# Java API Documentation (Experimental)

Package: com.realeyesit.nel

# Tracker interface

# interface Tracker

The Tracker interface

# track(ImageHeader imageHeader, long timestamp)

public TrackerResultFuture track(ImageHeader imageHeader, long timestamp)

Tracks the given frame asynchronously with the TrackerResultFuture API.

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

Parameters:

imageHeader - image descriptor
timestamp - timestamp of the image (in ms)

# resetTracking()

public void resetTracking()

Resets the internal tracking state. Should be called when a new video sequence starts.

# getEmotionIDs()

public java.util.List<EmotionID> getEmotionIDs()

Returns the emotion IDs provided by the loaded model. The order is the same as returned by ResultType.getEmotions().

See also: ResultType

# getEmotionNames()

public java.util.List<String> getEmotionNames()

Returns the emotion names provided by the loaded model. The order is the same as returned by ResultType.getEmotions().

See also: ResultType

# getMinimumFaceRatio()

public float getMinimumFaceRatio()

Gets the current minimum face ratio

See also: setMinimumFaceRatio

# setMinimumFaceRatio(float minimumFaceRatio)

public void setMinimumFaceRatio(float minimumFaceRatio)

Sets the minimum face ratio

The minimum face ratio defines the minimum face size the algorithm is looking for. The actual size is calculated from the smaller image dimension multiplied by the set minimum face ratio. The default value is 1/4.8, i.e., in case of VGA resolution input (640x480), the minimum face size is 100x100.

Warning: The shape alignment and classifier performance can degrade in case of low resolution, tracking faces smaller than 75x75 is ill advised.

Parameters:

minimumFaceRatio - new minimum face size as a ratio of the smaller image dimension

# isFaceTrackingEnabled()

public boolean isFaceTrackingEnabled()

Returns wether the face tracker is enabled

# setFaceTrackingEnabled(boolean enable)

public void setFaceTrackingEnabled(boolean enable)

Sets the face tracker to be enabled or disabled

Parameters:

enable - boolean to set to

# isEmotionEnabled(EmotionID emoID)

public boolean isEmotionEnabled(EmotionID emoID)

Returns wether the specified emotion is enabled

Parameters:

emoID - emotion to query

# setEmotionEnabled(EmotionID emoID, boolean enable)

public void setEmotionEnabled(EmotionID emoID, boolean enable)

Sets the specified emotion to enabled or disabled

Parameters:

emoID - emotion to set
enable - boolean to set to

# getModelName()

public String getModelName()

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

Returns: name of the model

# getSdkVersion()

public Version getSdkVersion()

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

Returns: version of the SDK

# getSdkVersionString()

public String getSdkVersionString()

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

Returns: version string of the SDK

# NelTracker class

# NelTracker(String modelFile, int max_concurrency)

public NelTracker(String modelFile, int max_concurrency)

Constructor

Parameters:

modelFile (str) - path for the used model
max_concurrency (int) - maximum allowed concurrency, 0 means automatic (using all cores), default: 0

# ImageHeader class

# class ImageHeader

Descriptor class for image data (non-owning)

# ImageHeader()

public ImageHeader()

Constructor

# getData()

public java.nio.ByteBuffer getData()

Returns: pointer to the byte array of the image

# setData(java.nio.ByteBuffer value)

public void setData(java.nio.ByteBuffer value)

Parameters:

value - pointer to the byte array of the image

# getFormat()

public ImageFormat getFormat()

Returns: image format

# setFormat(ImageFormat value)

public void setFormat(ImageFormat value)

Parameters:

value - image format

# getHeight()

public int getHeight()

Returns: height of the image in pixels

# setHeight(int value)

public void setHeight(int value)

Returns: height of the image in pixels

# getStride()

public int getStride()

Returns: length of one row of pixels in bytes (e.g: 3*width + padding)

# setStride(int value)

public void setStride(int value)

Parameters:

value - length of one row of pixels in bytes (e.g: 3*width + padding)

# getWidth()

public int getWidth()

Returns: width of the image in pixels

# setWidth(int value)

public void setWidth(int value)

Parameters:

value - width of the image in pixels

# enum ImageFormat

Values:

BGR - 24-bit BGR
BGRA - 32-bit BGRA or 32-bit BGR_
Grayscale - 8-bit grayscale
RGB - 24-bit RGB
RGBA - 32-bit RGBA or 32-bit RGB_

# Result classes

# enum EmotionID

IDs for the supported emotions/behaviours

Values:

ATTENTION
CONFUSION
CONTEMPT
DISGUST
EMPATHY
FEAR
HAPPY
PRESENCE
SURPRISE
EYES_ON_SCREEN
FACE_DETECTION

# interface TrackerResultFuture

Simple wrapper over the C++ future class

# get()

ResultType get()

Blocks until the future is ready and returns the result.

# interface ResultType

The ResultType struct.

# getEmotions()

java.util.List<EmotionData> getEmotions()

Detected emotions.

# getLandmarks()

LandmarkData getLandmarks()

Tracked landmarks.

# interface LandmarkData

# getScale()

double getScale()

Scale of the face.

# getRoll()

double getRoll()

Roll pose angle.

# getPitch()

double getPitch()

Pitch pose angle.

# getYaw()

double getYaw()

Yaw pose angle.

# getTranslate()

Point2d getTranslate()

Position of the head center in image coordinates.

# getLandmarks2d()

java.util.List<Point2d> getLandmarks2d()

Positions of the 49 landmarks, in image coordinates.

# getLandmarks3d()

java.util.List<Point3d> getLandmarks3d()

Positions of the 49 landmarks, in an un-scaled face-centered 3D space.

# getIsGood()

boolean getIsGood()

Whether the tracking is good quality or not.

# interface Point2d

# getX()

double getX()

# getY()

double getY()

# interface Point3d

# Point3d_GetInterfaceCPtr()

long Point3d_GetInterfaceCPtr()

# getX()

double getX()

# getY()

double getY()

# getZ()

double getZ()

# interface EmotionData

# getEmotionID()

EmotionID getEmotionID()

ID of the emotion.

# getIsActive()

boolean getIsActive()

Whether the probability is higher than an internal threshold.

# getIsDetectionSuccessful()

boolean getIsDetectionSuccessful()

Whether the tracking quality was good enough to reliable detect this emotion.

# getProbability()

double getProbability()

Probability of the emotion.

# interface Version

Semantic version number for the SDK

# getMajor()

int getMajor()

# getMinor()

int getMinor()

# getPatch()

int getPatch()