I am currently trying to use some pattern matching using python and opencv. I have copied the example code from the opencv website and tried to run it on my image. However when doing so I get an out of memory error due to the system not being able to allocate about 700mb, however I have more than enough free ram (32gb) and everything is running in 64-bit. I have looked at various posts with similar issues but could not find a solution that works for me.
Python code
import cv2
import numpy as np
from matplotlib import pyplot as plt
img = cv2.imread('***.jpg',0)
img2 = img.copy()
template = cv2.imread('***.png',0)
w, h = template.shape[::-1]
# All the 6 methods for comparison in a list
img = img2.copy()
method = eval('cv2.TM_CCOEFF')
# Apply template Matching
res = cv2.matchTemplate(img,template,method)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
# If the method is TM_SQDIFF or TM_SQDIFF_NORMED, take minimum
if method in [cv2.TM_SQDIFF, cv2.TM_SQDIFF_NORMED]:
top_left = min_loc
else:
top_left = max_loc
bottom_right = (top_left[0] + w, top_left[1] + h)
cv2.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()
Before anyone mentions it, yes there are valid filenames where the *s are.
Image im trying to use as a base has a size of about 11mb