Face recognition API V1.0
Hardware Interface API
1. Led control
Example code for controlling Led:
//red light
HardwareCtrl.ctrlLedSwitch( HardwareCtrl.LED_RED, true);
or
HardwareCtrl.ctrlLedRed(true);
//green light
HardwareCtrl.ctrlLedSwitch( HardwareCtrl.LED_GREEN, true);
or
HardwareCtrl.ctrlLedGreen(true);
//white light
HardwareCtrl.ctrlLedSwitch( HardwareCtrl.LED_WHITE, true);
or
HardwareCtrl.ctrlLedWhite(true);
//Only turn on the white light and turn off the other Led lights.
HardwareCtrl.ctrlLedOnlyOpenWhite();//green light only：ctrlLedOnlyOpenGreen(), red light only：ctrlLedOnlyOpenRed();
//Hardware version 2.3 and above supports adjusting the brightness of white led light, while green light and red light do not support adjusting the brightness.
HardwareCtrl.ctrlWhiteLightness(0);//Control the brightness of white led light: value range: 0-8
2. Control screen brightness
public static void setBrightness(int value)
Function Adjust screen brightness
Parameter value : range: 0 to 255
Example ：
HardwareCtrl.setBrightness(255);
3. Backlight control switch
public static void ctrlBlPower(boolean open)
Function Backlight control switch
Parameter open :true is on, false is off
Example ：
HardwareCtrl.ctrlBlPower(true);
4. Screen touch switch
public static void ctrlTp(boolean open)
Function Screen touch switch
Parameter open : true is on, false is off
Example ：
HardwareCtrl.ctrlTp(true);
5. RS485 / RS232 signal
Open RS485/RS232 serial port
public static SerialPort openSerialPortSignal(File device, int
baudrate, SerialPort.Callback callback)
Function Open RS485/RS232 serial port
Parameter device : Serial port file baudrate : Baud rate
callback : callback
public static void sendSerialPortHexMsg(SerialPort mSerialPort,
String msg)
Function Send signal
Parameter mSerialPort : Serial port object msg :Signal
(hex string, such as "1E60010000002F")
public statis void closeSerialPortSignal(SerialPort mSerialPort)
Function Close the RS485/RS232 serial port
Parameter void
Example ：
// Enter related content
/ **
such as:
1.A opens the gate to the credit card, the upper computer needs to send hexadecimal data:
Send: 0x1E 0x60 0x01 0x00 0x00 0x00 0x2F
The return code of the gate is divided into the following types:
a), the person has passed the gate
Returns: 0x1E 0x61 0x01 0x00 0x00 0x00 0x2F
b) The card does not pass the gate after a timeout after the card is swiped, the gate automatically closes the door and cancels the passage
Returns: 0x1E 0x44 0x01 0x00 0x00 0x00 0x2F
c) After the card is swiped, someone passes the gate in the reverse direction, and the gate is automatically closed to cancel the passage.
Returns: 0x1E 0x44 0x01 0x00 0x00 0x00 0x2F
*/
//Open RS485/RS232 serial port
SerialPort mSerialPort = HardwareCtrl.openSerialPortSignal(new File("dev/ttyS4"), 9600, new SerialPort.Callback() {
@Override
public void onDataReceived(byte[] buffer, int size) {
String result = StringUtils.bytesToHexString(buffer, size);
Log.e("lkdong","result = "+result);
}
});
//Send signal
HardwareCtrl.sendSerialPortHexMsg(mSerialPort, "1E60010000002F");
//Close the RS485/RS232 serial port
HardwareCtrl.closeSerialPortSignal(mSerialPort);
6. Wigan 26/34 signal
Wigan 26
public static void sendWiegandSignal(String msg)
Function Wiegand Signal Control
Parameter msg :
Wigan 34
public static void sendWiegand34Signal(String msg)
Function Wiegand Signal Control
Parameter msg :
Example ：
//Enter related content, such as card number, etc.
HardwareCtrl.sendWiegandSignal("1233456789");
7.Wigan input
public static void recvWiegandSignal(RecvWiegandCallBack callBack)
Function Wiegand signal input
Parameter callBack : Wiegand input signal return value interface
Example ：
HardwareCtrl.openRecvMiegandSignal("/dev/wiegand");//Open serial port
HardwareCtrl.recvWiegandSignal(new RecvWiegandCallBack() {
@Override
public void recvWiegandMsg(int i) {
Log.e("lkdong","recvWiegandMsg = "+i);
}
});
HardwareCtrl.closeRecvMiegandSignal();
8. RelaySignal
public static void sendRelaySignal(boolean up)
Function Relay control
Parameter up : The signal is pulled up to true and pulled down to
false.
