: String

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

Python prototype (for reference only):

save(filename) -> None

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

Apply a transformation, given a pre-estimated transformation parameters, to an Image.

Positional Arguments

• self: Evision.ShapeTransformer.t()

• transformingImage: Evision.Mat.t().

  Input image.

Keyword Arguments

• flags: int.

  Image interpolation method.

• borderMode: int.

  border style.

• borderValue: Scalar.

  border value.

Return

• output: Evision.Mat.t().

  Output image.

Python prototype (for reference only):

warpImage(transformingImage[, output[, flags[, borderMode[, borderValue]]]]) -> output

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

Apply a transformation, given a pre-estimated transformation parameters, to an Image.

Positional Arguments

• self: Evision.ShapeTransformer.t()

• transformingImage: Evision.Mat.t().

  Input image.

Keyword Arguments

• flags: int.

  Image interpolation method.

• borderMode: int.

  border style.

• borderValue: Scalar.

  border value.

Return

• output: Evision.Mat.t().

  Output image.

Python prototype (for reference only):

warpImage(transformingImage[, output[, flags[, borderMode[, borderValue]]]]) -> output

@spec write(t(), Evision.FileStorage.t()) :: t() | {:error, String.t()}

Stores algorithm parameters in a file storage

Positional Arguments

• self: Evision.ShapeTransformer.t()
• fs: Evision.FileStorage.t()

Python prototype (for reference only):

write(fs) -> None

@spec write(t(), Evision.FileStorage.t(), binary()) :: t() | {:error, String.t()}

write

Positional Arguments

• self: Evision.ShapeTransformer.t()
• fs: Evision.FileStorage.t()
• name: String

Has overloading in C++

Python prototype (for reference only):

write(fs, name) -> None