template_match.py 文件源码

def find_matches(img, template_list):
    # Make a copy of the image to draw on
    # Define an empty list to take bbox coords
    bbox_list = []
    # Iterate through template list
    # Read in templates one by one
    # Use cv2.matchTemplate() to search the image
    #     using whichever of the OpenCV search methods you prefer
    # Use cv2.minMaxLoc() to extract the location of the best match
    # Determine bounding box corners for the match
    # Return the list of bounding boxes
    method = cv2.TM_CCOEFF_NORMED
    for temp in templist:
        tmp = mpimg.imread(temp)
        # Apply template Matching
        res = cv2.matchTemplate(img,tmp,method)
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
        w, h = (tmp.shape[1], tmp.shape[0])

        # 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)
        bbox_list.append((top_left, bottom_right))
    return bbox_list