Add README

README.md

@@ -0,0 +1,52 @@
+# EloquentTinyML
+
+This Arduino library is here to simplify the deployment of Tensorflow Lite
+for Microcontrollers models to Arduino boards using the Arduino IDE.
+
+Including all the required files for you, the library exposes an eloquent
+interface to load a model and run inferences.
+
+## Install
+
+Clone this repo in you Arduino libraries folder.
+
+```bash
+git clone https://github.com/eloquentarduino/EloquentTinyML.git
+```
+
+
+## Use
+
+```cpp
+#include <EloquentTinyML.h>
+#include "sine_model.h"
+
+#define NUMBER_OF_INPUTS 1
+#define NUMBER_OF_OUTPUTS 1
+#define TENSOR_ARENA_SIZE 2*1024
+
+Eloquent::TinyML::TinyML<
+    NUMBER_OF_INPUTS,
+    NUMBER_OF_OUTPUTS,
+    TENSOR_ARENA_SIZE> ml(sine_model_quantized_tflite);
+
+
+void setup() {
+    Serial.begin(115200);
+}
+
+void loop() {
+    float x = 3.14 * random(100) / 100;
+    float y = sin(x);
+    float input[1] = { x };
+    float predicted = ml.predict(input);
+
+    Serial.print("sin(");
+    Serial.print(x);
+    Serial.print(") = ");
+    Serial.print(y);
+    Serial.print("\t predicted: ");
+    Serial.println(predicted);
+    delay(1000);
+}
+```

examples/SineExample/SineExample.ino

@@ -1,18 +1,31 @@
 #include <EloquentTinyML.h>
 #include "sine_model.h"
 
+#define NUMBER_OF_INPUTS 1
+#define NUMBER_OF_OUTPUTS 1
+#define TENSOR_ARENA_SIZE 2*1024
 
-Eloquent::TinyML::TinyML<1, 1, 2048> ml(sine_model_quantized_tflite);
+Eloquent::TinyML::TinyML<
+        NUMBER_OF_INPUTS,
+        NUMBER_OF_OUTPUTS,
+        TENSOR_ARENA_SIZE> ml(sine_model_quantized_tflite);
 
 
 void setup() {
     Serial.begin(115200);
 }
 
 void loop() {
-    float input[1] = {random(10) > 5 ? 3.14/2 : 0};
-    float output = ml.predict(input);
+    float x = 3.14 * random(100) / 100;
+    float y = sin(x);
+    float input[1] = { x };
+    float predicted = ml.predict(input);
 
-    Serial.println(output);
+    Serial.print("sin(");
+    Serial.print(x);
+    Serial.print(") = ");
+    Serial.print(y);
+    Serial.print("\t predicted: ");
+    Serial.println(predicted);
     delay(1000);
 }