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added examples for Edge Impulse microphone inference and Blynk integration
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‎examples/WioTerminal_EI_Microphone_Inference/WioTerminal_EI_Microphone_Inference.ino‎

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/*
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An example sketch for Edge Impulse trained model inference for Audio scene classification
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Copyright (c) 2021 Seeed technology co., ltd.
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Author : Dmitry Maslov
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Create Time : January 2021
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Change Log :
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The MIT License (MIT)
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in
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all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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THE SOFTWARE.
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*/
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// If your target is limited in memory remove this macro to save 10K RAM
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#define EIDSP_QUANTIZE_FILTERBANK 0
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/* Includes ---------------------------------------------------------------- */
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#include <audio_scene_mfe_conv1d_v1_inference.h>
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/** Audio buffers, pointers and selectors */
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typedef struct {
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int16_t *buffer;
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uint8_t buf_ready;
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uint32_t buf_count;
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uint32_t n_samples;
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} inference_t;
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static inference_t inference;
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static signed short sampleBuffer[2048];
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unsigned int sampling_period_us = round(600000 * (1.0 / 16000));
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static bool debug_nn = false; // Set this to true to see e.g. features generated from the raw signal
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/**
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* @brief Arduino setup function
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*/
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void setup()
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{
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// put your setup code here, to run once:
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Serial.begin(115200);
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Serial.println("Edge Impulse Inferencing Demo");
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// summary of inferencing settings (from model_metadata.h)
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ei_printf("Inferencing settings:\n");
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ei_printf("\tInterval: %.2f ms.\n", (float)EI_CLASSIFIER_INTERVAL_MS);
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ei_printf("\tFrame size: %d\n", EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE);
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ei_printf("\tSample length: %d ms.\n", EI_CLASSIFIER_RAW_SAMPLE_COUNT / 16);
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ei_printf("\tNo. of classes: %d\n", sizeof(ei_classifier_inferencing_categories) / sizeof(ei_classifier_inferencing_categories[0]));
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if (microphone_inference_start(EI_CLASSIFIER_RAW_SAMPLE_COUNT) == false) {
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ei_printf("ERR: Failed to setup audio sampling\r\n");
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return;
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}
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}
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/**
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* @brief Arduino main function. Runs the inferencing loop.
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*/
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void loop()
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{
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ei_printf("Recording...\n");
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bool m = microphone_inference_record();
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if (!m) {
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ei_printf("ERR: Failed to record audio...\n");
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return;
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}
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ei_printf("Recording done\n");
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signal_t signal;
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signal.total_length = EI_CLASSIFIER_RAW_SAMPLE_COUNT;
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signal.get_data = &microphone_audio_signal_get_data;
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ei_impulse_result_t result = { 0 };
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EI_IMPULSE_ERROR r = run_classifier(&signal, &result, debug_nn);
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if (r != EI_IMPULSE_OK) {
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ei_printf("ERR: Failed to run classifier (%d)\n", r);
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return;
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}
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// print the predictions
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ei_printf("Predictions ");
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ei_printf("(DSP: %d ms., Classification: %d ms., Anomaly: %d ms.)",
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result.timing.dsp, result.timing.classification, result.timing.anomaly);
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ei_printf(": \n");
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for (size_t ix = 0; ix < EI_CLASSIFIER_LABEL_COUNT; ix++) {
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ei_printf(" %s: %.5f\n", result.classification[ix].label, result.classification[ix].value);
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}
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#if EI_CLASSIFIER_HAS_ANOMALY == 1
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ei_printf(" anomaly score: %.3f\n", result.anomaly);
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#endif
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}
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/**
