diff --git a/README.md b/README.md
index d536f72..b1b34be 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,2 @@
 # VectorCalc
+# Uses mediapipe, pyauto, and a few other libraries to perform hand gesture recognition
diff --git a/main.py b/main.py
index 1c3a1f2..e478f04 100644
--- a/main.py
+++ b/main.py
@@ -2,6 +2,7 @@
 import cv2
 import time
 import mediapipe as mp
+import pyautogui
 
 # Globals
 DIM = 250
@@ -42,53 +43,161 @@ def findPosition(self, img, handNo=0, draw=True):
                 cx, cy = int(lm.x * w), int(lm.y * h)
                 lmlist.append([id, cx, cy])
                 if draw:
-                    cv2.circle(img, (cx, cy), 3, (255, 0, 255), cv2.FILLED)
+                    #cv2.circle(img, (cx, cy), 3, (255, 0, 255), cv2.FILLED)
+                    cv2.putText(img,str(int(id)),(cx,cy),cv2.FONT_HERSHEY_PLAIN,1,(255,0,255),1)
         return lmlist
 
 
 # Draws the axis for vector graphing    
-def axis(img):
+def axis(img,x,y,width,length):
     thickness = 3
-    cv2.line(img, (img.shape[1]-DIM, 0), (img.shape[1]-DIM, DIM), (0, 0, 255), thickness)
-    cv2.line(img, (img.shape[1]-DIM, DIM), (img.shape[1], DIM), (0, 0, 255), thickness)
-    cv2.line(img, (img.shape[1]-(DIM*2), 0), (img.shape[1]-(DIM*2), DIM), (0, 0, 255), thickness)
-    cv2.line(img, (img.shape[1]-(DIM*2), DIM), (img.shape[1]-DIM, DIM), (0, 0, 255), thickness)
-    cv2.line(img, (img.shape[1]-(DIM*2), DIM), (img.shape[1]-(DIM*2), (DIM*2)), (0, 0, 255), thickness)
-    cv2.line(img, (img.shape[1]-(DIM*2), (DIM*2)), (img.shape[1]-DIM, (DIM*2)), (0, 0, 255), thickness)
-    cv2.line(img, (img.shape[1]-DIM, DIM), (img.shape[1]-DIM, (DIM*2)), (0, 0, 255), thickness)
-    cv2.line(img, (img.shape[1]-DIM, (DIM*2)), (img.shape[1], (DIM*2)), (0, 0, 255), thickness)
+    color = (0, 0, 255)
+    xOffset = int(width)
+    yOffset = int(length)
+    #Middle axis
+    cv2.line(img, ((x-xOffset)//2,y//2), ((x+xOffset)//2,y//2), color, thickness)
+    cv2.line(img, (x//2,(y-yOffset)//2), (x//2,(y+yOffset)//2), color, thickness)
+    #Outer box
+    cv2.rectangle(img, ((x-xOffset)//2,(y-yOffset)//2), ((x+xOffset)//2,(y+yOffset)//2), color, thickness)
     return img
 
+def cursor(img,points):
+    thickness = 1
+    offset = 15
+    color = (0, 255, 0)
+    cv2.line(img, (points[1]-offset, points[2]), (points[1]+offset,points[2]), color, thickness)
+    cv2.line(img, (points[1], points[2]-offset), (points[1], points[2]+offset), color, thickness)
+    return img
+
+def countdown(img,timer,x,y):
+    color = (255,255,255)
+    size = 1
+    if timer - time.time() >=2:
+        color = (255,0,0)
+        size = 2
+    elif timer - time.time() >=1:
+        color = (0,255,0)
+        size = 3
+    elif timer - time.time() >=0:
+        color = (0,0,255)
+        size = 4
+    cv2.putText(img, str(int(timer - time.time())),(x, y), cv2.FONT_HERSHEY_PLAIN, 2, color,size)    
+
 def main():
     pTime = 0
     cTime = 0
+    #Timers for the timed functions
+    clickTimer = 0
+    keyTimer = 0
+    modeTimer = 0
+    stopTimer = 0
     
     # this initalizes what camera to use if an external camera is not used it switches to laptop cam
     cap = cv2.VideoCapture(1)
     if not cap.isOpened():
         cap.release()
         cap = cv2.VideoCapture(0)
+    frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    screen_Width, screen_Height = pyautogui.size()
+    xScale = screen_Width/frame_width
+    yScale = screen_Height/frame_height
+    
     
