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Sorry for reply. Try this:

import cv2
import numpy as np
import math
cap = cv2.VideoCapture(0)

while True:
    ret,frame = cap.read()
    frame=cv2.flip(frame,1)
    kernel = np.ones((3,3),np.uint8)

    #define region of interest   
    roi=frame[100:300, 100:300]
    cv2.rectangle(frame,(100,100),(300,300),(0,255,0),0)    
    hsv = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)

    #define range of skin color in HSV   
    lower_skin = np.array([0,20,70], dtype=np.uint8)
    upper_skin = np.array([20,255,255], dtype=np.uint8)

    #extract skin colur imagw    
    mask = cv2.inRange(hsv, lower_skin, upper_skin)

    #extrapolate the hand to fill dark spots within   
    mask = cv2.dilate(mask,kernel,iterations = 4)    
    #blur the image  
    mask = cv2.GaussianBlur(mask,(5,5),100) 

    #find contours    
    cnts,contours,hierarchy= cv2.findContours(mask,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

    #find contour of max area(hand)  
    cnt = max(contours, key = lambda x: cv2.contourArea(x))

    #approx the contour a little
    epsilon = 0.0005*cv2.arcLength(cnt,True)
    approx= cv2.approxPolyDP(cnt,epsilon,True)

    #make convex hull around hand   
    hull = cv2.convexHull(cnt)

    #define area of hull and area of hand   
    areahull = cv2.contourArea(hull)
    areacnt = cv2.contourArea(cnt)

    #find the percentage of area not covered by hand in convex hull    
    arearatio=((areahull-areacnt)/areacnt)*100

    #find the defects in convex hull with respect to hand   
    hull = cv2.convexHull(approx, returnPoints=False)
    defects = cv2.convexityDefects(approx, hull)

    #l = no. of defects    
    l=0

    #code for finding no. of defects due to fingers    
    for i in range(defects.shape[0]):
        s,e,f,d = defects[i,0]
        start = tuple(approx[s][0])
        end = tuple(approx[e][0])
        far = tuple(approx[f][0])
        pt= (100,180)

        #find length of all sides of triangle        
        a = math.sqrt((end[0] - start[0])**2 + (end[1] - start[1])**2)
        b = math.sqrt((far[0] - start[0])**2 + (far[1] - start[1])**2)
        c = math.sqrt((end[0] - far[0])**2 + (end[1] - far[1])**2)
        s = (a+b+c)/2
        ar = math.sqrt(s*(s-a)*(s-b)*(s-c))

        #distance between point and convex hull      
        d=(2*ar)/a

        #apply cosine rule here      
        angle = math.acos((b**2 + c**2 - a**2)/(2*b*c)) * 57

        #ignore angles > 90 and ignore points very close to convex hull(they generally come due to noise)       
        if angle <= 90 and d>30:
            l += 1
            cv2.circle(roi, far, 3, [255,0,0], -1)

        #draw lines around hand           
        cv2.line(roi,start, end, [0,255,0], 2)       

    l+=1

    #print corresponding gestures which are in their ranges   
    font = cv2.FONT_HERSHEY_SIMPLEX
    if l==1:
        if areacnt<2000:
            cv2.putText(frame,'Put hand in the box',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)
        else:
            if arearatio<12:
                cv2.putText(frame,'0',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)
            elif arearatio<17.5:
                cv2.putText(frame,'Best of luck',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

            else:
                cv2.putText(frame,'1',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

    elif l==2:
        cv2.putText(frame,'2',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

    elif l==3:

          if arearatio<27:
                cv2.putText(frame,'3',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)
          else:
                cv2.putText(frame,'ok',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

    elif l==4:
        cv2.putText(frame,'4',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

    elif l==5:
        cv2.putText(frame,'5',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

    elif l==6:
        cv2.putText(frame,'reposition',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

    else :
        cv2.putText(frame,'reposition',(10,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

    #show the windows       
    cv2.imshow('mask',mask)
    cv2.imshow('frame',frame)


    if cv2.waitKey(25) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()