def search_tile_rectangle(self,
image,
threshold=10,
encourage=5.1,
close_kernel=(5, 10, 15, 20, 25)):
"""
Search for the corner of empty tile.
This is a fallback method for fallback method, almost almost no need.
Note: This method may have a difference in about 2 pixels.
Args:
image (np.ndarray): Monochrome image.
threshold (int): Number of rectangles.
encourage (int, float):
close_kernel (tuple[int]): Kernel size use in morphology close
Returns:
bool: If success.
"""
location = np.array([])
for kernel in close_kernel:
# Re-creating closed image
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,
(kernel, kernel))
image_closed = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel)
# Find rectangles
contours, _ = cv2.findContours(image_closed, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
rectangle = np.array([
cv2.boundingRect(cv2.convexHull(cont).astype(np.float32))
for cont in contours
])
try:
# Filter out correct rectangles
rectangle = rectangle[(rectangle[:, 2] > 100)
& (rectangle[:, 3] > 100)]
shape = rectangle[:, 2:]
diff = np.abs(shape - np.round(shape / self.config.HOMO_TILE) *
self.config.HOMO_TILE)
rectangle = rectangle[np.all(diff < encourage, axis=1)]
location = np.append(
location, rectangle[:, :2],
axis=0) if len(location) else rectangle[:, :2]
except IndexError:
location = []
if len(location) > threshold:
self.homo_loca = fit_points(location,
mod=self.config.HOMO_TILE,
encourage=encourage)
self.map_inner = get_map_inner(location)
message = 'good match'
else:
message = 'bad match'
# print(self.homo_loca % self.config.HOMO_TILE)
logger.attr_align('tile_rectangle',
f'{len(location)} rectangles ({message})')
return message != 'bad match'
def load(self, image):
"""
Args:
image (np.ndarray):
"""
self.load_globe_map()
start_time = time.time()
local = self.find_peaks(
self.perspective_transform(image),
para=self.config.OS_LOCAL_FIND_PEAKS_PARAMETERS)
local = local.astype(np.uint8)
local = cv2.resize(local,
None,
fx=self.config.OS_GLOBE_IMAGE_RESIZE,
fy=self.config.OS_GLOBE_IMAGE_RESIZE)
result = cv2.matchTemplate(self.globe, local, cv2.TM_CCOEFF_NORMED)
_, similarity, _, loca = cv2.minMaxLoc(result)
loca = np.array(loca) / self.config.OS_GLOBE_IMAGE_RESIZE
loca = tuple(self.homo_center + loca - self.config.OS_GLOBE_IMAGE_PAD)
self.center_loca = loca
time_cost = round(time.time() - start_time, 3)
logger.attr_align('globe_center', loca)
logger.attr_align('similarity',
float2str(similarity),
front=float2str(time_cost) + 's')
if similarity < 0.1:
logger.warning('Low similarity when matching OS globe')
def search_tile_corner(self, image, threshold=0.8, encourage=1.0):
"""
Search for the corner of empty tile.
This is a fallback method, almost no need.
Note: This method has a difference in 0.5 ~ 1.0 pixel.
Args:
image (np.ndarray): Monochrome image.
threshold (float):
encourage (int, float):
Returns:
bool: If success.
"""
similarity = 0
location = np.array([])
for index in range(4):
template = ASSETS.tile_corner_image_list[index]
result = cv2.matchTemplate(image, template, cv2.TM_CCOEFF_NORMED)
similarity = max(similarity, np.max(result))
loca = np.argwhere(result > threshold)[:, ::-1] - self.config.HOMO_CORNER_OFFSET_LIST[index]
location = np.append(location, loca, axis=0) if len(location) else loca
if similarity > threshold:
self.homo_loca = fit_points(
location, mod=self.config.HOMO_TILE, encourage=encourage) - self.config.HOMO_CENTER_OFFSET
self.map_inner = get_map_inner(location)
message = f'{len(location)} matches'
else:
message = 'bad match'
# print(self.homo_loca % self.config.HOMO_TILE)
logger.attr_align('tile_corner', f'{float2str(similarity)} ({message})')
return message != 'bad match'
def search_tile_center(self, image, threshold_good=0.9, threshold=0.8, encourage=1.0):
"""
Search for the center of empty tile.