Example ：
HardwareCtrl.sendRelaySignal(!HardwareCtrl.getRelayValue());
9. Radar
The working principle of the radar function: within the radar
radiation range, with or without object activity, the key value is
reported to the Android application layer, and developers can develop
according to their own needs.
Example ：
public class MainActivity extends AppCompatActivity {
//Radar key value pair
public static final int KEYCODE_RADAR_IN = 305;//There is object activity
public static final int KEYCODE_RADAR_OUT = 306;//No object activity
@Override
public boolean dispatchKeyEvent(KeyEvent event) {
Log.v("lkdong", "dispatchKeyEvent keycode=" + event.getKeyCode());
if (event.getKeyCode() == KEYCODE_RADAR_IN) {//Radar reports object activity
if (event.getAction() == KeyEvent.ACTION_UP) {
//TODO
}
} else if (event.getKeyCode() == KEYCODE_RADAR_OUT) {//Radar reports no object activity
if (event.getAction() == KeyEvent.ACTION_UP) {
//TODO
}
}
return super.dispatchKeyEvent(event);
}
}
10.NFC
The principle of the nfc function: When the card is swiped, the system
will report the key value to the Android application layer, and save
the card information on the / dev / dl1825 node. When developing an
NFC card reader, you need to read the "/dev/dl1825" node value after
receiving the system report key value.
Example ：
public class MainActivity extends AppCompatActivity {
//NFC key pair
public static final int KEYCODE_NFC=307;
@Override
public boolean dispatchKeyEvent(KeyEvent event) {
Log.v("lkdong", "dispatchKeyEvent keycode=" + event.getKeyCode());
if (event.getKeyCode() == KEYCODE_NFC) {
if (event.getAction() == KeyEvent.ACTION_UP) {
//NFC card reading, please refer to the bottom gpiodemo for detailed implementation process.
String mNfcCode = NfcUtil.getCode();
}
}
return super.dispatchKeyEvent(event);
}
}
11.Qrcode
The two-dimensional code reading is mainly performed through the
serial port. The specific operation process is as follows:
Example ：
public class QrCodeUtil {
public static final String TAG = QrCodeUtil.class.getSimpleName();
//The current command is based on module e3000h
public static final byte[] ENABLE_QR_CONFIG = new byte[]{0x07, (byte) 0xC6, 0x04, 0x08, 0x00, (byte) 0xEC, 0x01, (byte) 0xFE, 0x3A};
public static final byte[] DISABLE_QR_CONFIG = new byte[]{0x07, (byte) 0xC6, 0x04, 0x08, 0x00, (byte) 0xEC, 0x00, (byte) 0xFE, 0x3B};
public static final byte[] LED_ON = new byte[]{0x08, (byte) 0xC6, 0x04, 0x08, 0x00, (byte) 0xF2, 0x02, 0x01, (byte) 0xFE, 0x31};
public static final byte[] LED_OFF = new byte[]{0x08, (byte) 0xC6, 0x04, 0x08, 0x00, (byte) 0xF2, 0x02, 0x02, (byte) 0xFE, 0x30};
public static final byte[] LED_AUTO = new byte[]{0x08, (byte) 0xC6, 0x04, 0x08, 0x00, (byte) 0xF2, 0x02, 0x00, (byte) 0xFE, 0x32};
public static final byte[] COMMADN_RESULT = new byte[]{0x04, (byte) 0xd0, 0x00, 0x00, (byte) 0xff, 0x2c};
private SerialPort mQrCodeSerialPort = null;
private static QrCodeUtil sQrCodeUtil = null;
private static boolean sQrCodeSupport = true;
/**
* Enable QR code recognition and open serial port
*/
public static void open() {
if (isQrCodeSupport() && sQrCodeUtil != null) {
sQrCodeUtil.openQrCodeSerialPort(new SerialPort.Callback() {
@Override
public void onDataReceived(byte[] bytes, int i) {
if (QrCodeUtil.isCommandResult(bytes, i)) {
} else {
String s = new String(bytes, 0, i);
Log.v(TAG, "QR string " + s);
if (sQrCodeUtil.mQRCodeCallback != null) {
sQrCodeUtil.mQRCodeCallback.onQrCodeData(s);
}
}
}
});
}
}
/**
* Close the QR code identification serial port
*/
public static void close() {
