diff --git a/android-sample/app/src/main/java/com/specpal/mobileai/MainActivity.java b/android-sample/app/src/main/java/com/specpal/mobileai/MainActivity.java
index 97ad1ba..739e097 100644
--- a/android-sample/app/src/main/java/com/specpal/mobileai/MainActivity.java
+++ b/android-sample/app/src/main/java/com/specpal/mobileai/MainActivity.java
@@ -24,15 +24,18 @@
 
 public class MainActivity extends AppCompatActivity {
 
+    //Load the tensorflow inference library
     static {
         System.loadLibrary("tensorflow_inference");
     }
 
+    //PATH TO OUR MODEL FILE AND NAMES OF THE INPUT AND OUTPUT NODES
     private String MODEL_PATH = "file:///android_asset/squeezenet.pb";
     private String INPUT_NAME = "input_1";
     private String OUTPUT_NAME = "output_1";
     private TensorFlowInferenceInterface tf;
 
+    //ARRAY TO HOLD THE PREDICTIONS AND FLOAT VALUES TO HOLD THE IMAGE DATA
     float[] PREDICTIONS = new float[1000];
     private float[] floatValues;
     private int[] INPUT_SIZE = {224,224,3};
@@ -46,12 +49,14 @@ protected void onCreate(Bundle savedInstanceState) {
         super.onCreate(savedInstanceState);
         setContentView(R.layout.activity_main);
 
-        tf = new TensorFlowInferenceInterface(getAssets(),MODEL_PATH);
-
 
         Toolbar toolbar = (Toolbar) findViewById(R.id.toolbar);
         setSupportActionBar(toolbar);
 
+
+        //initialize tensorflow with the AssetManager and the Model
+        tf = new TensorFlowInferenceInterface(getAssets(),MODEL_PATH);
+
         imageView = (ImageView) findViewById(R.id.imageview);
         resultView = (TextView) findViewById(R.id.results);
 
@@ -66,6 +71,7 @@ public void onClick(View view) {
 
                 try{
 
+                    //READ THE IMAGE FROM ASSETS FOLDER
                     InputStream imageStream = getAssets().open("testimage.jpg");
 
                     Bitmap bitmap = BitmapFactory.decodeStream(imageStream);
@@ -84,6 +90,7 @@ public void onClick(View view) {
         });
     }
 
+    //FUNCTION TO COMPUTE THE MAXIMUM PREDICTION AND ITS CONFIDENCE
     public Object[] argmax(float[] array){
 
 
@@ -110,20 +117,29 @@ public Object[] argmax(float[] array){
     public void predict(final Bitmap bitmap){
 
 
+        //Runs inference in background thread
         new AsyncTask<Integer,Integer,Integer>(){
 
             @Override
 
             protected Integer doInBackground(Integer ...params){
 
+                //Resize the image into 224 x 224
                 Bitmap resized_image = ImageUtils.processBitmap(bitmap,224);
+
+                //Normalize the pixels
                 floatValues = ImageUtils.normalizeBitmap(resized_image,224,127.5f,1.0f);
 
+                //Pass input into the tensorflow
                 tf.feed(INPUT_NAME,floatValues,1,224,224,3);
+
+                //compute predictions
                 tf.run(new String[]{OUTPUT_NAME});
 
+                //copy the output into the PREDICTIONS array
                 tf.fetch(OUTPUT_NAME,PREDICTIONS);
 
+                //Obtained highest prediction
                 Object[] results = argmax(PREDICTIONS);
 
 
@@ -135,10 +151,12 @@ protected Integer doInBackground(Integer ...params){
 
                     final String conf = String.valueOf(confidence * 100).substring(0,5);
 
+                    //Convert predicted class index into actual label name
                    final String label = ImageUtils.getLabel(getAssets().open("labels.json"),class_index);
 
 
 
+                   //Display result on UI
                     runOnUiThread(new Runnable() {
                         @Override
                         public void run() {