1+ /* *
2+ * This example shows how to use the Eloquent library
3+ * to perform inference using the EdgeImpulse generated library
4+ */
5+ #include < replace_with_edge_impulse_inferencing.h>
6+ #include < eloquent.h>
7+ #include < eloquent/tinyml/edgeimpulse.h>
8+ 9+ 10+ Eloquent::TinyML::EdgeImpulse::Impulse impulse;
11+ 12+ 13+ void setup () {
14+ Serial.begin (115200 );
15+ delay (3000 );
16+ Serial.println (" Starting EdgeImpulse inference"
17+ Serial.println (" Paste your feature vector in the Serial Monitor and get the predicted value"
18+ Serial.print (" (expecting "
19+ Serial.print (EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE);
20+ Serial.println (" comma-separated features)"
21+ }
22+ 23+ 24+ void loop () {
25+ float features[EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE] = {0 };
26+ 27+ if (!Serial.available ())
28+ return ;
29+ 30+ for (int i = 0 ; i < EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE; i++)
31+ features[i] = Serial.readStringUntil (' ,' toFloat ();
32+ 33+ Serial.print (" Predicted class: "
34+ Serial.println (impulse.predict (features));
35+ Serial.print (" Predicted label: "
36+ Serial.println (impulse.getLabel ());
37+ 38+ // debug class probabilities and timing
39+ impulse.printTo (Serial);
40+ }
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