if (isQrCodeSupport() && sQrCodeUtil != null) {
sQrCodeUtil.closeQrCodeSerialPort();
}
}
/**
* Close the serial port and release
*/
public static void destory() {
if (isQrCodeSupport() && sQrCodeUtil != null) {
sQrCodeUtil.closeQrCodeSerialPort();
sQrCodeUtil = null;
}
}
/**
* Open serial port
*
* @param qrCodeDataCallBack
*/
private void openQrCodeSerialPort(SerialPort.Callback qrCodeDataCallBack) {
if (mQrCodeSerialPort == null) {
Log.v(TAG, "openQrCodeSerialPort===");
mQrCodeSerialPort = HardwareCtrl.openSerialPortSignal(new File("/dev/ttyS0"), 9600, qrCodeDataCallBack);
disableQRCodeConfig();
}
}
/**
* Close serial port
*/
private void closeQrCodeSerialPort() {
Log.v(TAG, "closeQrCodeSerialPort()");
if (mQrCodeSerialPort != null) {
HardwareCtrl.closeQrCodeSerialPort(mQrCodeSerialPort);
mQrCodeSerialPort = null;
}
}
/**
* Turn on identification configuration QR code function
*/
private void enableQRCodeConfig() {
if (mQrCodeSerialPort != null) {
mQrCodeSerialPort.sendHexMsg(ENABLE_QR_CONFIG);
}
}
/**
* Turn off identification configuration QR code function
*/
private void disableQRCodeConfig() {
if (mQrCodeSerialPort != null) {
mQrCodeSerialPort.sendHexMsg(DISABLE_QR_CONFIG);
}
}
/**
* Qrcode light automatically turns on during scanning
*/
private void setLEDAuto() {
if (mQrCodeSerialPort != null) {
mQrCodeSerialPort.sendHexMsg(LED_AUTO);
}
}
/**
* Qrcode light is always off
*/
private void setLEDOFF() {
if (mQrCodeSerialPort != null) {
mQrCodeSerialPort.sendHexMsg(LED_OFF);
}
}
/**
* Qrcode light on all the time
*/
private void setLEDON() {
if (mQrCodeSerialPort != null) {
mQrCodeSerialPort.sendHexMsg(LED_ON);
}
}
/**
* Configure QR code scan qrcode light status.
* At present, it is only opened and closed automatically during scanning
*
* @param isAuto
*/
public static void setLedState(boolean isAuto) {
if (isQrCodeSupport() && sQrCodeUtil != null) {
if (isAuto)
sQrCodeUtil.setLEDAuto();
else
sQrCodeUtil.setLEDOFF();
}
}
public interface QRCodeCallback {
public void onQrCodeData(String s);
}
private QRCodeCallback mQRCodeCallback;
/**
* Support successful monitoring of QR code scanning
*
* @param callback
*/
public void setQRCodeCallback(QRCodeCallback callback) {
mQRCodeCallback = callback;
}
}
12. Normal GPIO control
D0 Signal
public static void sendSignalD0(boolean up)
Function GPIO D0 signal control
Parameter up : false is pulled low, true is pulled high
Example ：
HardwareCtrl.sendSignalD0(true);
D1 Signal
public static void sendSignalD1(boolean up)
Function GPIO D1 signal control
Parameter up : false is pulled low, true is pulled high
Example ：
HardwareCtrl.sendSignalD1(true);
13. Shutdown
public static void shutdown()
Function Shutdown
Parameter void
Example ：
HardwareCtrl.shutdown();
14. reboot
public static void reboot()
Function reboot
Parameter void
Example ：
HardwareCtrl.reboot();
15. Watchdog
public static void setWdt(int value)
Function System freezes or does not respond for a long time,
reboot the device
Parameter value ： Valid values are integer values between 0
(inclusive) and 3 (inclusive). 0 means reboot after 0.46s
of crash 1 means reboot after 2.56s of crash 2
means reboot after 10.24s of crash 3 means reboot after
40.96s of crash
Example ：
HardwareCtrl.ctrlWdt(1);
16. Get device unique ID
public static String getFireflyCid()
Function device unique ID
Parameter void
Example ：
String cid = HardwareCtrl.getFireflyCid();
17. Other commands
public static void execSuCmd(String command)
Function Run command through shell
Parameter command：command
Example ：
//Such as syncing files, etc.
