Question/Issue:
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I am unable to compile the examples , hello_world_arcada and micro_speech_arcada , on the adafruit website found here on my Circuit playground bluefruit microcontroller
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I installed the Adafruit_Tensorflow_Lite library in my arduino ide as mentioned in the site however it turns out that when compiling the examples they have numerous missing files. So i downloaded this tensorflow git hub repo and then transfered the missing files into the Adafruit_Tensorflow_Lite library.
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I am now facing this error for the missing files : am_bsp.h,am_mcu_apollo.h, am_util.h , i cannot locate these files on the repo or on google [Note: i did find the am_bsp.h file in the sparkfun_edge_bsp repo, but it did not solve the error]
Can anyone let me know where i can find these files or a way to compile the code and download the bluefruit microcontroller ?
- The error is shown in the pic below of the missing file am_bsp.h when using Arduino IDE to compile:
- My code is shown below:
#include <TensorFlowLite.h>
#include "Adafruit_TFLite.h"
#include "Adafruit_Arcada.h"
#include "output_handler.h"
#include "sine_model_data.h"
// Create an area of memory to use for input, output, and intermediate arrays.
// Finding the minimum value for your model may require some trial and error.
const int kTensorAreaSize (2 * 1024);
// This constant represents the range of x values our model was trained on,
// which is from 0 to (2 * Pi). We approximate Pi to avoid requiring additional
// libraries.
const float kXrange = 2.f * 3.14159265359f;
// Will need tuning for your chipset
const int kInferencesPerCycle = 200;
int inference_count = 0;
Adafruit_Arcada arcada;
Adafruit_TFLite ada_tflite(kTensorAreaSize);
// The name of this function is important for Arduino compatibility.
void setup() {
Serial.begin(115200);
//while (!Serial) yield();
arcada.arcadaBegin();
// If we are using TinyUSB we will have the filesystem show up!
arcada.filesysBeginMSD();
arcada.filesysListFiles();
// Set the display to be on!
arcada.displayBegin();
arcada.setBacklight(255);
arcada.display->fillScreen(ARCADA_BLUE);
if (! ada_tflite.begin()) {
arcada.haltBox("Failed to initialize TFLite");
while (1) yield();
}
if (arcada.exists("model.tflite")) {
arcada.infoBox("Loading model.tflite from disk!");
if (! ada_tflite.loadModel(arcada.open("model.tflite"))) {
arcada.haltBox("Failed to load model file");
}
} else if (! ada_tflite.loadModel(g_sine_model_data)) {
arcada.haltBox("Failed to load default model");
}
Serial.println("\nOK");
// Keep track of how many inferences we have performed.
inference_count = 0;
}
// The name of this function is important for Arduino compatibility.
void loop() {
// Calculate an x value to feed into the model. We compare the current
// inference_count to the number of inferences per cycle to determine
// our position within the range of possible x values the model was
// trained on, and use this to calculate a value.
float position = static_cast<float>(inference_count) /
static_cast<float>(kInferencesPerCycle);
float x_val = position * kXrange;
// Place our calculated x value in the model's input tensor
ada_tflite.input->data.f[0] = x_val;
// Run inference, and report any error
TfLiteStatus invoke_status = ada_tflite.interpreter->Invoke();
if (invoke_status != kTfLiteOk) {
ada_tflite.error_reporter->Report("Invoke failed on x_val: %f\n",
static_cast<double>(x_val));
return;
}
// Read the predicted y value from the model's output tensor
float y_val = ada_tflite.output->data.f[0];
// Output the results. A custom HandleOutput function can be implemented
// for each supported hardware target.
HandleOutput(ada_tflite.error_reporter, x_val, y_val);
// Increment the inference_counter, and reset it if we have reached
// the total number per cycle
inference_count += 1;
if (inference_count >= kInferencesPerCycle) inference_count = 0;
}