Timeline video analysis of LoL replay(cont'd) and Objective tracking from minimap

  object_log = dict()
  timeline_W = timeline.shape[1]

  for obj_name, obj_icon in object_dict.items():
      (tH, tW) = obj_icon.shape[:2]

      # Find the matched region using the query icon as a template
      result = cv2.matchTemplate(timeline, obj_icon, cv2.TM_CCORR_NORMED)
      scores = np.sort(result.reshape(-1))[::-1]

      # for top-k matched regions
      for score in scores[:10]:
          (yCoords, xCoords) = np.where(result == score)

          for x, y in zip(xCoords, yCoords):
              matched_part = timeline[y:y+tH, x:x+tW].copy()
              ssim = structural_similarity(obj_icon, matched_part, multichannel=True)

              if ssim > 0.7:
                  x_center = x+tW//2

                  object_time_secs = int(x_center / timeline_W * full_time_secs)

                  if obj_name in object_log:
                      object_log[obj_name].append(object_time_secs)                
                  else:
                      object_log[obj_name] = [object_time_secs]