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

Estimates focal lengths for each given camera.

Positional Arguments

• hs: [Evision.Mat]

Return

• retval: bool
• k: Evision.Mat.t().

Python prototype (for reference only):

calibrateRotatingCamera(Hs[, K]) -> retval, K

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

Estimates focal lengths for each given camera.

Positional Arguments

• hs: [Evision.Mat]

Return

• retval: bool
• k: Evision.Mat.t().

Python prototype (for reference only):

calibrateRotatingCamera(Hs[, K]) -> retval, K

@spec computeImageFeatures2(Evision.Feature2D.t(), Evision.Mat.maybe_mat_in()) ::
  Evision.Detail.ImageFeatures.t() | {:error, String.t()}

Positional Arguments

• featuresFinder: Evision.Feature2D.t().

• image: Evision.Mat.t().

Keyword Arguments

• mask: Evision.Mat.t().

Return

• features: Evision.Detail.ImageFeatures.t().

Python prototype (for reference only):

computeImageFeatures2(featuresFinder, image[, mask]) -> features

@spec computeImageFeatures2(
  Evision.Feature2D.t(),
  Evision.Mat.maybe_mat_in(),
  [{atom(), term()}, ...] | nil
) :: Evision.Detail.ImageFeatures.t() | {:error, String.t()}

Positional Arguments

• featuresFinder: Evision.Feature2D.t().

• image: Evision.Mat.t().

Keyword Arguments

• mask: Evision.Mat.t().

Return

• features: Evision.Detail.ImageFeatures.t().

Python prototype (for reference only):

computeImageFeatures2(featuresFinder, image[, mask]) -> features

@spec computeImageFeatures(Evision.Feature2D.t(), [Evision.Mat.maybe_mat_in()]) ::
  [Evision.Detail.ImageFeatures.t()] | {:error, String.t()}

Positional Arguments

• featuresFinder: Evision.Feature2D.t().

• images: [Evision.Mat].

Keyword Arguments

• masks: [Evision.Mat].

Return

• features: [Evision.Detail.ImageFeatures].

Python prototype (for reference only):

computeImageFeatures(featuresFinder, images[, masks]) -> features

@spec computeImageFeatures(
  Evision.Feature2D.t(),
  [Evision.Mat.maybe_mat_in()],
  [{atom(), term()}, ...] | nil
) :: [Evision.Detail.ImageFeatures.t()] | {:error, String.t()}

Positional Arguments

• featuresFinder: Evision.Feature2D.t().

• images: [Evision.Mat].

Keyword Arguments

• masks: [Evision.Mat].

Return

• features: [Evision.Detail.ImageFeatures].

Python prototype (for reference only):

computeImageFeatures(featuresFinder, images[, masks]) -> features

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

createLaplacePyr

Positional Arguments

• img: Evision.Mat.t()
• num_levels: int

Return

• pyr: [Evision.Mat]

Python prototype (for reference only):

createLaplacePyr(img, num_levels, pyr) -> pyr

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

createLaplacePyrGpu

Positional Arguments

• img: Evision.Mat.t()
• num_levels: int

Return

• pyr: [Evision.Mat]

Python prototype (for reference only):

createLaplacePyrGpu(img, num_levels, pyr) -> pyr

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

createWeightMap

Positional Arguments

• mask: Evision.Mat.t()
• sharpness: float

Return

• weight: Evision.Mat.t()

Python prototype (for reference only):

createWeightMap(mask, sharpness, weight) -> weight

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

Tries to estimate focal lengths from the given homography under the assumption that the camera undergoes rotations around its centre only.

Positional Arguments

• h: Evision.Mat.t().

  Homography.

• f0: double.

  Estimated focal length along X axis.

• f1: double.

  Estimated focal length along Y axis.

• f0_ok: bool.

  True, if f0 was estimated successfully, false otherwise.

• f1_ok: bool.

  True, if f1 was estimated successfully, false otherwise.

See "Construction of Panoramic Image Mosaics with Global and Local Alignment" by Heung-Yeung Shum and Richard Szeliski.

Python prototype (for reference only):

focalsFromHomography(H, f0, f1, f0_ok, f1_ok) -> None

@spec leaveBiggestComponent(
  [Evision.Detail.ImageFeatures.t()],
  [Evision.Detail.MatchesInfo.t()],
  number()
) :: [integer()] | {:error, String.t()}

leaveBiggestComponent

Positional Arguments

• features: [Evision.Detail.ImageFeatures]
• pairwise_matches: [Evision.Detail.MatchesInfo]
• conf_threshold: float

Return

• retval: [int]

Python prototype (for reference only):

leaveBiggestComponent(features, pairwise_matches, conf_threshold) -> retval

@spec matchesGraphAsString([binary()], [Evision.Detail.MatchesInfo.t()], number()) ::
  binary() | {:error, String.t()}

matchesGraphAsString

Positional Arguments

• paths: [String]
• pairwise_matches: [Evision.Detail.MatchesInfo]
• conf_threshold: float

Return

• retval: String

Python prototype (for reference only):

matchesGraphAsString(paths, pairwise_matches, conf_threshold) -> retval

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

normalizeUsingWeightMap

Positional Arguments

• weight: Evision.Mat.t()

Return

• src: Evision.Mat.t()

Python prototype (for reference only):

normalizeUsingWeightMap(weight, src) -> src

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

overlapRoi

Positional Arguments

• tl1: Point
• tl2: Point
• sz1: Size
• sz2: Size
• roi: Rect

Return

• retval: bool

Python prototype (for reference only):

overlapRoi(tl1, tl2, sz1, sz2, roi) -> retval

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

restoreImageFromLaplacePyr

Return

• pyr: [Evision.Mat]

Python prototype (for reference only):

restoreImageFromLaplacePyr(pyr) -> pyr

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

restoreImageFromLaplacePyrGpu

Return

• pyr: [Evision.Mat]

Python prototype (for reference only):

restoreImageFromLaplacePyrGpu(pyr) -> pyr

@spec resultRoi([{number(), number()}], [{number(), number()}]) ::
  {number(), number(), number(), number()} | {:error, String.t()}

resultRoi

Positional Arguments

• corners: [Point]
• sizes: [Size]

Return

• retval: Rect

Python prototype (for reference only):

resultRoi(corners, sizes) -> retval

@spec resultRoiIntersection([{number(), number()}], [{number(), number()}]) ::
  {number(), number(), number(), number()} | {:error, String.t()}

resultRoiIntersection

Positional Arguments

• corners: [Point]
• sizes: [Size]

Return

• retval: Rect

Python prototype (for reference only):

resultRoiIntersection(corners, sizes) -> retval

@spec resultTl([{number(), number()}]) :: {number(), number()} | {:error, String.t()}

resultTl

Positional Arguments

• corners: [Point]

Return

• retval: Point

Python prototype (for reference only):

resultTl(corners) -> retval

@spec selectRandomSubset(integer(), integer(), [integer()]) ::
  :ok | {:error, String.t()}

selectRandomSubset

Positional Arguments

• count: int
• size: int
• subset: [int]

Python prototype (for reference only):

selectRandomSubset(count, size, subset) -> None

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

stitchingLogLevel

Return

• retval: int

Python prototype (for reference only):

stitchingLogLevel() -> retval

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

Tries to make panorama more horizontal (or vertical).

Positional Arguments

• kind: WaveCorrectKind.

  Correction kind, see detail::WaveCorrectKind.

Return

• rmats: [Evision.Mat].

  Camera rotation matrices.

Python prototype (for reference only):

waveCorrect(rmats, kind) -> rmats