HardwareCtrl.execSuCmd("sync");
18. Other GPIO use
public static int gpioParse(String gpioStr)
Function Convert gpio name to corresponding gpio encoding
Parameter gpioStr：gpio name, such as GPIO2_A2
public static void ctrlGpio(int gpio, String direction, int value)
Function Controlling GPIO
Parameter gpio：gpio encoding, such as 152 direction :
value : Set GPIO value
Example ：
HardwareCtrl.ctrlGpio(HardwareCtrl.gpioParse("GPIO2_A2"), "out", 1);
19.TestGpioDemo download link
https://drive.google.com/open?id=14wzm7jRB9rdi-0MnwpOW6gWiPksjDlRC
Android Quick start
1. Add dependent libraries
Copy facelibrary-release.aar and openCVLibrary331-release.aar to the app/libs directory
2. Add compile information for aar
Add the following code to build.gradle's dependencies:
compile(name: 'facelibrary-release', ext: 'aar')
compile(name: 'openCVLibrary331-release', ext: 'aar')
3. Setting permissions
Add the following permissions in the AndroidManifest.xml file
4. Defining FaceAPP variables in your program
private FaceAPP face = FaceAPP.GetInstance(); //Get the instance of FaceApp
5.Calling Android API interface through face
Face recognition SDK
This SDK development guide will guide you how to install and configure
the development environment, and how to perform secondary development
and system integration by calling the interface (API) provided by the
SDK. Users can call the API provided by the SDK according to
requirements to achieve the purpose of using services such as face
detection / tracking, living body recognition, face recognition, and
other services.
1. Return values
public static final int SUCCESS = 0; //execution succeed public
static final int ERROR_INVALID_PARAM = -1; //Illegal parameter
public static final int ERROR_TOO_MANY_REQUESTS = -2; //Too many
requests public static final int ERROR_NOT_EXIST = -3; //does not
exist public static final int ERROR_FAILURE = -4; // Execution
failed
2. FaceInfo
public class FaceInfo {
public Rect mRect;//Face recognition frame
public FaceAttribute mAttr;//Face attributes
public FaceQuality mQuality;//Face recognition quality
public Landmark mLandmark;//Used to store the coordinates of 5 key points, which are left eye, right eye, nose, left side of lips, right side of lips
}
3. FaceAttribute
public class FaceAttribute {
public int mGender;//Gender 0-> Male, 1->Female
public int mEmotion;//expression 0->calm 1->glad
public int mAge;//Age
}
4. FaceQuality
public class FaceQuality {
public float mScore;//Confidence in Face Quality
public float mLeftRight;//Roll
public float mUpDown;//Pitch
public float mHorizontal;//Yaw
public float mClarity;//Clarity
public float mBright;//Bright
}
5. Constructors
static FaceAPP GetInstance()
Function: Returns the FaceApp object
Parameters: void
Returns: FaceAPP
Example ：
private FaceAPP face = FaceAPP.GetInstance();
6. Recognize facial features
int Recognize( Image image, float featureArray [][512], int size,
List faceinfos, int[] res )
Function : Identify the facial features in the submitted Image,
then compare with the data in the featureArray to find the data
with the highest similarity.Returns the index of the array.
Parameters : image : Image object holding face image
featureArray : An array of facial feature values. The length of
the facial feature value array is 512.
size : The length of featureArray
faceinfos : FaceInfo checklist. FaceInfo is an object used to
save the results of operations
res: Face recognition results.The length of res is always 1.If no
face is recognized in the picture,res[0] return
ERROR_INVALID_PARAM.If the face in image is not in
featureArray,res[0] return ERROR_NOT_EXIST.If res [0]> = 0, the
index of the featureArray is returned.
Returns Execution succeed return SUCCESS Execution failed
return ERROR_FAILURE
Example ：
float[][] featurelist = new float[][]; //Array storing facial feature values
int size = featurelist.lenth;
int[] ret = new int[1];
byte[] tmpPos = new byte[1024];
FaceAPP.Image image = FaceAPP.GetInstance().new Image();
image.matAddrframe = mRgbaFrame.getNativeObjAddr();
face.Recognize( image, featurelist, size, tmpPos, res );
7. Recognize facial features(According to facial feature values)
int Recognize( float[] feature, float featureArray [][512], int
size, float[] high, int[] res )
Function : According to the input facial feature values, then
compare with the data in the featureArray to find the data with the
highest similarity.Returns the index of the array。
Parameters : feature : Facial feature values
featureArray : An array of facial feature values. The length of
the facial feature value array is 512.
size : The length of featureArray
high : Similarity score
res : Face recognition results.The length of res is always 1.If
no face is recognized in the picture,res[0] return
ERROR_INVALID_PARAM.If the face in image is not in featureArray,
res[0] return ERROR_NOT_EXIST. If res [0]> = 0, the index of the
featureArray is returned.
