4.7 Face Recognition

4.7.1 Algorithm

It detects and recognizes human face in the image. Users can train to store or delete facial data by the function button. Sengo2 can store 15 faces at most.

4.7.2 Classification Label

Sengo2 defines 17 classification labels for human faces:

Label value	Meaning	Label value	Meaning
0	New face	1-15	Classification number for stored faces
200	Face wearing a mask

New face (label value 0):

Face wearing a mask (label value 200):

Stored face (label value 1-15):

4.7.3 Save Data

After enabling the face recognition algorithm, point the camera at the face, press the function button for 5 seconds and then release it. Sengo2 will start recording the face, and the current face data will be stored and assigned an ID number.

The smallest number among the currently available numbers will be assigned to the label value. If there are no vacant numbers, Sengo2 will prompt a storage failure.

4.7.4 Delete Data

After storing, press the function button for about 10 seconds and then release it to delete the data just stored. Press it again for 10 seconds, and all the stored faces will be cleared. If no face has been stored after enabling the algorithm, all storage of faces will be directly cleared when you press the function button for 10 seconds.

4.7.5 Returned Values

When the controller acquires the recognition result, the algorithm will return the followings:

Parameter	Definition
kXValue	Face central coordinate x
kYValue	Face central coordinate y
kWidthValue	Face width w
kHeightValue	Face height h
kLabel	Face label value

Code:

    // Traverse all the detected faces
    for (int i = 1; i <= face_count; ++i) {
      // Obtain the coordinate and size of the face in the image
      int face_x = sengo.GetValue(VISION_TYPE, kXValue, i);      // Face central coordinate x
      int face_y = sengo.GetValue(VISION_TYPE, kYValue, i);      // Face central coordinate y
      int face_width = sengo.GetValue(VISION_TYPE, kWidthValue, i);  // Face width
      int face_height = sengo.GetValue(VISION_TYPE, kHeightValue, i); // Face height
      
      // Obtain the face label (usually representing the face ID in face detection, used to track different people)
      int face_id = sengo.GetValue(VISION_TYPE, kLabel, i);
      
      // Print the detailed information of the face
      Serial.print("  Face #");
      Serial.print(i);
      Serial.print(": ");
      Serial.print("Position=(");
      Serial.print(face_x);
      Serial.print(",");
      Serial.print(face_y);
      Serial.print("), Size=");
      Serial.print(face_width);
      Serial.print("x");
      Serial.print(face_height);
      Serial.print(", ID=");
      Serial.println(face_id);
      
    }

4.7.6 Tips of Face Recognition Algorithm

When the ambient light is sufficient, the complete face is directly facing the camera and occupies a large field of view, the module can recognize it much better.
When wearing glasses or covered by hair, the human face may not be detected completely.

4.7.7 Test Code

#include <Arduino.h>          // Arduino core library
#include <Sentry.h>           // Sentry machine vision sensor library

// Create an alias Sengo for the Sengo2 type to simplify subsequent usage
typedef Sengo2 Sengo;

// Communication method (currently enabled I2C).
#define SENGO_I2C             
// #define SENGO_UART         // UART serial communication solution (annotated as disabled)

// Include the corresponding library according to the selected communication mode
#ifdef SENGO_I2C
#include <Wire.h>             // Libraries required for I2C communication
#endif

#ifdef SENGO_UART
#include <SoftwareSerial.h>   // Soft serial library
#define TX_PIN 11  // Customize the TX pin
#define RX_PIN 10  // Customize the RX pin
SoftwareSerial mySerial(RX_PIN, TX_PIN);  // Create a soft serial port object
#endif

// Define the visual processing type as a machine face recognition mode
#define VISION_TYPE Sengo::kVisionFace  

// Create a Sengo sensor object
Sengo sengo;

void setup() {
  sentry_err_t err = SENTRY_OK;  // Define the error state variable and initialize it to be error-free

  Serial.begin(9600);            // Initialize the serial port for debugging the output
  Serial.println("Waiting for sengo initialize...");  // Print the initialization prompt

// Initialize the sensor according to the selected communication mode
#ifdef SENGO_I2C
  Wire.begin();  // Initialize the I2C bus
  // Keep trying to connect until succeed
  // The yield() function allows ESP8266/ESP32 to handle background tasks during the waiting period
  while (SENTRY_OK != sengo.begin(&Wire)) { 
    yield();  
  }
#endif  // SENGO_I2C

#ifdef SENGO_UART
  mySerial.begin(9600);    // Initialize the soft serial port with a baud rate of 9600
  // Keep trying to connect until succeed
  while (SENTRY_OK != sengo.begin(&mySerial)) { 
    yield();  
  }
#endif  // SENGO_UART

  Serial.println("Sengo begin Success.");  // Print the successful initialization information of the sensor
  
  // Activate the machine face recognition function
  err = sengo.VisionBegin(VISION_TYPE);
  
  // Print the initialization result of f recognition
  Serial.print("sengo.VisionBegin(kVisionFace) ");
  if (err) {
    Serial.print("Error: 0x");    // If an error occurs, print the error prefix
  } else {
    Serial.print("Success: 0x");  // If successful, print the success prefix
  }
  Serial.println(err, HEX);       // Print the error code in hexadecimal format
  
  // Note: There is no additional configuration here. Use the default face detection parameters
  // Optional: Set parameters such as the minimum face size and detection angle
}

void loop() {
  // Obtain the number of detected faces (kStatus returns the total number of detected faces)
  int face_count = sengo.GetValue(VISION_TYPE, kStatus);
  
  // If at least one face is detected
  if (face_count > 0) {
    // Print the total number of detected faces
    Serial.print("Totally ");
    Serial.print(face_count);
    Serial.println(" faces detected");
    
    // Traverse all the detected faces
    for (int i = 1; i <= face_count; ++i) {
      // Obtain the coordinate and size of the fa in the image
      int face_x = sengo.GetValue(VISION_TYPE, kXValue, i);      // Face central coordinate x
      int face_y = sengo.GetValue(VISION_TYPE, kYValue, i);      // Face central coordinate y
      int face_width = sengo.GetValue(VISION_TYPE, kWidthValue, i);  // Face width
      int face_height = sengo.GetValue(VISION_TYPE, kHeightValue, i); // Face height
      
      // Obtain the face label (usually representing the face ID in face detection, used to track different people)
      int face_id = sengo.GetValue(VISION_TYPE, kLabel, i);
      
      // Print the detailed information of the face
      Serial.print("  Face #");
      Serial.print(i);
      Serial.print(": ");
      Serial.print("Position=(");
      Serial.print(face_x);
      Serial.print(",");
      Serial.print(face_y);
      Serial.print("), Size=");
      Serial.print(face_width);
      Serial.print("x");
      Serial.print(face_height);
      Serial.print(", ID=");
      Serial.println(face_id);
      
    }
  }
  
  delay(200);
}

4.7.8 Test Result

After uploading the code, press and hold the function button for 5 seconds, and then the module will starts to learn and record the face on the screen. Wait for a while until the recording is completed. When encountering new faces or faces wearing masks, prompts will also be given on it.

4.7.9 Extension Gameplay

Concentration monitor

Game rule: When studying, the camera is pointed at you. If it detects that your face has left the its field of view (when you turn your head to do something else), it will emit a friendly prompt sound “beep beep”.
Practice: Program to continuously detect human faces. If no face is detected in several consecutive frames, it sounds a reminder audio from the connected voice module.