Note: This is the main method.
`len(res[res > 0.8])` is 3x faster than `np.sum(res > 0.8)`
Args:
image (np.ndarray): Monochrome image.
threshold_good (float);
threshold (float):
encourage (int, float):
Returns:
bool: If success.
"""
result = cv2.matchTemplate(image, ASSETS.tile_center_image, cv2.TM_CCOEFF_NORMED)
_, similarity, _, loca = cv2.minMaxLoc(result)
if similarity > threshold_good:
self.homo_loca = np.array(loca) - self.config.HOMO_CENTER_OFFSET
self.map_inner = np.array(loca)
message = 'good match'
elif similarity > threshold:
location = np.argwhere(result > threshold)[:, ::-1]
self.homo_loca = fit_points(
location, mod=self.config.HOMO_TILE, encourage=encourage) - self.config.HOMO_CENTER_OFFSET
self.map_inner = get_map_inner(location)
message = f'{len(location)} matches'
else:
message = 'bad match'
# print(self.homo_loca % self.config.HOMO_TILE)
logger.attr_align('tile_center', f'{float2str(similarity)} ({message})')
return message != 'bad match'
def predict(self):
"""
Predict grid info.
"""
start_time = time.time()
for grid in self:
grid.predict()
logger.attr_align('predict', len(self.grids.keys()), front=float2str(time.time() - start_time) + 's')
def load(self, image):
"""
Args:
image:
"""
image = self._image_clear_ui(np.array(image))
self.image = image
super().load(image)
# Create local view map
grids = {}
grid_class = OSGrid if self.mode == 'os' else Grid
for loca, points in self.generate():
if area_in_area(area1=corner2area(points),
area2=self.config.DETECTING_AREA):
grids[loca] = grid_class(location=loca,
image=image,
corner=points,
config=self.config)
# Handle grids offset
offset = np.min(list(grids.keys()), axis=0)
if np.sum(np.abs(offset)) > 0:
logger.attr_align('grids_offset', tuple(offset.tolist()))
self.grids = {}
for loca, grid in grids.items():
x, y = np.subtract(loca, offset)
grid.location = (x, y)
self.grids[(x, y)] = grid
else:
self.grids = grids
self.shape = np.max(list(self.grids.keys()), axis=0)
# Find local view center
for loca, grid in self.grids.items():
offset = grid.screen2grid([self.config.SCREEN_CENTER
])[0].astype(int)
points = grid.grid2screen(
np.add([[0.5, 0], [-0.5, 0], [0, 0.5], [0, -0.5]], offset))
self.swipe_base = np.array([
np.linalg.norm(points[0] - points[1]),
np.linalg.norm(points[2] - points[3])
])
self.center_loca = tuple(np.add(loca, offset).tolist())
logger.attr_align('center_loca', self.center_loca)
if self.center_loca in self:
self.center_offset = self.grids[self.center_loca].screen2grid(
[self.config.SCREEN_CENTER])[0]
else:
x = max(self.center_loca[0] - self.shape[0],
0) if self.center_loca[0] > 0 else self.center_loca[0]
y = max(self.center_loca[1] - self.shape[1],
0) if self.center_loca[1] > 0 else self.center_loca[1]
self.center_offset = offset - self.center_loca
raise MapDetectionError(
f'Camera outside map: offset=({x}, {y})')
break
def update(self, camera=True):
"""Update map image
Args:
camera: True to update camera position and perspective data.