Returns Execution succeed return SUCCESS Execution
failed return ERROR_FAILURE
Example ：
float[][] featurelist = new float[][]; //Array storing facial feature values
int size = featurelist.lenth;
int[] ret = new int[1];
byte[] tmpPos = new byte[1024];
float[] feature;
float[] high = float[1];
FaceAPP.Image image = FaceAPP.GetInstance().new Image();
image.matAddrframe = mRgbaFrame.getNativeObjAddr();
face.Recognize( feature, featurelist, size, high, tmpPos, res );
8. Detect faces
int Detect( Image image, List faceinfos, int[] res )
Function : Detect faces in submitted pictures
Parameters : image : Image object containing a face image
faceinfos : FaceInfo checklist. FaceInfo is an object used to
save the results of operations
res : Face recognition results.The length of res is always 1.If
no face is recognized in the picture,res[0] return
ERROR_INVALID_PARAM.
Returns Execution succeed return SUCCESS Execution
failed return ERROR_FAILURE
Example ：
int[] ret = new int[1];
byte[] tmpPos = new byte[1024];//Used to store location information
FaceAPP.Image image = FaceAPP.GetInstance().new Image(); //Init
image.matAddrframe = mRgbaFrame.getNativeObjAddr(); //Set the memory address of the picture to be identified
if( success = face.Detect( image, tmpPos, res ) ){
//to do
};
9. Compare feature data
int Compare( float[] origin, float[] chose, float score )
Function : Used to compare the similarity of two feature values
Parameters : origin : Feature array to be compared
chose : Feature array for comparison
score : similarity between origin and chose
Returns Execution succeed return SUCCESS Execution
failed return ERROR_FAILURE
Example ：
float score;
float[] origin = new float[512];
Float[] chose = new float[512];
face.Compare( origin, chose, score );
10. Face extraction with binocular and living body
int GetFeature( Image image, Image grayImage, float[] feature, List
faceinfos, int[] res )
Function : Extracting facial features from data obtained by
binocular cameras,and only one face can be extracted.
Parameters: image : Image object containing a face image
grayImage : Image object containing an infrared image
feature : Stores the facial feature information of the detection
results, and returns an empty array without a face
faceinfos : FaceInfo checklist. FaceInfo is an object used to
save the results of operations
res : Face recognition results.The length of res is always 1.If
no face is recognized in the picture,res[0] return
ERROR_INVALID_PARAM.
Returns SUCCESS : Successfully obtained face information
ERROR_FAILURE : No face information was obtained
Example ：
float[] feature = new float[512];
int[] ret = new int[1];
byte[] tmpPos = new byte[1024]; //Used to store location information
ret = face.GetFeature( image, grayImage, feature, tmpPos, res);
if( ret == SUCCESS ){
//to do
}
11. Liveness Detection
int DetectLiveness(Image image, List faceinfos, int[] res)
Function: Detect whether a face is alive.
Parameters: image : Color face pictures, pictures for detection
and recognition.
faceinfos : FaceInfo checklist. FaceInfo is an object used to
save the results of operations
res : Face recognition results.The length of res is always 1.If
no face is recognized in the picture,res[0] return
ERROR_INVALID_PARAM.
Returns SUCCESS : Living ERROR_FAILURE : Non-living
Example ：
int[] ret=new int[1];
ret= face.DetectLiveness(image,grayImage ,tmpPos,res);
if(ret== SUCCESS){
//to do
}
12. Binocular for Liveness detection
int GetDetectLiveness(Image image, Image grayImage, List faceinfos,
int[] res)
Function: Detect whether a face is alive.
Parameters: image : Color face pictures, pictures for detection
and recognition.
grayImage :Image object containing an infrared image.
faceinfos : FaceInfo checklist. FaceInfo is an object used to
save the results of operations
res : Face recognition results.The length of res is always
1.If no face is recognized in the picture,res[0] return
ERROR_INVALID_PARAM.
Returns SUCCESS : Living ERROR_FAILURE : Non-living
Example ：
int[] ret=new int[1];
ret= face.GetDetectLiveness(image,grayImage ,tmpPos,res);
if(ret== SUCCESS){
//to do
}
13. Binocular Calibration
int Calibration( Image image, Image grayImage, float[] scale, int[]
Rect, int[] res );
Function: The calibration of the dual camera recognition consisting
of infrared light and ordinary light requires one person to stand
at the optimal position (0.8-1 meters), and it takes about 20
checks to obtain the face correction parameters. And return the
coordinates of the infrared camera display area relative to
ordinary light, this area is an effective recognition and living
body detection area.
Parameters : image : Color face pictures, pictures for detection
and recognition.
grayImage : Image object containing an infrared image
scale : Returns Face Frame Correction Parameters
rect : Returns the overlapping area of the infrared image and the
color image (the corresponding area of the infrared image in the
color image / recommended detection area)
res : Face recognition results.The length of res is always 1.If
no face is recognized in the picture,res[0] return
ERROR_INVALID_PARAM.
