Question/Issue:
Failed to start PDM in arduino nano ble 33 sense board after downloaded & installed from library. Normally pdm works fine when i using with my library it does not work.
Project ID:
255155
Context/Use case:
/* Edge Impulse ingestion SDK
- Copyright (c) 2022 EdgeImpulse Inc.
- Licensed under the Apache License, Version 2.0 (the “License”);
- you may not use this file except in compliance with the License.
- You may obtain a copy of the License at
- http://www.apache.org/licenses/LICENSE-2.0
- Unless required by applicable law or agreed to in writing, software
- distributed under the License is distributed on an “AS IS” BASIS,
- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- See the License for the specific language governing permissions and
- limitations under the License.
*/
// If your target is limited in memory remove this macro to save 10K RAM
#define EIDSP_QUANTIZE_FILTERBANK 0
/**
- Define the number of slices per model window. E.g. a model window of 1000 ms
- with slices per model window set to 4. Results in a slice size of 250 ms.
- For more info: https://docs.edgeimpulse.com/docs/continuous-audio-sampling
*/
#define EI_CLASSIFIER_SLICES_PER_MODEL_WINDOW 4
/*
** NOTE: If you run into TFLite arena allocation issue.
**
** This may be due to may dynamic memory fragmentation.
** Try defining “-DEI_CLASSIFIER_ALLOCATION_STATIC” in boards.local.txt (create
** if it doesn’t exist) and copy this file to
** <ARDUINO_CORE_INSTALL_PATH>/arduino/hardware/<mbed_core>/<core_version>/.
**
** See
** (https://support.arduino.cc/hc/en-us/articles/360012076960-Where-are-the-installed-cores-located-)
** to find where Arduino installs cores on your machine.
**
** If the problem persists then there’s not enough memory for this model and application.
*/
/* Includes ---------------------------------------------------------------- */
#include <PDM.h>
#include <parthiban-project-1_inferencing.h>
/** Audio buffers, pointers and selectors */
typedef struct {
signed short *buffers[2];
unsigned char buf_select;
unsigned char buf_ready;
unsigned int buf_count;
unsigned int n_samples;
} inference_t;
static inference_t inference;
static bool record_ready = false;
static signed short *sampleBuffer;
static bool debug_nn = false; // Set this to true to see e.g. features generated from the raw signal
static int print_results = -(EI_CLASSIFIER_SLICES_PER_MODEL_WINDOW);
/**
-
@brief Arduino setup function
*/
void setup()
{
// put your setup code here, to run once:
Serial.begin(115200);
// comment out the below line to cancel the wait for USB connection (needed for native USB)
while (!Serial);
Serial.println(“Edge Impulse Inferencing Demo”);// summary of inferencing settings (from model_metadata.h)
ei_printf(“Inferencing settings:\n”);
ei_printf(“\tInterval: %.2f ms.\n”, (float)EI_CLASSIFIER_INTERVAL_MS);
ei_printf(“\tFrame size: %d\n”, EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE);
ei_printf(“\tSample length: %d ms.\n”, EI_CLASSIFIER_RAW_SAMPLE_COUNT / 16);
ei_printf(“\tNo. of classes: %d\n”, sizeof(ei_classifier_inferencing_categories) /
sizeof(ei_classifier_inferencing_categories[0]));run_classifier_init();
if (microphone_inference_start(EI_CLASSIFIER_SLICE_SIZE) == false) {
ei_printf(“ERR: Could not allocate audio buffer (size %d), this could be due to the window length of your model\r\n”, EI_CLASSIFIER_RAW_SAMPLE_COUNT);
return;
}
}
/**
-
@brief Arduino main function. Runs the inferencing loop.