     # hand detection class
     detector = handDetector()
+    mouse = False
     
     # the first vector is the origin vector 
     # vectors will be formed from the orgin to any place in the graph
     # vectors is x distance from origin, y distance from origin, angle made
     success, img = cap.read()
     vecs = np.array([img.shape[1]-DIM,DIM,0], dtype=float)
-    
     while True:
         #get
         success, img = cap.read()
         if not success:
             break
         img = cv2.flip(img, 1)
-        img = axis(img)
+        img = axis(img,frame_width,frame_height,100*xScale,100*yScale)
         img = detector.findHands(img)
         lmlist = detector.findPosition(img)
+        
+        #Gesture detection block 
+        #thumb, index, middle, ring, and pinkie are true if they are extended and false if they aren't
+        thumb = False
+        index = False
+        middle = False
+        ring = False
+        pinkie = False
+
         if len(lmlist) >= 8:
-            print(lmlist[8])
+            if (lmlist[4][1]<lmlist[3][1] and lmlist[1][1]<lmlist[0][1]) or (lmlist[4][1]>lmlist[3][1] and lmlist[1][1]>lmlist[0][1]):
+                thumb = True
+            if lmlist[8][2]<lmlist[5][2]:
+                index = True
+            if lmlist[12][2]<lmlist[9][2]:
+                middle = True
+            if lmlist[16][2]<lmlist[13][2]:
+                ring = True
+            if lmlist[20][2]<lmlist[17][2]:
+                pinkie = True
+        
+        if (index and pinkie and not thumb and middle and ring):
+            countdown(img,modeTimer,lmlist[0][1],lmlist[0][2]-50)
+            if modeTimer - time.time() <=0:
+                mouse = not mouse
+                modeTimer=time.time() + 3
+        else :
+            modeTimer=time.time() + 3
+        vector = not mouse
+        
+
+        if mouse:
+            #mouse mode
+
+            #If the thumb and index finger are extended, it moves the cursor to the fingertip
+            if thumb and index:
+                cursor(img,lmlist[8])
+                pyautogui.moveTo(lmlist[8][1]*xScale, lmlist[8][2]*yScale)
+                #if the middle finger is also extended for 3 seconds, clicks where the cursor is
+                if middle and not (ring or pinkie):
+                    countdown(img,clickTimer,lmlist[8][1],lmlist[8][2]+20)
+                    if clickTimer == 0:
+                        clickTimer=time.time() + 3
+                    elif clickTimer-time.time() <=0:
+                        pyautogui.click()
+                        clickTimer=time.time() + 3 
+                else :
+                    clickTimer=time.time() + 3
+                    
+            #if only the index, middle, and ring are up for 3 seconds then toggles the windows onscreen keyboard
+            if not thumb and not pinkie and index and middle and ring:
+                countdown(img,keyTimer,lmlist[12][1],lmlist[12][2]+20)
+                if keyTimer == 0:
+                    keyTimer = time.time()
+                elif keyTimer - time.time() <=0:
+                    pyautogui.hotkey('ctrl','win', 'o')
+                    keyTimer=time.time() + 3
+            else :
+                keyTimer=time.time() + 3
+        elif vector:
+            #vector mode
+            #implimentation of vector modes
+            tmp = 0
+
+        # stops the program if the index and pinkie are out and no other fingers are up
+        if (index and pinkie) and not (thumb or middle or ring):
+            countdown(img,stopTimer,frame_width-50,frame_height-50)
+            if stopTimer - time.time() <=0:
+                break
+        else :
+            stopTimer=time.time() + 3
+
+                
+
+        #if len(lmlist) >= 8:
+        #    print(lmlist[8])
         
         # calculate the frames
         cTime = time.time()
@@ -103,6 +212,10 @@ def main():
         cv2.putText(img, "Settings", (10, 50), cv2.FONT_HERSHEY_PLAIN, 3, (255, 0, 255), 3)
         cv2.putText(img, str(int(fps)),(10, img.shape[0] - 30), cv2.FONT_HERSHEY_PLAIN, 3, (255,0, 255),3)
         cv2.imshow("Image", img)
+
+        #generates a cursor
+
+
         # When you press q it quits the program
         if cv2.waitKey(10) & 0xFF == ord('q'):
             break