title: getting error : contours is not defined for my hand-web-browser project
body: <p>I am trying to build a project &quot;hand_web_browser&quot;, the primary objective of this project is to open web pages using hand-gestures. But, I am getting an error at line 55 which says</p>
  <blockquote>
  <p>cnt = max(contours, key=lambda x: cv2.contourArea(x))</p>
  </blockquote>
  <blockquote>
  <p>NameError: name 'contours' is not defined</p>
  </blockquote>
  <p>If anyone could help me with the issue???</p>
  <pre><code>import cv2
  import numpy as np
  import math
  import webbrowser as wb
  import os
  
  print(&quot;Enter full website for&quot;)
  
  print(&quot;\n2 fingers&quot;)
  fingers2 = input()
  
  print(&quot;\n3 fingers&quot;)
  fingers3 = input()
  
  print(&quot;\n4 fingers&quot;)
  fingers4 = input()
  
  tabs = 0
  count = 0
  cap = cv2.VideoCapture(0)
  
  while (cap.isOpened()):
      # read image
      ret, img = cap.read()
  
      # get hand data from the rectangle sub window on the screen
      cv2.rectangle(img, (400, 400), (100, 100), (0, 255, 0), 0)
      crop_img = img[100:400, 100:400]
  
      # convert to grayscale
      grey = cv2.cvtColor(crop_img, cv2.COLOR_BGR2GRAY)
  
      # applying gaussian blur
      value = (35, 35)
      blurred = cv2.GaussianBlur(grey, value, 0)
  
      # thresholdin: Otsu's Binarization method
      _, thresh1 = cv2.threshold(blurred, 127, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
  
      # show thresholded image, not necessary and can be skipped
      cv2.imshow('Thresholded', thresh1)
  
      # check OpenCV version to avoid unpacking error
      (version, _, _) = cv2.__version__.split('.')
  
      if version == '3':
          image, contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
      elif version == '2':
          contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
  
      # find contour with max area
      cnt = max(contours, key=lambda x: cv2.contourArea(x))
  
      # create bounding rectangle around the contour (can skip below two lines)
      x, y, w, h = cv2.boundingRect(cnt)
      cv2.rectangle(crop_img, (x, y), (x + w, y + h), (0, 0, 255), 0)
  
      # finding convex hull
      hull = cv2.convexHull(cnt)
  
      # drawing contours
      drawing = np.zeros(crop_img.shape, np.uint8)
      cv2.drawContours(drawing, [cnt], 0, (0, 255, 0), 0)
      cv2.drawContours(drawing, [hull], 0, (0, 0, 255), 0)
  
      # finding convex hull
      hull = cv2.convexHull(cnt, returnPoints=False)  # return point false to find convexity defects
  
      # finding convexity defects
      defects = cv2.convexityDefects(cnt, hull)
      count_defects = 0
      cv2.drawContours(thresh1, contours, -1, (0, 255, 0), 3)  # to draw all contours pass -1
  
      # applying Cosine Rule to find angle for all defects (between fingers)
      # with angle &gt; 90 degrees and ignore defects
      for i in range(defects.shape[0]):
          s, e, f, d = defects[i, 0]  # [ start point, end point, farthest point, approximate distance to farthest point ]
  
          start = tuple(cnt[s][0])
          end = tuple(cnt[e][0])
          far = tuple(cnt[f][0])
  
          # 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)
  
          # apply cosine rule here
          angle = math.acos((b ** 2 + c ** 2 - a ** 2) / (2 * b * c)) * 57
  
          # ignore angles &gt; 90 and highlight rest with red dots
          if angle &lt;= 90:
              count_defects += 1
              cv2.circle(crop_img, far, 1, [0, 0, 255], -1)
          # dist = cv2.pointPolygonTest(cnt,far,True)
  
          # draw a line from start to end i.e. the convex points (finger tips)
          # (can skip this part)
          cv2.line(crop_img, start, end, [0, 255, 0], 2)
          # cv2.circle(crop_img,far,5,[0,0,255],-1)
      if count == 0:
          cv2.putText(img, &quot;Wait for it :p&quot;, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
      # define actions required
      if count_defects == 1 and count != 2 and tabs &lt;= 8:
          wb.open_new_tab('http://www.' + fingers2 + '.com')
          tabs = tabs + 1
          cv2.putText(img, &quot;2.&quot; + fingers2, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 0, 0), 3)
          count = 2
      elif count_defects == 2 and count != 3 and tabs &lt;= 8:
          wb.open_new_tab('http://www.' + fingers3 + '.com')
          tabs = tabs + 1
          cv2.putText(img, &quot;3.&quot; + fingers3, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (0, 0, 255), 3)
          count = 3
      elif count_defects == 3 and count != 4 and tabs &lt;= 8:
          wb.open_new_tab('http://www.' + fingers4 + '.com')
          cv2.putText(img, &quot;4.&quot; + fingers4, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 165, 0), 3)
          tabs = tabs + 1
          count = 4
      elif count_defects == 4 and count != 5:
          cv2.putText(img, &quot;5.Close Web browser&quot;, (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
          os.system(&quot;taskkill /im chrome.exe /f&quot;)
          tabs = 0
          count = 5
      else:
          cv2.putText(img, &quot;&quot;, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
  
      if count == 2:
          cv2.putText(img, &quot;2.&quot; + fingers2, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 0, 0), 3)
      elif count == 3:
          cv2.putText(img, &quot;3.&quot; + fingers3, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (0, 0, 255), 3)
      elif count == 4:
          cv2.putText(img, &quot;4.&quot; + fingers4, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 165, 0), 3)
      elif count == 5:
          cv2.putText(img, &quot;5.WebBrowser close&quot;, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
  
      # show appropriate images in windows
      cv2.imshow('Gesture', img)
      all_img = np.hstack((drawing, crop_img))
      # not necessary to show contours and can be skipped
      cv2.imshow('Contours', all_img)
  
      k = cv2.waitKey(10)
      if k == 27:
          break
  </code></pre>