Returns SUCCESS : Calibration succeeded ERROR_FAILURE :
Calibration failed
Example ：
int[] ret = new int[1];
float[] scale = new float[1];
int[] rect = new int[4];
ret = face.Calibration( image, grayimage, scale, rect, res );
if( ret == SUCCESS ){
//to do
}
14. Device Activation 1
int AuthorizedDevice( String uidStr, String password, Context
activity )
Function: Device activation
Parameters: uidStr : OEMID + contract Id
password : password
Returns 0 : Authentication succeeded
Example ：
String oem_id = "1000000000000001";//OEMID
String contract_id = "0001";// contract Id
String password = "0123456789abcdef0123456789abcdef"; //password
String uidStr = oem_id + contract_id;
int res = face.AuthorizedDevice( uidStr, password, LoginActivity.this );
15. Device Activation 2
int fireflyInit(Context context, String uidStr, String password)
Function : Device activation;This interface is a temporary
interface for firefly, which can permanently activate the device.
This interface may be removed later.If the interface description is
not included in subsequent development documents, it has been
removed. The development documents are subject to the documents in
the open source Demo.
Parameters : uidStr : OEMID + contract Id
password : password
Returns 0 : Authentication succeeded
Example ：
String oem_id = "1000000000000001";//OEMID
String contract_id = "0001";//contract Id
String password = "0123456789abcdef0123456789abcdef"; //password
String uidStr = oem_id + contract_id;
int res =face.fireflyInit(LoginActivity.this, uidStr, password);
16. Device Activation 3
int AuthorizedDeviceUserPassword(String uidStr, String password,
Context context, String userPassword)
Function : Device activation，This interface is mainly used for the
activation method with user password.
Parameters : uidStr : OEMID + contract Id
password : password
userPassword:user password
Returns 0 : Authentication succeeded
Example ：
String oem_id ="1000000000000001";//OEMID
String contract_id ="0001";//contract Id
String password = "0123456789abcdef0123456789abcdef";//password
String userPassword ="012345678912";//user password;
String uidStr = oem_id+contract_id;
int res =face. AuthorizedDeviceUserPassword(uidStr,password,
LoginActivity.this,userPassword);
17. Get authentication activation status
int getAuthStatus()
Function: Get authentication activation status
Parameters: void
Returns 0 : activated
Example ：
int res = face.getAuthStatus();
18. Extracting facial features
int GetFeature( Image image, float[] feature, List faceinfos, int[]
res )
Function: Extract feature values of pictures in image,and get only
the characteristics of one person in the picture。
Parameters: image : Image object containing a face image
feature : Stores the facial feature information of the detection
results, and returns an empty array without a face
faceinfos : FaceInfo checklist. FaceInfo is an object used to
save the results of operations
res : Face recognition results.The length of res is always 1.If
no face is recognized in the picture,res[0] return
ERROR_INVALID_PARAM.
Returns SUCCESS : Feature extraction successful
ERROR_FAILURE : No face information was obtained
Example ：
float[] feature = new float[512];
int[] ret = new int[1];
byte[] tmpPos = new byte[1024]; //Used to store location information
ret = face.GetFeature( image, feature, tmpPos, res );
if( ret == SUCCESS ){
//to do
}
19. Extraction of face features (based on face coordinate information)
int GetFeature( Image image, FaceInfo detectInfo, float[] feature,
int[] res )
Function: Extract feature values of pictures in image,and get only
the characteristics of one person in the picture。
Parameters: image : Image object containing a face image
detectInfo : Face information detected for facial feature
extraction
feature : Stores the facial feature information of the detection
results, and returns an empty array without a face
res : Face recognition results.The length of res is always 1.If
no face is recognized in the picture,res[0] return
ERROR_INVALID_PARAM.
Returns SUCCESS : Feature extraction successful
ERROR_FAILURE : No face information was obtained
Example ：
float[] feature = new float[512];
int[] ret = new int[1];
float[] detectinfo = new float[]{ x0, y0, x1, y1, landmarkx0, landmarky0,
landmarkx1, landmarky1, landmarkx2, landmarky2,
landmarkx3, landmarky3, landmarkx4, landmarky4 }
byte[] tmpPos = new byte[1024]; //Used to store location information
ret = face.GetFeature( image, detectinfo, feature, res );
if( ret == SUCCESS ){
//to do
}
20. Extracting facial features (based on picture files)
float[] GetFeature(String path, List faceinfos)
Function: Get the facial feature value data in the image according
to the path of the incoming image file.
