<p>我们可以使用opencv python执行多尺度模板匹配。其想法是缩放模板图像,并尝试在屏幕截图中定位调整大小的模板。下面的代码(改编自<a href="https://www.pyimagesearch.com/2015/01/26/multi-scale-template-matching-using-python-opencv/" rel="nofollow noreferrer">here</a>)循环了[0.25,2]范围内的50个缩放参数,并选择了提供最佳匹配的参数。为了提高效率,可能需要减小缩放参数的范围或数量。保存正确的缩放参数并将其重新用于多个图像也更好</p>
<pre><code>import cv2
import pyscreeze
import numpy as np
import imutils
import pyautogui
def template_match_with_scaling(image,gs=True,confidence=0.8):
"""
Locate an image and return a pyscreeze box surrounding it.
Template matching is done by default in grayscale (gs=True)
Detect image if normalized correlation coefficient is > confidence (0.8 is default)
"""
templateim = pyscreeze._load_cv2(image,grayscale=gs) # template image
(tH, tW) = templateim.shape[:2]
screenim_color = pyautogui.screenshot() # screenshot of image
screenim_color = cv2.cvtColor(np.array(screenim_color),cv2.COLOR_RGB2BGR)
if gs is True:
screenim = cv2.cvtColor(np.array(screenim_color),cv2.COLOR_BGR2GRAY)
else:
screenim = screenim_color
#try different scaling parameters and see which one matches best
found = None #bookeeping variable for the maximum correlation coefficient, position and scale
scalingrange = np.linspace(0.25,2,num=50)
for scale in scalingrange:
resizedtemplate = imutils.resize(templateim, width = int(templateim.shape[1]*scale) ) # resizing with imutils maintains the aspect ratio
r = float(resizedtemplate.shape[1])/templateim.shape[1] # recompute scaling factor
result = cv2.matchTemplate(screenim, resizedtemplate, cv2.TM_CCOEFF_NORMED) # template matching using the correlation coefficient
(_, maxVal, _, maxLoc) = cv2.minMaxLoc(result) #returns a 4-tuple which includes the minimum correlation value, the maximum correlation value, the (x, y)-coordinate of the minimum value, and the (x, y)-coordinate of the maximum value
if found is None or maxVal > found[0]:
found = (maxVal, maxLoc, r)
(maxVal, maxLoc, r) = found
if maxVal > confidence:
box = pyscreeze.Box(int(maxLoc[0]), int(maxLoc[1]), int(tW*r), int(tH*r) )
return box
else:
return None
def locate_center_with_scaling(image,gs=True):
loc = template_match_with_scaling(image,gs=gs)
if loc:
return pyautogui.center(loc)
else:
raise Exception("Image not found")
#sample usage
coords = locate_center_with_scaling('images/arrow.png')
</code></pre>