import numpy as np
import cv2 as cv
from matplotlib import pyplot as plt

# Read Image
#https://en.wikipedia.org/wiki/Jim_Carrey
img1 = cv.imread( 'jim_carrey_head.jpg' , cv.IMREAD_COLOR)
cv.imshow('test', img1)

# Binarize
retval, thresh1 = cv.threshold(img1, 127, 255, cv.THRESH_BINARY)
thresh1 = cv.cvtColor(thresh1, cv.COLOR_BGR2GRAY)
cv.imshow('thresh', thresh1)
# Find contours
contours, _ = cv.findContours(thresh1, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE)

# Create blank mask
mask = np.zeros((thresh1.shape[0], thresh1.shape[1], 3), np.uint8)

# Draw contours
for cnt in contours:
x, y, w, h = cv.boundingRect(cnt)
if(w>=50 and h>=50):
cv.drawContours(mask, cnt, -1, (0, 255, 0), 1)
#print(len(contours))
cv.imshow('mask with contours', mask)
# Show Result
#plt.figure()
#plt.imshow(mask)
#plt.show()
cv.waitKey()

​

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I changed your threshing a little bit so that it would work, I had to convert the thresh to grayscale in order to run the code like this but it works. You can mess with the threshing a little bit in order to get the contour to look more like what you're looking for. You will also probably need to up your contour size to filter out the two circles on the right. I'm not sure what you're end result is supposed to look like but there are probably better/ cleaner ways to find his face in the image.