View Source Evision.Text.OCRBeamSearchDecoder (Evision v0.2.7)

Summary

Types

t()

Type that represents an Text.OCRBeamSearchDecoder struct.

Functions

create(named_args)

create(classifier, vocabulary, transition_probabilities_table, emission_probabilities_table)

Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder.

create(classifier, vocabulary, transition_probabilities_table, emission_probabilities_table, opts)

Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder.

run(named_args)

run(self, image, min_confidence)

Recognize text using Beam Search.

run(self, image, min_confidence, opts)

Variant 1:

run

run(self, image, mask, min_confidence, opts)

run

Types

t()

@type t() :: %Evision.Text.OCRBeamSearchDecoder{ref: reference()}

Type that represents an Text.OCRBeamSearchDecoder struct.

ref. reference()
The underlying erlang resource variable.

Functions

create(named_args)

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

create(classifier, vocabulary, transition_probabilities_table, emission_probabilities_table)

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

Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder.

Positional Arguments

classifier: Evision.Text.OCRBeamSearchDecoder.ClassifierCallback.
The character classifier with built in feature extractor.
vocabulary: string.
The language vocabulary (chars when ASCII English text). vocabulary.size() must be equal to the number of classes of the classifier.
transition_probabilities_table: Evision.Mat.
Table with transition probabilities between character pairs. cols == rows == vocabulary.size().
emission_probabilities_table: Evision.Mat.
Table with observation emission probabilities. cols == rows == vocabulary.size().

Keyword Arguments

mode: text_decoder_mode.
HMM Decoding algorithm. Only OCR_DECODER_VITERBI is available for the moment (http://en.wikipedia.org/wiki/Viterbi_algorithm).
beam_size: integer().
Size of the beam in Beam Search algorithm.

Return

retval: OCRBeamSearchDecoder

Python prototype (for reference only):

create(classifier, vocabulary, transition_probabilities_table, emission_probabilities_table[, mode[, beam_size]]) -> retval

create(classifier, vocabulary, transition_probabilities_table, emission_probabilities_table, opts)

@spec create(
  term(),
  binary(),
  Evision.Mat.maybe_mat_in(),
  Evision.Mat.maybe_mat_in(),
  [beam_size: term(), mode: term()] | nil
) :: t() | {:error, String.t()}

Creates an instance of the OCRBeamSearchDecoder class. Initializes HMMDecoder.

Positional Arguments

classifier: Evision.Text.OCRBeamSearchDecoder.ClassifierCallback.
The character classifier with built in feature extractor.
vocabulary: string.
The language vocabulary (chars when ASCII English text). vocabulary.size() must be equal to the number of classes of the classifier.
transition_probabilities_table: Evision.Mat.
Table with transition probabilities between character pairs. cols == rows == vocabulary.size().
emission_probabilities_table: Evision.Mat.
Table with observation emission probabilities. cols == rows == vocabulary.size().

Keyword Arguments

mode: text_decoder_mode.
HMM Decoding algorithm. Only OCR_DECODER_VITERBI is available for the moment (http://en.wikipedia.org/wiki/Viterbi_algorithm).
beam_size: integer().
Size of the beam in Beam Search algorithm.

Return

retval: OCRBeamSearchDecoder

Python prototype (for reference only):

create(classifier, vocabulary, transition_probabilities_table, emission_probabilities_table[, mode[, beam_size]]) -> retval

run(named_args)

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

run(self, image, min_confidence)

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

Recognize text using Beam Search.

Positional Arguments

self: Evision.Text.OCRBeamSearchDecoder.t()
image: Evision.Mat.
Input binary image CV_8UC1 with a single text line (or word).
min_confidence: integer()

Keyword Arguments

component_level: integer().
Only OCR_LEVEL_WORD is supported.

Return

retval: String

Takes image on input and returns recognized text in the output_text parameter. Optionally provides also the Rects for individual text elements found (e.g. words), and the list of those text elements with their confidence values.

Python prototype (for reference only):

run(image, min_confidence[, component_level]) -> retval

run(self, image, min_confidence, opts)

@spec run(
  t(),
  Evision.Mat.maybe_mat_in(),
  integer(),
  [{:component_level, term()}] | nil
) ::
  binary() | {:error, String.t()}

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

Variant 1:

run

Positional Arguments

self: Evision.Text.OCRBeamSearchDecoder.t()
image: Evision.Mat
mask: Evision.Mat
min_confidence: integer()

Keyword Arguments

component_level: integer().

Return

retval: String

Python prototype (for reference only):

run(image, mask, min_confidence[, component_level]) -> retval

Variant 2:

Recognize text using Beam Search.

Positional Arguments

self: Evision.Text.OCRBeamSearchDecoder.t()
image: Evision.Mat.
Input binary image CV_8UC1 with a single text line (or word).
min_confidence: integer()

Keyword Arguments

component_level: integer().
Only OCR_LEVEL_WORD is supported.

Return

retval: String

Python prototype (for reference only):

run(image, min_confidence[, component_level]) -> retval

run(self, image, mask, min_confidence, opts)

@spec run(
  t(),
  Evision.Mat.maybe_mat_in(),
  Evision.Mat.maybe_mat_in(),
  integer(),
  [{:component_level, term()}] | nil
) :: binary() | {:error, String.t()}

run

Positional Arguments

self: Evision.Text.OCRBeamSearchDecoder.t()
image: Evision.Mat
mask: Evision.Mat
min_confidence: integer()

Keyword Arguments

component_level: integer().

Return

retval: String

Python prototype (for reference only):

run(image, mask, min_confidence[, component_level]) -> retval