diff --git a/software/firmware/cam.py b/software/firmware/cam.py
index cf824e7..ec7d4a9 100644
--- a/software/firmware/cam.py
+++ b/software/firmware/cam.py
@@ -1,56 +1,78 @@
 import cv2
 import numpy as np
+
+# Starts Webcam
 cap = cv2.VideoCapture(0)
+
+# Performs Blurring,Thresholding and Edge detection
 while( cap.isOpened() ) :
     ret,img = cap.read()
     gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
     blur = cv2.GaussianBlur(gray,(5,5),0)
     ret,thresh1 = cv2.threshold(blur,70,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
-  
     contours, hierarchy = cv2.findContours(thresh1,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
     drawing = np.zeros(img.shape,np.uint8)
-
+       
+# Finds the object with the maximum area in the frame   
     max_area=0
-   
     for i in range(len(contours)):
-            cnt=contours[i]
-            area = cv2.contourArea(cnt)
-            if(area>max_area):
-                max_area=area
-                ci=i
+        cnt=contours[i]
+        area = cv2.contourArea(cnt)
+        if(area>max_area):
+            max_area=area
+            ci=i
     cnt=contours[ci]
+    
+# Calculates Convex hull    
     hull = cv2.convexHull(cnt)
+    
+# Calculates the center of the object using moments
     moments = cv2.moments(cnt)
+    
     if moments['m00']!=0:
-                cx = int(moments['m10']/moments['m00']) # cx = M10/M00
-                cy = int(moments['m01']/moments['m00']) # cy = M01/M00
+        cx = int(moments['m10']/moments['m00']) # cx = M10/M00
+        cy = int(moments['m01']/moments['m00']) # cy = M01/M00
               
     centr=(cx,cy)       
     cv2.circle(img,centr,5,[0,0,255],2)       
     cv2.drawContours(drawing,[cnt],0,(0,255,0),2) 
     cv2.drawContours(drawing,[hull],0,(0,0,255),2) 
-          
+
+# Finds Approximate contours and convex hull.
+# This time convex hull returns indices of cnt rather than explicit co-ordinates.            
     cnt = cv2.approxPolyDP(cnt,0.01*cv2.arcLength(cnt,True),True)
     hull = cv2.convexHull(cnt,returnPoints = False)
     
-    if(1):
-               defects = cv2.convexityDefects(cnt,hull)
-               mind=0
-               maxd=0
-               for i in range(defects.shape[0]):
-                    s,e,f,d = defects[i,0]
-                    start = tuple(cnt[s][0])
-                    end = tuple(cnt[e][0])
-                    far = tuple(cnt[f][0])
-                    dist = cv2.pointPolygonTest(cnt,centr,True)
-                    cv2.line(img,start,end,[0,255,0],2)
-                    
-                    cv2.circle(img,far,5,[0,0,255],-1)
-               print(i)
-               i=0
+# Finds convexity defects in the current frame
+# cv2.pointPolygonTest determines whether the convexity defect is inside or outside the object
+    try:
+        defects = cv2.convexityDefects(cnt,hull)
+                
+        for i in range(defects.shape[0]):
+            s,e,f,d = defects[i,0]
+            start = tuple(cnt[s][0])
+            end = tuple(cnt[e][0])
+            far = tuple(cnt[f][0])
+            dist = cv2.pointPolygonTest(cnt,centr,True)
+            cv2.line(img,start,end,[0,255,0],2)
+            cv2.circle(drawing,far,5,[0,0,255],-1)
+ 
+# Prints the command in the upper-left pane of the frame
+                  
+            if (defects.shape[0]==4):
+                # Do Something
+            elif(defects.shape[0]==3):
+                # Do Something
+	    elif(defects.shape[0]==2):
+                # Do Something
+    except AttributeError:
+        pass
+               
+               
     cv2.imshow('output',drawing)
     cv2.imshow('input',img)
                 
     k = cv2.waitKey(10)
+    
     if k == 27:
         break