*/
void loop()
{
bool m = microphone_inference_record();
if (!m) {
ei_printf(“ERR: Failed to record audio…\n”);
return;
}signal_t signal;
signal.total_length = EI_CLASSIFIER_SLICE_SIZE;
signal.get_data = µphone_audio_signal_get_data;
ei_impulse_result_t result = {0};EI_IMPULSE_ERROR r = run_classifier_continuous(&signal, &result, debug_nn);
if (r != EI_IMPULSE_OK) {
ei_printf(“ERR: Failed to run classifier (%d)\n”, r);
return;
}if (++print_results >= (EI_CLASSIFIER_SLICES_PER_MODEL_WINDOW)) {
// print the predictions
ei_printf(“Predictions “);
ei_printf(”(DSP: %d ms., Classification: %d ms., Anomaly: %d ms.)”,
result.timing.dsp, result.timing.classification, result.timing.anomaly);
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);
}
#if EI_CLASSIFIER_HAS_ANOMALY == 1
ei_printf(" anomaly score: %.3f\n", result.anomaly);
#endifprint_results = 0;}
}
/**
- @brief PDM buffer full callback
-
Get data and call audio thread callback
*/
static void pdm_data_ready_inference_callback(void)
{
int bytesAvailable = PDM.available();
// read into the sample buffer
int bytesRead = PDM.read((char *)&sampleBuffer[0], bytesAvailable);
if (record_ready == true) {
for (int i = 0; i<bytesRead>> 1; i++) {
inference.buffers[inference.buf_select][inference.buf_count++] = sampleBuffer[i];
if (inference.buf_count >= inference.n_samples) {
inference.buf_select ^= 1;
inference.buf_count = 0;
inference.buf_ready = 1;
}
}
}
}
/**
-
@brief Init inferencing struct and setup/start PDM
-
@param[in] n_samples The n samples
-
@return { description_of_the_return_value }
*/
static bool microphone_inference_start(uint32_t n_samples)
{
inference.buffers[0] = (signed short *)malloc(n_samples * sizeof(signed short));if (inference.buffers[0] == NULL) {
return false;
}inference.buffers[1] = (signed short *)malloc(n_samples * sizeof(signed short));
if (inference.buffers[1] == NULL) {
free(inference.buffers[0]);
return false;
}sampleBuffer = (signed short *)malloc((n_samples >> 1) * sizeof(signed short));
if (sampleBuffer == NULL) {
free(inference.buffers[0]);
free(inference.buffers[1]);
return false;
}inference.buf_select = 0;
inference.buf_count = 0;
inference.n_samples = n_samples;
inference.buf_ready = 0;// configure the data receive callback
PDM.onReceive(&pdm_data_ready_inference_callback);PDM.setBufferSize((n_samples >> 1) * sizeof(int16_t));
// initialize PDM with:
// - one channel (mono mode)
// - a 16 kHz sample rate
if (!PDM.begin(1, EI_CLASSIFIER_FREQUENCY)) {
ei_printf(“Failed to start PDM!”);
}// set the gain, defaults to 20
PDM.setGain(127);record_ready = true;
return true;
}
/**
-
@brief Wait on new data
-
@return True when finished
*/
static bool microphone_inference_record(void)
{
bool ret = true;if (inference.buf_ready == 1) {
ei_printf(
"Error sample buffer overrun. Decrease the number of slices per model window "
“(EI_CLASSIFIER_SLICES_PER_MODEL_WINDOW)\n”);
ret = false;
}while (inference.buf_ready == 0) {
delay(1);
}inference.buf_ready = 0;
return ret;
}
/**
-
Get raw audio signal data
*/
static int microphone_audio_signal_get_data(size_t offset, size_t length, float *out_ptr)
{
numpy::int16_to_float(&inference.buffers[inference.buf_select ^ 1][offset], out_ptr, length);return 0;
}
/**
-
@brief Stop PDM and release buffers
*/
static void microphone_inference_end(void)
{
PDM.end();
free(inference.buffers[0]);
free(inference.buffers[1]);
free(sampleBuffer);
}
#if !defined(EI_CLASSIFIER_SENSOR) || EI_CLASSIFIER_SENSOR != EI_CLASSIFIER_SENSOR_MICROPHONE
#error “Invalid model for current sensor.”
#endif
#in_serial monitor
Edge Impulse Inferencing Demo
Inferencing settings:
Interval: 0.12 ms.
Frame size: 8000
Sample length: 500 ms.
No. of classes: 5
Failed to start PDM!