TypeError: Required argument 'src2' (pos 2) not found

[MBasdas]

I Use python 3.6.4 and OpenCV 3.4.0

line 40: cnt = max(contours, key = lambda x: cv2.contourArea(x))

At this line raise this error

"cnt = max(contours, key=lambda x: contourArea(x))
TypeError: Required argument 'src2' (pos 2) not found"

[gleich]

So this has to do an earlier line that you must have had where there needs to be some variable for the false boolean to be appended to. If you can share the whole file then I probably tell you what to fix.

[viraj63]

import cv2
import numpy as np
import math

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, (300,300), (100,100), (0,255,0),0)
crop_img = img[100:300, 100:300]

# 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
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_NONE)
elif version == '2':
    contours, hierarchy = cv2.findContours(thresh1.copy(),cv2.RETR_TREE, \
           cv2.CHAIN_APPROX_NONE)

# 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)

# finding convexity defects
defects = cv2.convexityDefects(cnt, hull)
count_defects = 0
cv2.drawContours(thresh1, contours, -1, (0, 255, 0), 3)

# 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 = 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)

# define actions required
if count_defects == 1:
    cv2.putText(img,"I am Vipul", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 2, 2)
elif count_defects == 2:
    str = "This is a basic hand gesture recognizer"
    cv2.putText(img, str, (5, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, 2)
elif count_defects == 3:
    cv2.putText(img,"This is 4 :P", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 2, 2)
elif count_defects == 4:
    cv2.putText(img,"Hi!!!", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 2, 2)
else:
    cv2.putText(img,"Hello World!!!", (50, 50),\
                cv2.FONT_HERSHEY_SIMPLEX, 2, 2)

# show appropriate images in windows
cv2.imshow('Gesture', img)
all_img = np.hstack((drawing, crop_img))
cv2.imshow('Contours', all_img)

k = cv2.waitKey(10)
if k == 27:
    break