Parameters: path :The absolute path of the face image file.
faceinfos : FaceInfo checklist. FaceInfo is an object used to
save the results of operations
Returns Float[] : Face feature value array
Example ：
int ret = this.FaceGetFeatureFromAddr(addr, feature, mFaceInfos, policy);
if (ret == -1) {
return null;
} else {
faceInfos.addAll(Arrays.asList(this.mFaceInfos).subList(0,ret));
return this.feature;
}
21. Extract key points of the face
int GetLandmark ( Image image, float[] landmark, int[] res )
Function: Get face key point coordinate information
Parameters: Image : Face picture, a picture used to extract key
point information of the face, only extract key point information
of a person
Landmark : Used to store the coordinates of 5 key points, which
are left eye, right eye, nose, left side of lips, right side of
lips
res : Face recognition results.The length of res is always 1.If
no face is recognized in the picture,res[0] return
ERROR_INVALID_PARAM.
Returns SUCCESS : Successfully obtain coordinate information
of face keypoints ERROR_FAILURE : No facial keypoint
information was obtained
Example ：
float[] landmark = new float[10];
int[] ret = new int[1];
ret = face.GetLandmark( image, landmark, res);
if( ret == SUCCESS ){
}
22. Face quality
FaceInfo getQuality(long matAddrframe)
Function: Get the face information of the largest face in the image
。
Parameters: matAddrframe : Image address stored in Mat object
Returns FaceInfo : Used to store face information in pictures
Example ：
Faceinfo faceinfo=new Faceinfo();
faceinfo=face.getQuality(matAddrframe);
if(faceinfo!=null){
}
23. Parameters Setting
bool SetParameter( const String[] name, float value[] )
Function: Set the entered Parameter key and value
Parameters: char[] name : Parameters key array
a : Internal Parameters, set according to the example, please do
not modify.
b : Internal Parameters, set according to the example, please do
not modify.
c : Internal Parameters, set according to the example, please do
not modify.
d : Internal Parameters, set according to the example, please do
not modify.
factor : Detect face magnification. Internal Parameters, set
according to the example, please do not modify.
min_size : Minimum face frame size, recommended range:32-80
faceclarity : Photo sharpness threshold, recommended
range:200-400
perfoptimize : Whether to optimize the effect , recommended
range: 0 or 1
livenessdetect : Whether live detection , recommended range:0 or
1
gray2colorscale : Binocular live detection ratio , recommended
range: 0.1-0.5
frame_num : Number of frames,recommended range:20-40
quality_thresh : Picture quality threshold,recommended
range:0.7-0.8
mode : Operating mode :0-> Entrance 1-> Access control
facenum : Detects the maximum number of faces and supports
detection of up to 3 faces and 1 face.recommended range:1-3
value[] : Parameters key array
Returns: Whether the parameters are set successfully
Example ：
String[] name = { "a", "b","c", "d", "factor", "min_size", "clarity", "perfoptimize",
"livenessdetect", "gray2colorscale", "frame_num", "qualit_thresh",
"mode", "facenum" };
double[] value = {0.9, 0.9, 0.9, 0.715, 0.6, 64, 400, 1, 0, 0.5, 20, 0.8, 1, 1 };
face.SetParameter( name, value );
24. Parameters Setting(Mode for modifying parameter length as needed)
bool SetParameters( String[] name, float value[] )
Function: Set the entered Parameter key and value
Parameters: char[] name : Parameters key array(length>=1),See
details in 23.
value[] : Parameters value array(length>=1)
Returns: Whether the parameters are set successfully
Example ：
String[] name = { "perfoptimize", "livenessdetect", "frame_num", "quality_thresh",
"mode", "facenum" };
double[] value = { 1, 0, 20, 0.8, 1, 1 };
face.SetParameter( name, value );
25. Get version information
public String GetVersion()
Function: Get information about the current SDK version
Parameters void
Returns: Return current version information
Example ：
Face.GetVersion();
26. Get Facelib Version
public String GetFacelibVersion()
Function: Get Facelib Version
Parameters: void
Returns: Return Facelib version information
Example ：
Face.GetFacelibVersion();
27. Open the face database
int OpenDB()
Function: Using face database, internal face database can achieve
1-to-N efficient and fast query
Parameters: void
Returns Execution succeed return SUCCESS Execution
failed return ERROR_FAILURE
Example ：
if(face.OpenDB() == SUCCESS){
// TODO
}
28. Registered face
int AddDB( float[] feature, string name )
Function: Registered face to database
Parameters: feature : Facial features
name : Registered name
Returns Execution succeed return SUCCESS Execution
failed return ERROR_FAILURE
Example ：
String name= "test";
int[] res=new int[];
if( Face.GetFeature( image, feature, tmpPos, res ) == SUCCESS ){
Face.AddDB ( feature, name );
}
29. Save face
int SaveDB()
Function: Save the results of adding, modifying, and deleting faces
to a database file；If it is not called，the modification is
invalid after exiting the program.