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* @brief Printf function uses vsnprintf and output using Arduino Serial
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*
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* @param[in] format Variable argument list
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*/
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void ei_printf(const char *format, ...) {
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static char print_buf[1024] = { 0 };
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va_list args;
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va_start(args, format);
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int r = vsnprintf(print_buf, sizeof(print_buf), format, args);
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va_end(args);
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if (r > 0) {
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Serial.write(print_buf);
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}
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}
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/**
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* @brief Init inferencing struct and setup/start PDM
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*
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* @param[in] n_samples The n samples
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*
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* @return { description_of_the_return_value }
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*/
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static bool microphone_inference_start(uint32_t n_samples)
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{
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inference.buffer = (int16_t *)malloc(n_samples * sizeof(int16_t));
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if(inference.buffer == NULL) {
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return false;
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}
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inference.buf_count = 0;
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inference.n_samples = n_samples;
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inference.buf_ready = 0;
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pinMode(WIO_MIC, INPUT);
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return true;
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}
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/**
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* @brief Wait on new data
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*
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* @return True when finished
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*/
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static bool microphone_inference_record(void)
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{
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inference.buf_ready = 0;
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inference.buf_count = 0;
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if (inference.buf_ready == 0) {
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for(int i = 0; i < 8001; i++) {
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inference.buffer[inference.buf_count++] = map(analogRead(WIO_MIC), 0, 1023, -32768, 32767);
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delayMicroseconds(sampling_period_us);
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if(inference.buf_count >= inference.n_samples) {
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inference.buf_count = 0;
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inference.buf_ready = 1;
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break;
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}
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}
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}
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return true;
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}
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/**
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* Get raw audio signal data
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*/
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static int microphone_audio_signal_get_data(size_t offset, size_t length, float *out_ptr)
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{
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numpy::int16_to_float(&inference.buffer[offset], out_ptr, length);
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return 0;
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}
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/**
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* @brief Stop PDM and release buffers
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*/
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static void microphone_inference_end(void)
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{
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free(inference.buffer);
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}
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#if !defined(EI_CLASSIFIER_SENSOR) || EI_CLASSIFIER_SENSOR != EI_CLASSIFIER_SENSOR_MICROPHONE
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#error "Invalid model for current sensor."
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#endif

‎examples/WioTerminal_EI_Microphone_Inference_Blynk/WioTerminal_EI_Microphone_Inference_Blynk.ino‎

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/*
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An example sketch for Edge Impulse trained model inference for Audio scene classification and Blynk push notifications
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Copyright (c) 2021 Seeed technology co., ltd.
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Author : Dmitry Maslov
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Create Time : January 2021
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Change Log :
8+
9+
The MIT License (MIT)
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11+
Permission is hereby granted, free of charge, to any person obtaining a copy
12+
of this software and associated documentation files (the "Software"), to deal
13+
in the Software without restriction, including without limitation the rights
14+
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
15+
copies of the Software, and to permit persons to whom the Software is
16+
furnished to do so, subject to the following conditions:
17+
18+
The above copyright notice and this permission notice shall be included in
19+
all copies or substantial portions of the Software.
20+
21+
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
22+
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
23+
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
24+
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
25+
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
26+
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
27+
THE SOFTWARE.
