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

Clears the algorithm state

Positional Arguments

• self: Evision.CUDA.HOG.t()

Python prototype (for reference only):

clear() -> None

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

@spec compute(t(), Evision.CUDA.GpuMat.t()) ::
  Evision.CUDA.GpuMat.t() | {:error, String.t()}

Variant 1:

Returns block descriptors computed for the whole image.

Positional Arguments

• self: Evision.CUDA.HOG.t()

• img: Evision.Mat.t().

  Source image. See cuda::HOGDescriptor::detect for type limitations.

Keyword Arguments

• stream: Evision.CUDA.Stream.t().

  CUDA stream.

Return

• descriptors: Evision.Mat.t().

  2D array of descriptors.

Python prototype (for reference only):

compute(img[, descriptors[, stream]]) -> descriptors

Variant 2:

Returns block descriptors computed for the whole image.

Positional Arguments

• self: Evision.CUDA.HOG.t()

• img: Evision.CUDA.GpuMat.t().

  Source image. See cuda::HOGDescriptor::detect for type limitations.

Keyword Arguments

• stream: Evision.CUDA.Stream.t().

  CUDA stream.

Return

• descriptors: Evision.CUDA.GpuMat.t().

  2D array of descriptors.

Python prototype (for reference only):

compute(img[, descriptors[, stream]]) -> descriptors

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

@spec compute(t(), Evision.CUDA.GpuMat.t(), [{atom(), term()}, ...] | nil) ::
  Evision.CUDA.GpuMat.t() | {:error, String.t()}

Variant 1:

Returns block descriptors computed for the whole image.

Positional Arguments

• self: Evision.CUDA.HOG.t()

• img: Evision.Mat.t().

  Source image. See cuda::HOGDescriptor::detect for type limitations.

Keyword Arguments

• stream: Evision.CUDA.Stream.t().

  CUDA stream.

Return

• descriptors: Evision.Mat.t().

  2D array of descriptors.

Python prototype (for reference only):

compute(img[, descriptors[, stream]]) -> descriptors

Variant 2:

Returns block descriptors computed for the whole image.

Positional Arguments

• self: Evision.CUDA.HOG.t()

• img: Evision.CUDA.GpuMat.t().

  Source image. See cuda::HOGDescriptor::detect for type limitations.

Keyword Arguments

• stream: Evision.CUDA.Stream.t().

  CUDA stream.

Return

• descriptors: Evision.CUDA.GpuMat.t().

  2D array of descriptors.

Python prototype (for reference only):

compute(img[, descriptors[, stream]]) -> descriptors

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

Creates the HOG descriptor and detector.

Keyword Arguments

• win_size: Size.

  Detection window size. Align to block size and block stride.

• block_size: Size.

  Block size in pixels. Align to cell size. Only (16,16) is supported for now.

• block_stride: Size.

  Block stride. It must be a multiple of cell size.

• cell_size: Size.

  Cell size. Only (8, 8) is supported for now.

• nbins: int.

  Number of bins. Only 9 bins per cell are supported for now.

Return

• retval: HOG

Python prototype (for reference only):

create([, win_size[, block_size[, block_stride[, cell_size[, nbins]]]]]) -> retval

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

Creates the HOG descriptor and detector.

Keyword Arguments

• win_size: Size.

  Detection window size. Align to block size and block stride.

• block_size: Size.

  Block size in pixels. Align to cell size. Only (16,16) is supported for now.

• block_stride: Size.

  Block stride. It must be a multiple of cell size.

• cell_size: Size.

  Cell size. Only (8, 8) is supported for now.

• nbins: int.

  Number of bins. Only 9 bins per cell are supported for now.

Return

• retval: HOG

Python prototype (for reference only):

create([, win_size[, block_size[, block_stride[, cell_size[, nbins]]]]]) -> retval

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

@spec detect(t(), Evision.CUDA.GpuMat.t()) ::
  {[{number(), number()}], [number()]} | {:error, String.t()}

Variant 1:

Performs object detection without a multi-scale window.

Positional Arguments

• self: Evision.CUDA.HOG.t()

• img: Evision.Mat.t().

  Source image. CV_8UC1 and CV_8UC4 types are supported for now.

Return

• found_locations: [Point].

  Left-top corner points of detected objects boundaries.

• confidences: [double].

  Optional output array for confidences.

Python prototype (for reference only):

detect(img) -> found_locations, confidences

Variant 2:

Performs object detection without a multi-scale window.

Positional Arguments

• self: Evision.CUDA.HOG.t()

• img: Evision.CUDA.GpuMat.t().

