João Vitor Yukio Bordin Yamashita
Published © LGPL

Gesture Classification with Esp32 and TinyML

Classificate gestures using an Esp32, MPU6050 and Edge Impulse.

BeginnerFull instructions provided2,989

Things used in this project

Hardware components

thingSoC ESP32 WiFi Module
thingSoC ESP32 WiFi Module
×1
6 DOF Sensor - MPU6050
DFRobot 6 DOF Sensor - MPU6050
×1
RGB Diffused Common Cathode
RGB Diffused Common Cathode
×1
Jumper wires (generic)
Jumper wires (generic)
×1

Software apps and online services

Edge Impulse Studio
Edge Impulse Studio
Arduino IDE
Arduino IDE

Story

Read more

Schematics

MPU6050 connection

Source:
https://randomnerdtutorials.com/esp32-mpu-6050-accelerometer-gyroscope-arduino/

Code

Inference

C/C++
Inferencing data using Arduino IDE and Esp32
#include <Adafruit_MPU6050.h>
#include <Adafruit_Sensor.h>
#include <Wire.h>
#include <gesture_class_ESP32_dataForwarder_inferencing.h>

#define FREQUENCY_HZ        60
#define INTERVAL_MS         (1000 / (FREQUENCY_HZ + 1))

// objeto da classe Adafruit_MPU6050
Adafruit_MPU6050 mpu;

float features[EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE];
size_t feature_ix = 0;

static unsigned long last_interval_ms = 0;


void setup() {
  Serial.begin(115200);

  if (!mpu.begin()) {
    Serial.println("Failed to find MPU6050 chip");
    while (1) {
      delay(10);
    }
  }
  Serial.println("MPU6050 Found!");

  mpu.setAccelerometerRange(MPU6050_RANGE_8_G);
  Serial.print("Accelerometer range set to: ");
  switch (mpu.getAccelerometerRange()) {
    case MPU6050_RANGE_2_G:
      Serial.println("+-2G");
      break;
    case MPU6050_RANGE_4_G:
      Serial.println("+-4G");
      break;
    case MPU6050_RANGE_8_G:
      Serial.println("+-8G");
      break;
    case MPU6050_RANGE_16_G:
      Serial.println("+-16G");
      break;
  }
  mpu.setGyroRange(MPU6050_RANGE_500_DEG);
  Serial.print("Gyro range set to: ");
  switch (mpu.getGyroRange()) {
    case MPU6050_RANGE_250_DEG:
      Serial.println("+- 250 deg/s");
      break;
    case MPU6050_RANGE_500_DEG:
      Serial.println("+- 500 deg/s");
      break;
    case MPU6050_RANGE_1000_DEG:
      Serial.println("+- 1000 deg/s");
      break;
    case MPU6050_RANGE_2000_DEG:
      Serial.println("+- 2000 deg/s");
      break;
  }

  mpu.setFilterBandwidth(MPU6050_BAND_21_HZ);
  Serial.print("Filter bandwidth set to: ");
  switch (mpu.getFilterBandwidth()) {
    case MPU6050_BAND_260_HZ:
      Serial.println("260 Hz");
      break;
    case MPU6050_BAND_184_HZ:
      Serial.println("184 Hz");
      break;
    case MPU6050_BAND_94_HZ:
      Serial.println("94 Hz");
      break;
    case MPU6050_BAND_44_HZ:
      Serial.println("44 Hz");
      break;
    case MPU6050_BAND_21_HZ:
      Serial.println("21 Hz");
      break;
    case MPU6050_BAND_10_HZ:
      Serial.println("10 Hz");
      break;
    case MPU6050_BAND_5_HZ:
      Serial.println("5 Hz");
      break;
  }

  Serial.println("");
  delay(100);

  Serial.print("Features: ");
  Serial.println(EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE);
  Serial.print("Label count: ");
  Serial.println(EI_CLASSIFIER_LABEL_COUNT);

}

void loop() {
  sensors_event_t a, g, temp;

  if (millis() > last_interval_ms + INTERVAL_MS) {
    last_interval_ms = millis();

    mpu.getEvent(&a, &g, &temp);

    features[feature_ix++] = a.acceleration.x;
    features[feature_ix++] = a.acceleration.y;
    features[feature_ix++] = a.acceleration.z;

    if (feature_ix == EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE) {
      Serial.println("Running the inference...");
      signal_t signal;
      ei_impulse_result_t result;
      int err = numpy::signal_from_buffer(features, EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE, &signal);
      if (err != 0) {
        ei_printf("Failed to create signal from buffer (%d)\n", err);
        return;
      }

