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# C++ API Documentation

# Estimator class

# class del::DemographicEstimator

The Demographic Estimator class

# Constructors 

DemographicEstimator(const std::string& modelFile, int maxConcurrency = 0)

Constructor: loads model file, sets up the processing.

Parameters:

  • modelFile - path for the used model
  • maxConcurrency - maximum allowed concurrency, 0 means automatic (using all cores), default: 0
~DemographicEstimator()

Destructor

# Methods 

std::future<std::vector<del::Face>> detectFaces(const del::ImageHeader& imageHeader)

Detects the faces on an image with the std::future API.

Note: The given ImageHeader doesn't own the image data, and it is safe to delete the data after the call, a copy is happening internally. See del::ImageHeader for details.

Note: Calling this function is non-blocking, so calling it again with the next image without waiting for the result is possible. Also see getConcurrentCalculations().

Note: This is the std::future based API, for callback API see del::DemographicEstimator::detectFaces(const del::ImageHeader&, std::function<void (ResultOrError<std::vector<Face>>)>).

Parameters:

  • imageHeader - image descriptor
void detectFaces(const del::ImageHeader& imageHeader,
                 std::function<void (ResultOrError<std::vector<Face>>)> callback)

Detects the faces on an image with a callback API.

Note: The given ImageHeader doesn't own the image data, and it is safe to delete the data after the call, a copy is happening internally. See del::ImageHeader for details.

Note: Calling this function is non-blocking, so calling it again with the next frame without waiting for the result is possible. Also see getConcurrentCalculations().

Note: This is the callback based API, for std::future API see del::DemographicEstimator::detectFaces(const del::ImageHeader&).

Parameters:

  • imageHeader - image descriptor
  • callback - callback to call with the result

Returns: tracked landmarks and emotions

std::future<std::vector<del::Output>> estimate(const del::Face& face)

Returns the demographic estimation of the detected face.

Note: Calling this function is non-blocking, so calling it again with the next frame without waiting for the result is possible. Also see getConcurrentCalculations().

Note: This is the std::future based API, for callback API see del::DemographicEstimator::estimate(const del::Face&, std::function<void (ResultOrError<std::vector<del::Output>>)>).

Parameters:

  • face - the previously detected face to embed

Returns: estimations

void estimate(const del::Face& face,
              std::function<void (ResultOrError<std::vector<del::Output>>)> callback)

Returns the demographic estimation of the detected face.

Note: Calling this function is non-blocking, so calling it again with the next frame without waiting for the result is possible. Also see getConcurrentCalculations().

Note: This is the callback based API, for std::future API see del::DemographicEstimator::estimate(const del::Face&).

Parameters:

  • face - the previously detected face to embed
  • callback - callback to call with the result
int getConcurrentCalculations() const

Returns the value of the atomic counter for the number of calculations currently running concurrently. You can use this to limit the number of concurrent calculations.

Returns: The (approximate) number of calculations currently in-flight.

std::string getModelName() const

Returns the name (version etc) of the loaded model.

Returns: name of the model

static del::Version getSDKVersion()

Returns the version of the SDK (and not the model)

Returns: version of the SDK

static std::string getSDKVersionString()

Returns the version string of the SDK (and not the model)

Returns: version string of the SDK

# Image header class

# struct del::ImageHeader

Descriptor class for image data (non-owning)

Members:

  • const uint8_t* data - pointer to the byte array of the image
  • int width - width of the image in pixels
  • int height - height of the image in pixels
  • int stride - length of one row of pixels in bytes (e.g: 3*width + padding)
  • del::ImageFormat format - image format

# enum class del::ImageFormat

Values:

  • Grayscale = 0 - 8-bit grayscale
  • RGB = 1 - 24-bit RGB
  • RGBA = 2 - 32-bit RGBA or 32-bit RGB_
  • BGR = 3 - 24-bit BGR
  • BGRA = 4 - 32-bit BGRA or 32-bit BGR_

# Result classes

# Face

See also: landmarks specification.

# class del::Face

Face Class

# Constructors 
Face(const del::ImageHeader& imageHeader,
     const std::vector<del::Point2d>& landmarks,
     const del::BoundingBox& bbox = del::BoundingBox(),
     float confidence = 0.0f)

Constructor for the Face object to support 3rd party face detectors

Parameters:

  • imageHeader - image descriptor
  • landmarks - face landmarks
  • bbox - face bounding box
  • confidence - face detection confidence
~Face()

Destructor

# Methods 
BoundingBox boundingBox() const

Returns the bounding box of the detected face

Returns: BoundingBox

float confidence() const

Returns the confidence value of the detected face

Returns: float

std::vector<del::Point2d> landmarks() const

Returns the landmarks of the face

Returns: std::vectordel::Point2d

# Point2d

# struct del::Point2d

Point2d class for landmarks

Members:

  • float x - x coordinate of the point
  • float y - y coordinate of the point

# BoundingBox

# struct del::BoundingBox

Bounding Box class for the faces

Members:

  • int x - x coordinate of the top-left corner
  • int y - y coordinate of the top-left corner
  • int width - width of the bounding box in pixels
  • int height - height of the bounding box in pixels

# OutputType

# enum class del::OutputType

Type of the output in Output struct.

Values:

  • AGE = 0
  • GENDER = 1
  • AGE_UNCERTAINTY = 2

# Gender

# enum class del::Gender

Gender enum.

Values:

  • FEMALE = 0
  • MALE = 1

# Output

# struct del::Output

Output struct for various estimated outputs.

Members:

  • del::OutputType type - type of the output
  • std::variant<Gender, float> value - value of the output
  • std::string name - name of the output