  Source image. CV_8UC1 and CV_8UC4 types are supported for now.

Return

• found_locations: [Point].

  Left-top corner points of detected objects boundaries.

• confidences: [double].

  Optional output array for confidences.

Python prototype (for reference only):

detect(img) -> found_locations, confidences

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

@spec detectMultiScale(t(), Evision.CUDA.GpuMat.t()) ::
  {[{number(), number(), number(), number()}], [number()]}
  | {:error, String.t()}

Variant 1:

Performs object detection with a multi-scale window.

Positional Arguments

• self: Evision.CUDA.HOG.t()

• img: Evision.Mat.t().

  Source image. See cuda::HOGDescriptor::detect for type limitations.

Return

• found_locations: [Rect].

  Detected objects boundaries.

• confidences: [double].

  Optional output array for confidences.

Python prototype (for reference only):

detectMultiScale(img) -> found_locations, confidences

Variant 2:

Performs object detection with a multi-scale window.

Positional Arguments

• self: Evision.CUDA.HOG.t()

• img: Evision.CUDA.GpuMat.t().

  Source image. See cuda::HOGDescriptor::detect for type limitations.

Return

• found_locations: [Rect].

  Detected objects boundaries.

• confidences: [double].

  Optional output array for confidences.

Python prototype (for reference only):

detectMultiScale(img) -> found_locations, confidences

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

@spec detectMultiScaleWithoutConf(t(), Evision.CUDA.GpuMat.t()) ::
  [{number(), number(), number(), number()}] | {:error, String.t()}

Variant 1:

Performs object detection with a multi-scale window.

Positional Arguments

• self: Evision.CUDA.HOG.t()

• img: Evision.Mat.t().

  Source image. See cuda::HOGDescriptor::detect for type limitations.

Return

• found_locations: [Rect].

  Detected objects boundaries.

Python prototype (for reference only):

detectMultiScaleWithoutConf(img) -> found_locations

Variant 2:

Performs object detection with a multi-scale window.

Positional Arguments

• self: Evision.CUDA.HOG.t()

• img: Evision.CUDA.GpuMat.t().

  Source image. See cuda::HOGDescriptor::detect for type limitations.

Return

• found_locations: [Rect].

  Detected objects boundaries.

Python prototype (for reference only):

detectMultiScaleWithoutConf(img) -> found_locations

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

@spec detectWithoutConf(t(), Evision.CUDA.GpuMat.t()) ::
  [{number(), number()}] | {:error, String.t()}

Variant 1:

Performs object detection without a multi-scale window.

Positional Arguments

• self: Evision.CUDA.HOG.t()

• img: Evision.Mat.t().

  Source image. CV_8UC1 and CV_8UC4 types are supported for now.

Return

• found_locations: [Point].

  Left-top corner points of detected objects boundaries.

Python prototype (for reference only):

detectWithoutConf(img) -> found_locations

Variant 2:

Performs object detection without a multi-scale window.

Positional Arguments

• self: Evision.CUDA.HOG.t()

• img: Evision.CUDA.GpuMat.t().

  Source image. CV_8UC1 and CV_8UC4 types are supported for now.

Return

• found_locations: [Point].

  Left-top corner points of detected objects boundaries.

Python prototype (for reference only):

detectWithoutConf(img) -> found_locations

@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.CUDA.HOG.t()

Return

• retval: bool

Python prototype (for reference only):

empty() -> retval

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

Returns the block histogram size.

Positional Arguments

• self: Evision.CUDA.HOG.t()

Return

• retval: size_t

Python prototype (for reference only):

getBlockHistogramSize() -> retval

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

getDefaultName

Positional Arguments

• self: Evision.CUDA.HOG.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 getDefaultPeopleDetector(t()) :: Evision.Mat.t() | {:error, String.t()}

Returns coefficients of the classifier trained for people detection.

Positional Arguments

• self: Evision.CUDA.HOG.t()

Return

• retval: Evision.Mat.t()

Python prototype (for reference only):

getDefaultPeopleDetector() -> retval

@spec getDescriptorFormat(t()) ::
  Evision.CUDA.HOGDescriptor_DescriptorStorageFormat.t() | {:error, String.t()}

getDescriptorFormat

Positional Arguments

• self: Evision.CUDA.HOG.t()

Return

• retval: HOGDescriptor::DescriptorStorageFormat

Python prototype (for reference only):

getDescriptorFormat() -> retval

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

Returns the number of coefficients required for the classification.

