import os
import cv2 as cv
from matplotlib import pyplot as plt
 
# interpolate here_path to get the path to the fishing target image      
herePath = os.path.dirname(os.path.realpath(__file__))

img = cv.imread(os.path.join(herePath, "assets", "Bobber2.png"), cv.IMREAD_GRAYSCALE)
assert img is not None, "file could not be read, check with os.path.exists()"
img2 = img.copy()
template = cv.imread(os.path.join(herePath, "assets", "FishTest3.png"), cv.IMREAD_GRAYSCALE)
assert template is not None, "file could not be read, check with os.path.exists()"
w, h = template.shape[::-1]
 
# All the 6 methods for comparison in a list
methods = ['TM_CCOEFF', 'TM_CCOEFF_NORMED', 'TM_CCORR',
            'TM_CCORR_NORMED', 'TM_SQDIFF', 'TM_SQDIFF_NORMED']
 
for meth in methods:
    img = img2.copy()
    method = getattr(cv, meth)
 
    # Apply template Matching
    res = cv.matchTemplate(img,template,method)
    min_val, max_val, min_loc, max_loc = cv.minMaxLoc(res)
 
    # If the method is TM_SQDIFF or TM_SQDIFF_NORMED, take minimum
    if method in [cv.TM_SQDIFF, cv.TM_SQDIFF_NORMED]:
        top_left = min_loc
    else:
        top_left = max_loc
    bottom_right = (top_left[0] + w, top_left[1] + h)
 
    cv.rectangle(img,top_left, bottom_right, 255, 2)
 
    plt.subplot(121)
    plt.imshow(res,cmap = 'gray')
    plt.title('Matching Result')
    plt.xticks([])
    plt.yticks([])
    plt.subplot(122)
    plt.imshow(img,cmap = 'gray')
    plt.title('Detected Point')
    plt.xticks([])
    plt.yticks([])
    plt.suptitle(meth)
 
    plt.show()