      EI_IMPULSE_ERROR res = run_classifier(&signal, &result, true);

      if (res != 0) return;

      ei_printf("Predictions ");
      ei_printf("(DSP: %d ms., Classification: %d ms.)",
                result.timing.dsp, result.timing.classification);
      ei_printf(": \n");

      for (size_t ix = 0; ix < EI_CLASSIFIER_LABEL_COUNT; ix++) {
        ei_printf("    %s: %.5f\n", result.classification[ix].label, result.classification[ix].value);
      }
      feature_ix = 0;
    }

  }
}

void ei_printf(const char *format, ...) {
  static char print_buf[1024] = { 0 };

  va_list args;
  va_start(args, format);
  int r = vsnprintf(print_buf, sizeof(print_buf), format, args);
  va_end(args);

  if (r > 0) {
    Serial.write(print_buf);
  }
}

Data Acquisition

C/C++
#include <Adafruit_MPU6050.h>
#include <Adafruit_Sensor.h>
#include <Wire.h>

#define FREQUENCY_HZ        60
#define INTERVAL_MS         (1000 / (FREQUENCY_HZ + 1))

// objeto da classe Adafruit_MPU6050
Adafruit_MPU6050 mpu;

static unsigned long last_interval_ms = 0;

void setup() {
  Serial.begin(115200);
  Serial.println("Classificador de gestos com TinyML");

  // Try to initialize!
  if (!mpu.begin()) {
    Serial.println("Failed to find MPU6050 chip");
    while (1) {
      delay(10);
    }
  }
  Serial.println("MPU6050 Found!");

  mpu.setAccelerometerRange(MPU6050_RANGE_8_G);
  Serial.print("Accelerometer range set to: ");
  switch (mpu.getAccelerometerRange()) {
    case MPU6050_RANGE_2_G:
      Serial.println("+-2G");
      break;
    case MPU6050_RANGE_4_G:
      Serial.println("+-4G");
      break;
    case MPU6050_RANGE_8_G:
      Serial.println("+-8G");
      break;
    case MPU6050_RANGE_16_G:
      Serial.println("+-16G");
      break;
  }
  mpu.setGyroRange(MPU6050_RANGE_500_DEG);
  Serial.print("Gyro range set to: ");
  switch (mpu.getGyroRange()) {
    case MPU6050_RANGE_250_DEG:
      Serial.println("+- 250 deg/s");
      break;
    case MPU6050_RANGE_500_DEG:
      Serial.println("+- 500 deg/s");
      break;
    case MPU6050_RANGE_1000_DEG:
      Serial.println("+- 1000 deg/s");
      break;
    case MPU6050_RANGE_2000_DEG:
      Serial.println("+- 2000 deg/s");
      break;
  }

  mpu.setFilterBandwidth(MPU6050_BAND_21_HZ);
  Serial.print("Filter bandwidth set to: ");
  switch (mpu.getFilterBandwidth()) {
    case MPU6050_BAND_260_HZ:
      Serial.println("260 Hz");
      break;
    case MPU6050_BAND_184_HZ:
      Serial.println("184 Hz");
      break;
    case MPU6050_BAND_94_HZ:
      Serial.println("94 Hz");
      break;
    case MPU6050_BAND_44_HZ:
      Serial.println("44 Hz");
      break;
    case MPU6050_BAND_21_HZ:
      Serial.println("21 Hz");
      break;
    case MPU6050_BAND_10_HZ:
      Serial.println("10 Hz");
      break;
    case MPU6050_BAND_5_HZ:
      Serial.println("5 Hz");
      break;
  }

  Serial.println("");
  delay(100);
}

void loop() {

  sensors_event_t a, g, temp;

  if (millis() > last_interval_ms + INTERVAL_MS) {
    last_interval_ms = millis();

    mpu.getEvent(&a, &g, &temp);

    Serial.print(a.acceleration.x);
    Serial.print(",");
    Serial.print(a.acceleration.y);
    Serial.print(",");
    Serial.println(a.acceleration.z);

  }

}

TinyML Gesture recognition

Credits

João Vitor Yukio Bordin Yamashita

João Vitor Yukio Bordin Yamashita

3 projects • 1 follower

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