Positional Arguments

• self: Evision.CUDA.HOG.t()

Return

• retval: size_t

Python prototype (for reference only):

getDescriptorSize() -> retval

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

getGammaCorrection

Positional Arguments

• self: Evision.CUDA.HOG.t()

Return

• retval: bool

Python prototype (for reference only):

getGammaCorrection() -> retval

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

getGroupThreshold

Positional Arguments

• self: Evision.CUDA.HOG.t()

Return

• retval: int

Python prototype (for reference only):

getGroupThreshold() -> retval

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

getHitThreshold

Positional Arguments

• self: Evision.CUDA.HOG.t()

Return

• retval: double

Python prototype (for reference only):

getHitThreshold() -> retval

@spec getL2HysThreshold(t()) :: number() | {:error, String.t()}

getL2HysThreshold

Positional Arguments

• self: Evision.CUDA.HOG.t()

Return

• retval: double

Python prototype (for reference only):

getL2HysThreshold() -> retval

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

getNumLevels

Positional Arguments

• self: Evision.CUDA.HOG.t()

Return

• retval: int

Python prototype (for reference only):

getNumLevels() -> retval

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

getScaleFactor

Positional Arguments

• self: Evision.CUDA.HOG.t()

Return

• retval: double

Python prototype (for reference only):

getScaleFactor() -> retval

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

getWinSigma

Positional Arguments

• self: Evision.CUDA.HOG.t()

Return

• retval: double

Python prototype (for reference only):

getWinSigma() -> retval

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

getWinStride

Positional Arguments

• self: Evision.CUDA.HOG.t()

Return

• retval: Size

Python prototype (for reference only):

getWinStride() -> retval

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

Reads algorithm parameters from a file storage

Positional Arguments

• self: Evision.CUDA.HOG.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.CUDA.HOG.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 setDescriptorFormat(t(), Evision.CUDA.HOGDescriptor_DescriptorStorageFormat.t()) ::
  t() | {:error, String.t()}

setDescriptorFormat

Positional Arguments

• self: Evision.CUDA.HOG.t()
• descr_format: HOGDescriptor_DescriptorStorageFormat

Python prototype (for reference only):

setDescriptorFormat(descr_format) -> None

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

setGammaCorrection

Positional Arguments

• self: Evision.CUDA.HOG.t()
• gamma_correction: bool

Python prototype (for reference only):

setGammaCorrection(gamma_correction) -> None

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

setGroupThreshold

Positional Arguments

• self: Evision.CUDA.HOG.t()
• group_threshold: int

Python prototype (for reference only):

setGroupThreshold(group_threshold) -> None

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

setHitThreshold

Positional Arguments

• self: Evision.CUDA.HOG.t()
• hit_threshold: double

Python prototype (for reference only):

setHitThreshold(hit_threshold) -> None

@spec setL2HysThreshold(t(), number()) :: t() | {:error, String.t()}

setL2HysThreshold

Positional Arguments

• self: Evision.CUDA.HOG.t()
• threshold_L2hys: double

Python prototype (for reference only):

setL2HysThreshold(threshold_L2hys) -> None

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

setNumLevels

Positional Arguments

• self: Evision.CUDA.HOG.t()
• nlevels: int

Python prototype (for reference only):

setNumLevels(nlevels) -> None

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

setScaleFactor

Positional Arguments

• self: Evision.CUDA.HOG.t()
• scale0: double

Python prototype (for reference only):

setScaleFactor(scale0) -> None

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

@spec setSVMDetector(t(), Evision.CUDA.GpuMat.t()) :: t() | {:error, String.t()}

Variant 1:

Sets coefficients for the linear SVM classifier.

Positional Arguments

• self: Evision.CUDA.HOG.t()
• detector: Evision.Mat.t()

Python prototype (for reference only):

setSVMDetector(detector) -> None

Variant 2:

Sets coefficients for the linear SVM classifier.

Positional Arguments

• self: Evision.CUDA.HOG.t()
• detector: Evision.CUDA.GpuMat.t()

Python prototype (for reference only):

setSVMDetector(detector) -> None

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

setWinSigma

Positional Arguments

• self: Evision.CUDA.HOG.t()
• win_sigma: double

Python prototype (for reference only):

setWinSigma(win_sigma) -> None

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

setWinStride

Positional Arguments

• self: Evision.CUDA.HOG.t()
• win_stride: Size

Python prototype (for reference only):

setWinStride(win_stride) -> None

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

Stores algorithm parameters in a file storage

Positional Arguments

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

Has overloading in C++

Python prototype (for reference only):

write(fs, name) -> None