waldo.py

import numpy
import argparse
import imutils
import cv2

#https://machinelearningmastery.com/using-opencv-python-and-template-matching-to-play-wheres-waldo/

print("img location")
puzzle = "ExampleImages\Waldo2.jpg"

print("sol location")
waldo = "ExampleImages\Waldo2solution.jpg"

# load the puzzle and waldo images
puzzle = cv2.imread(puzzle)
waldo = cv2.imread(waldo)
(waldoHeight, waldoWidth) = waldo.shape[:2]

# find the waldo in the puzzle
result = cv2.matchTemplate(puzzle, waldo, cv2.TM_CCOEFF)
(_, _, minLoc, maxLoc) = cv2.minMaxLoc(result)

# grab the bounding box of waldo and extract him from
# the puzzle image
topLeft = maxLoc
botRight = (topLeft[0] + waldoWidth, topLeft[1] + waldoHeight)
roi = puzzle[topLeft[1]:botRight[1], topLeft[0]:botRight[0]]
 
# construct a darkened transparent 'layer' to darken everything
# in the puzzle except for waldo
mask = numpy.zeros(puzzle.shape, dtype = "uint8")
puzzle = cv2.addWeighted(puzzle, 0.25, mask, 0.75, 0)

# put the original waldo back in the image so that he is
# 'brighter' than the rest of the image
puzzle[topLeft[1]:botRight[1], topLeft[0]:botRight[0]] = roi
 
# display the images
cv2.imshow("Puzzle", imutils.resize(puzzle, height = 650))
cv2.waitKey(0)