getting error : contours is not defined for my hand-web-browser project

I am trying to build a project “hand_web_browser”, 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

cnt = max(contours, key=lambda x: cv2.contourArea(x))

NameError: name ‘contours’ is not defined

If anyone could help me with the issue???

import cv2
import numpy as np
import math
import webbrowser as wb
import os

print("Enter full website for")

print("n2 fingers")
fingers2 = input()

print("n3 fingers")
fingers3 = input()

print("n4 fingers")
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 > 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 > 90 and highlight rest with red dots
        if angle <= 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, "Wait for it :p", (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
    # define actions required
    if count_defects == 1 and count != 2 and tabs <= 8:
        wb.open_new_tab('http://www.' + fingers2 + '.com')
        tabs = tabs + 1
        cv2.putText(img, "2." + fingers2, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 0, 0), 3)
        count = 2
    elif count_defects == 2 and count != 3 and tabs <= 8:
        wb.open_new_tab('http://www.' + fingers3 + '.com')
        tabs = tabs + 1
        cv2.putText(img, "3." + fingers3, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (0, 0, 255), 3)
        count = 3
    elif count_defects == 3 and count != 4 and tabs <= 8:
        wb.open_new_tab('http://www.' + fingers4 + '.com')
        cv2.putText(img, "4." + 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, "5.Close Web browser", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
        os.system("taskkill /im chrome.exe /f")
        tabs = 0
        count = 5
    else:
        cv2.putText(img, "", (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)

    if count == 2:
        cv2.putText(img, "2." + fingers2, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 0, 0), 3)
    elif count == 3:
        cv2.putText(img, "3." + fingers3, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (0, 0, 255), 3)
    elif count == 4:
        cv2.putText(img, "4." + fingers4, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 165, 0), 3)
    elif count == 5:
        cv2.putText(img, "5.WebBrowser close", (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

Answer

I presume you are using a latest version of OpenCV. If you are using something like 4.x.x, try the following code.

if version == '4':
        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)

The reason for the error is that your code is not extracting the contours at all, because the statement (version, _, _) = cv2.__version__.split('.') returns 4 and your “if and else” both fail.

Please note the following line of code as well.

contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

This is changed because

Since OpenCV 3.2, findContours() no longer modifies the source image.

I hope this will solve your issue.