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August 7, 2014 11:47
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python opencv2 find multi template image
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#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
import cv2 | |
import numpy as np | |
def _cv2open(filename, arg=0): | |
obj = cv2.imread(filename, arg) | |
if obj == None: | |
raise IOError('cv2 read file error:'+filename) | |
return obj | |
def _show_image(filename, left_top, (w, h)): | |
img = cv2.imread(filename) | |
x, y = left_top | |
cv2.rectangle(img, (x, y), (x+w, y+h), 255, 2) | |
cv2.namedWindow('image', cv2.WINDOW_NORMAL) | |
cv2.imshow('image',img) | |
cv2.waitKey(0) | |
cv2.destroyAllWindows() | |
def findall(search_file, image_file, threshold=0.7): | |
''' | |
Locate image position with cv2.templateFind | |
Use pixel match to find pictures. | |
Args: | |
search_file(string): filename of search object | |
image_file(string): filename of image to search on | |
threshold: optional variable, to ensure the match rate should >= threshold | |
Returns: | |
A tuple like (x, y) or None if nothing found | |
Raises: | |
IOError: when file read error | |
''' | |
search = _cv2open(search_file) | |
image = _cv2open(image_file) | |
w, h = search.shape[::-1] | |
method = cv2.TM_CCOEFF_NORMED | |
# method = cv2.TM_CCORR_NORMED | |
res = cv2.matchTemplate(image, search, method) | |
points = [] | |
while True: | |
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res) | |
if method in [cv2.TM_SQDIFF, cv2.TM_SQDIFF_NORMED]: | |
top_left = min_loc | |
else: | |
top_left = max_loc | |
if max_val > threshold: | |
# floodfill the already found area | |
sx, sy = top_left | |
for x in range(sx-w/2, sx+w/2): | |
for y in range(sy-h/2, sy+h/2): | |
try: | |
res[y][x] = np.float32(-10000) # -MAX | |
except IndexError: # ignore out of bounds | |
pass | |
# _show_image(image_file, top_left, (w, h)) | |
middle_point = (top_left[0]+w/2, top_left[1]+h/2) | |
points.append(middle_point) | |
else: | |
break | |
return points | |
if __name__ == '__main__': | |
search_file = 'me.png' | |
threshold = 0.5 | |
positions = findall(search_file, 'timer.png', threshold) | |
if positions: | |
w, h = cv2.imread(search_file, 0).shape[::-1] | |
img = cv2.imread('timer.png') | |
for (x, y) in positions: | |
cv2.rectangle(img, (x-w/2, y-w/2), (x+w/2, y+w/2), 255, 2) | |
cv2.imshow('image',img) | |
cv2.waitKey(0) | |
cv2.destroyAllWindows() | |
cv2.namedWindow('image', cv2.WINDOW_NORMAL) | |
# from matplotlib import pyplot as plt | |
# plt.imshow(img, cmap = 'gray', interpolation = 'bicubic') | |
# plt.xticks([]), plt.yticks([]) # to hide tick values on X and Y axis | |
# plt.show() |
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