Question/Issue:
I’m currently doing a gesture recognition using an accelerometer, gyroscope and 4 potentiometers, I followed the data forwarder tutorial and used the arduino library edge impulse documentation
Data forwarder | Edge Impulse Documentation
Arduino library | Edge Impulse Documentation
I changed the code “Classifying data” from the first link and it is currently the following:
#define __STATIC_FORCEINLINE attribute((always_inline)) static inline
#define __SSAT(ARG1, ARG2)
extension
({
int32_t __RES, __ARG1 = (ARG1);
__ASM volatile (“ssat %0, %1, %2” : “=r” (__RES) : “I” (ARG2), “r” (__ARG1) : “cc” );
__RES;
})
#define EIDSP_USE_CMSIS_DSP 1
#define EIDSP_LOAD_CMSIS_DSP_SOURCES 1#include <tcc_duti_inferencing.h>
#include <Arduino_LSM6DS3.h>#define CONVERT_G_TO_MS2 9.80665f
#define FREQUENCY_HZ EI_CLASSIFIER_FREQUENCY
#define INTERVAL_MS (1000 / (FREQUENCY_HZ + 1))// Definição dos pinos dos potenciômetros
#define POT1_PIN A0
#define POT2_PIN A1
#define POT3_PIN A2
#define POT4_PIN A3static unsigned long last_interval_ms = 0;
// Buffer para armazenar os dados coletados
float features[EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE];
size_t feature_ix = 0;int qtddados = 0;
void setup() {
Serial.begin(115200);
Serial.println(“Started”);// Inicialização do sensor IMU if (!IMU.begin()) { Serial.println("Failed to initialize IMU!"); while (1); } delay(5000);}
void loop() {
unsigned long start_time = millis(); // Marca o início do loopfloat ax, ay, az; // Valores do acelerômetro float gx, gy, gz; // Valores do giroscópio int p1, p2, p3, p4; // Valores dos potenciômetros if (millis() > last_interval_ms + INTERVAL_MS) { last_interval_ms = millis(); // Leitura do acelerômetro IMU.readAcceleration(ax, ay, az); features[feature_ix++] = ax * CONVERT_G_TO_MS2; features[feature_ix++] = ay * CONVERT_G_TO_MS2; features[feature_ix++] = az * CONVERT_G_TO_MS2; // Leitura do giroscópio IMU.readGyroscope(gx, gy, gz); features[feature_ix++] = gx; features[feature_ix++] = gy; features[feature_ix++] = gz; // Leitura dos potenciômetros p1 = analogRead(POT1_PIN); p2 = analogRead(POT2_PIN); p3 = analogRead(POT3_PIN); p4 = analogRead(POT4_PIN); features[feature_ix++] = p1; features[feature_ix++] = p2; features[feature_ix++] = p3; features[feature_ix++] = p4; qtddados++; Serial.print("Leu os dados: "); Serial.println(qtddados); Serial.print("feature_ix: "); Serial.println(feature_ix); // Quando o buffer estiver cheio, processa a classificação if (feature_ix == EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE) { ei_impulse_result_t result; Serial.println("Processando"); // Criação do sinal a partir do buffer signal_t signal; numpy::signal_from_buffer(features, EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE, &signal); Serial.println("Sinal a partir do buffer criado"); // Executa o classificador EI_IMPULSE_ERROR res = run_classifier(&signal, &result, false); Serial.println("Classificador executado"); if (res != 0) return; Serial.println("Sem erros"); // Determina a classe com maior probabilidade float max_value = 0.0f; const char* max_label = ""; for (size_t ix = 0; ix < EI_CLASSIFIER_LABEL_COUNT; ix++) { Serial.println("Inicio FOR"); if (result.classification[ix].value > max_value) { Serial.println("Inicio IF"); max_value = result.classification[ix].value; max_label = result.classification[ix].label; } } // Imprime a classe com maior probabilidade ei_printf("Class: %s (Confidence: %d%%)\n", max_label, static_cast<int>(max_value * 100)); // Reinicia o buffer feature_ix = 0; qtddados = 0; } unsigned long end_time = millis(); // Marca o final do loop Serial.print("Tempo gasto no loop: "); Serial.print(end_time - start_time); Serial.println(" ms"); }}
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); }}
Basically what happens is, it collects the data from all of my sensors and potentiometers (totaling 2450 different data) and runs the loop one time correctly, no errors occur and the class most probable is printed in the serial monitor, however when running the loop a second time it collects the data as it should and has the same amount of data as the first time (2450) but when the code gets to the run_classifier function it returns the error -1004, I’ve read in the forums that the error is because one of the buffers passed into the function is the wrong size, but I don’t know how to solve this.
Project ID:
590102