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*/
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// If your target is limited in memory remove this macro to save 10K RAM
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#define EIDSP_QUANTIZE_FILTERBANK 0
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#define BLYNK_PRINT Serial
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/* Includes ---------------------------------------------------------------- */
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#include <audio_scene_mfe_conv1d_v1_inference.h>
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#include <rpcWiFi.h>
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#include <WiFiClient.h>
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#include <BlynkSimpleWioTerminal.h>
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/** Audio buffers, pointers and selectors */
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typedef struct {
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int16_t *buffer;
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uint8_t buf_ready;
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uint32_t buf_count;
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uint32_t n_samples;
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} inference_t;
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static inference_t inference;
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static signed short sampleBuffer[2048];
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unsigned int sampling_period_us = round(600000 * (1.0 / 16000));
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static bool debug_nn = false; // Set this to true to see e.g. features generated from the raw signal
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char auth[] = "token";
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char ssid[] = "ssid";
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char pass[] = "password";
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void infer()
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{
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ei_printf("Recording...\n");
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bool m = microphone_inference_record();
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if (!m) {
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ei_printf("ERR: Failed to record audio...\n");
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return;
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}
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ei_printf("Recording done\n");
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signal_t signal;
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signal.total_length = EI_CLASSIFIER_RAW_SAMPLE_COUNT;
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signal.get_data = &microphone_audio_signal_get_data;
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ei_impulse_result_t result = { 0 };
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EI_IMPULSE_ERROR r = run_classifier(&signal, &result, debug_nn);
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if (r != EI_IMPULSE_OK) {
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ei_printf("ERR: Failed to run classifier (%d)\n", r);
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return;
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}
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// print the predictions
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ei_printf("Predictions ");
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ei_printf("(DSP: %d ms., Classification: %d ms., Anomaly: %d ms.)",
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result.timing.dsp, result.timing.classification, result.timing.anomaly);
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ei_printf(": \n");
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for (size_t ix = 0; ix < EI_CLASSIFIER_LABEL_COUNT; ix++) {
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ei_printf(" %s: %.5f\n", result.classification[ix].label, result.classification[ix].value);
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}
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if (result.classification[1].value > 0.6) { Blynk.notify("Dog is barking"); }
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if (result.classification[2].value > 0.6) { Blynk.notify("Glass breaking"); }
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if (result.classification[3].value > 0.6) { Blynk.notify("Shots fired"); }
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}
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void setup()
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{
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// put your setup code here, to run once:
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Serial.begin(115200);
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Blynk.begin(auth, ssid, pass);
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Serial.println("Edge Impulse Inferencing Demo");
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// summary of inferencing settings (from model_metadata.h)
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ei_printf("Inferencing settings:\n");
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ei_printf("\tInterval: %.2f ms.\n", (float)EI_CLASSIFIER_INTERVAL_MS);
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ei_printf("\tFrame size: %d\n", EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE);
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ei_printf("\tSample length: %d ms.\n", EI_CLASSIFIER_RAW_SAMPLE_COUNT / 16);
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ei_printf("\tNo. of classes: %d\n", sizeof(ei_classifier_inferencing_categories) / sizeof(ei_classifier_inferencing_categories[0]));
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if (microphone_inference_start(EI_CLASSIFIER_RAW_SAMPLE_COUNT) == false) {
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ei_printf("ERR: Failed to setup audio sampling\r\n");
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return;
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}
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}
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void loop()
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{
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Blynk.run();
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infer();
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}
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void ei_printf(const char *format, ...) {
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static char print_buf[1024] = { 0 };
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va_list args;
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va_start(args, format);
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int r = vsnprintf(print_buf, sizeof(print_buf), format, args);
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va_end(args);
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if (r > 0) {
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Serial.write(print_buf);
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}
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}
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static bool microphone_inference_start(uint32_t n_samples)
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{
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inference.buffer = (int16_t *)malloc(n_samples * sizeof(int16_t));
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if(inference.buffer == NULL) {
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return false;
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}
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inference.buf_count = 0;
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inference.n_samples = n_samples;
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inference.buf_ready = 0;
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pinMode(WIO_MIC, INPUT);
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return true;
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}
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static bool microphone_inference_record(void)
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{
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inference.buf_ready = 0;
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inference.buf_count = 0;
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if (inference.buf_ready == 0) {
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for(int i = 0; i < 8001; i++) {
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inference.buffer[inference.buf_count++] = map(analogRead(WIO_MIC), 0, 1023, -32768, 32767);
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delayMicroseconds(sampling_period_us);
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if(inference.buf_count >= inference.n_samples) {
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inference.buf_count = 0;
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inference.buf_ready = 1;
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break;
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}
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}
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}
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while(inference.buf_ready == 0) {
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delay(10);
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}
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return true;
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}
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static int microphone_audio_signal_get_data(size_t offset, size_t length, float *out_ptr)
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{
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numpy::int16_to_float(&inference.buffer[offset], out_ptr, length);
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return 0;
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}
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static void microphone_inference_end(void)
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{
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free(inference.buffer);
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}

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