Parameters: void
Returns Execution succeed return SUCCESS Execution
failed return ERROR_FAILURE
Example ：
Face.AddDB(feature,name);
...
//After adding faces, make sure to execute Face.SaveDB () before restarting the device;
Face.SaveDB();
30. Delete face
int DelDB(string name)
Function: Delete face
Parameters: name : Registered name
Returns Execution succeed return SUCCESS Execution
failed return ERROR_FAILURE
Example ：
String name= "test";
Face.DelDB (name);
31. Delete all registered faces
int DelAllDB()
Function: Delete all registered faces
Parameters: void
Returns Execution succeed return SUCCESS Execution
failed return ERROR_FAILURE
Example ：
Face.DelAllDB ();
32. Querying Face
String QueryDB( float[] feature, float [] score )
Function: Returns the data that is closest to the input facial
features.
Parameters: feature : Facial features
score : Store the similarity score of the queried face data and
the input face data
Returns Execution succeed return registered name
Execution failed return unknown
Example ：
float[] score = new float[1];
String name = Face.QueryDB( feature, score );
if( score > thresh_hold ){
// TODO
}
33. Close the face database
int CloseDB()
Function: Close the face database
Parameters: void
Returns Execution succeed return SUCCESS Execution
failed return ERROR_FAILURE
Example ：
if( Face.CloseDB() == SUCCESS ){
// TODO
}
34. Load Quick Compare Function
int FastQueryInit()
Function: Load Quick Compare Function
Parameters: void
Returns Execution succeed return SUCCESS Execution
failed return ERROR_FAILURE
Example ：
if(Face.FastQueryInit () == SUCCESS){
// TODO
}
35. Refresh fast match buffer
int FastQueryFlush(float [] data, int num)
Function: Refresh fast match buffer
Parameters: Data : External feature buffer
Num : Number of features
Returns Execution succeed return SUCCESS Execution
failed return ERROR_FAILURE
Example ：
if(Face.FastQueryFlush(data,num) == SUCCESS){
// TODO
}
36. Quick Query
int FastQuery(float[] data, float[] feature, float[] scores, int
num)
Function: Quick query
Parameters: Data : External feature buffer
feature : The feature to query
scores:Similarity score
num : Number of features
Returns Execution succeed return SUCCESS Execution
failed return ERROR_FAILURE
Example ：
if(Face.FastQuery(data,feature,num) == SUCCESS){
// TODO
}
37. Get face attributes
int GetFaceAttr( Image image, FaceInfo data, FaceAttribute
face_attr, int *res )
Function: After Detect is executed, the face attributes including
age, gender and expression are obtained by detecting the acquired
face position and keypoint information.
Parameters: image : Image object containing a face image
data : Detected face position and face keypoint information
face_attr : Store calculated face attributes
res : Face recognition results.The length of res is always 1.If
no face is recognized in the picture,res[0] return
ERROR_INVALID_PARAM.
Returns SUCCESS : Obtain face attributes succeed
ERROR_FAILURE : Obtain face attributes failed
Example ：
if( face.GetFaceAttr( Image, data, attr, res ) == SUCCESS ){
// TODO
}
38. Release face recognition resources
public void Destroy()
Function: Free resources allocated when initializing and setting
Parameters
Parameters: void
Returns void
Example ：
Face.Destroy();
39. Sample code
Initialize the binocular camera face recognition demo.
public class MainActivity extends Activity implements CvCameraViewListener2 {
private FaceAPP face= FaceAPP.GetInstance(); //face as member variable
.........
@Override
protected void onCreate(Bundle savedInstanceState) {
.........
String[] name={"a","b","c","d","factor","min_size","clarity","perf-optimize","liveness-detect","gray2color-scale"};
double[] value={0.9,0.9,0.9,0.715,0.6,64,400,1,0,0.5};
face.SetParameter(name,value);
mainLoop = new Thread() { //Face detection needs to run on a child thread
public void run() {
.........
float[] feature=new float[512];
byte[] tmpPos = new byte[1024];// used to store position information
switch (mixController.curState){
......
case mixController. STATE_IDLE :
FaceAPP.Image image= FaceAPP. GetInstance ().new Image();
image.matAddrframe=mRgbaFrame.getNativeObjAddr();
int[] res=new int[1];
int ret;
ret= face.GetFeature(image,feature,tmpPos,res);
if(ret== SUCCESS){
//to do Successfully obtained facial feature values
}
}
}
}
}