def _perform_template_matching(self, minimap):
context_slice = self._get_scaled_context()
context_coords = get_coords_from_slices(context_slice)
template_match = cv2.matchTemplate(
self.gray_map[context_slice],
cv2.cvtColor(minimap, cv2.COLOR_RGB2GRAY), cv2.TM_CCOEFF_NORMED)
# match is an array, the same shape as the context. Next, we must find the minimum value
# in the array because we're using the TM_CCOEFF_NORMED matching method.
if context_slice != slice(None, None, None):
context_last_known = coordinate_sum(
scale_coords(self.last_known_position, self.scale),
[-x for x in context_coords])
x_rows = np.arange(template_match.shape[0]) - context_last_known[0]
y_rows = np.arange(template_match.shape[0]) - context_last_known[1]
x_grid, y_grid = np.meshgrid(x_rows, y_rows)
match_adjustment = np.sqrt(np.sqrt(x_grid**2 + y_grid**2)) / 1000
template_match -= match_adjustment
else:
match_adjustment = None
_, template_match_value, _, match_position = cv2.minMaxLoc(
template_match)
scaled_position = coordinate_sum(match_position, context_coords)
scaled_position = coordinate_offset(scaled_position,
self.minimap_iter.size // 2)
if self.debug:
self.__debug_context(match_position, context_slice)
self.__debug_template_match(template_match, match_adjustment)
self.__debug_land(scaled_position)
return scaled_position, template_match_value
def _is_position_on_land(self, unscaled_position):
on_land = False
if unscaled_position:
land_mask_coords = scale_coords(unscaled_position,
self.land_mask_scale)
on_land = bool(self.land_mask[land_mask_coords[1],
land_mask_coords[0]])
return on_land
def __debug_land(self, scaled_position):
land_debug = np.copy(self.land_mask)
if scaled_position:
unscaled_position = self._unscale_coords(scaled_position)
on_land = self._is_position_on_land(unscaled_position)
land_debug = cv2.cvtColor(land_debug, cv2.COLOR_GRAY2BGR)
land_mask_coords = scale_coords(unscaled_position,
self.land_mask_scale)
cv2.circle(land_debug, land_mask_coords, 10,
LAND() if on_land else WATER(), cv2.FILLED)
cv2.imshow("land", land_debug)
cv2.waitKey(10)
def _get_scaled_context(self):
# Context defines the area that the template matching will be limited to.
# This area gets larger each time a match is missed to account for movement processing.
context_slice = slice(None)
if self.last_known_position:
max_reachable_dist = self._calculate_max_travel_distance()
context_coords, context_size = find_path_bounds(
self.gray_map.shape[0],
[scale_coords(self.last_known_position, self.scale)],
crop_border=0,
min_size=max_reachable_dist)
context_slice = create_slice(context_coords, context_size)
return context_slice