"""
self.device.screenshot()
if not camera:
self.view.update(image=self.device.image)
return True
if not hasattr(self, 'view'):
self.view = View(self.config)
try:
self.view.load(self.device.image)
except MapDetectionError as e:
if self.info_bar_count():
logger.info('Perspective error cause by info bar. Waiting.')
self.handle_info_bar()
return self.update(camera=camera)
elif self.is_in_stage():
logger.warning('Image is in stage')
raise CampaignEnd('Image is in stage')
elif not self.appear(IN_MAP):
logger.warning('Image to detect is not in_map')
raise e
elif 'Camera outside map' in str(e):
string = str(e)
logger.warning(string)
x, y = string.split('=')[1].strip('() ').split(',')
self._map_swipe((-int(x.strip()), -int(y.strip())))
else:
raise e
if not self._correct_camera:
self.show_camera()
return False
# Set camera position
if self.view.left_edge:
x = 0 + self.view.center_loca[0]
elif self.view.right_edge:
x = self.map.shape[0] - self.view.shape[0] + self.view.center_loca[0]
else:
x = self.camera[0]
if self.view.lower_edge:
y = 0 + self.view.center_loca[1]
elif self.view.upper_edge:
y = self.map.shape[1] - self.view.shape[1] + self.view.center_loca[1]
else:
y = self.camera[1]
if self.camera != (x, y):
logger.attr_align('camera_corrected', f'{location2node(self.camera)} -> {location2node((x, y))}')
self.camera = (x, y)
self.show_camera()
def load(self, image):
"""
Args:
image (np.ndarray): Shape (720, 1280, 3)
"""
start_time = time.time()
self.image = image
# Image initialisation
image = self.load_image(image)
# Lines detection
inner_h = self.detect_lines(
image,
is_horizontal=True,
param=self.config.INTERNAL_LINES_FIND_PEAKS_PARAMETERS,
threshold=self.config.INTERNAL_LINES_HOUGHLINES_THRESHOLD,
theta=self.config.HORIZONTAL_LINES_THETA_THRESHOLD).move(
*self.config.DETECTING_AREA[:2])
inner_v = self.detect_lines(
image,
is_horizontal=False,
param=self.config.INTERNAL_LINES_FIND_PEAKS_PARAMETERS,
threshold=self.config.INTERNAL_LINES_HOUGHLINES_THRESHOLD,
theta=self.config.VERTICAL_LINES_THETA_THRESHOLD).move(
*self.config.DETECTING_AREA[:2])
edge_h = self.detect_lines(
image,
is_horizontal=True,
param=self.config.EDGE_LINES_FIND_PEAKS_PARAMETERS,
threshold=self.config.EDGE_LINES_HOUGHLINES_THRESHOLD,
theta=self.config.HORIZONTAL_LINES_THETA_THRESHOLD,
pad=self.config.DETECTING_AREA[2] -
self.config.DETECTING_AREA[0]).move(
*self.config.DETECTING_AREA[:2])
edge_v = self.detect_lines(
image,
is_horizontal=False,
param=self.config.EDGE_LINES_FIND_PEAKS_PARAMETERS,
threshold=self.config.EDGE_LINES_HOUGHLINES_THRESHOLD,
theta=self.config.VERTICAL_LINES_THETA_THRESHOLD,
pad=self.config.DETECTING_AREA[3] -
self.config.DETECTING_AREA[1]).move(
*self.config.DETECTING_AREA[:2])
# Lines pre-cleansing
horizontal = inner_h.add(edge_h).group()
vertical = inner_v.add(edge_v).group()
edge_h = edge_h.group()
edge_v = edge_v.group()
if not self.config.TRUST_EDGE_LINES:
edge_h = edge_h.delete(inner_h) # Experimental, reduce edge lines.
edge_v = edge_v.delete(inner_v)
self.horizontal = horizontal
self.vertical = vertical
# Calculate perspective
self.crossings = self.horizontal.cross(self.vertical)
self.vanish_point = optimize.brute(self._vanish_point_value,
self.config.VANISH_POINT_RANGE)
distance_point_x = optimize.brute(
self._distant_point_value, self.config.DISTANCE_POINT_X_RANGE)[0]
self.distant_point = (distance_point_x, self.vanish_point[1])
logger.attr_align('vanish_point',
point2str(*self.vanish_point, length=5))
logger.attr_align('distant_point',
point2str(*self.distant_point, length=5))
if np.linalg.norm(np.subtract(self.vanish_point,
self.distant_point)) < 10:
raise MapDetectionError('Vanish point and distant point too close')
# Re-generate lines. Useless after mid_cleanse function added.
# self.horizontal = self.crossings.link(None, is_horizontal=True).group()
# self.vertical = self.crossings.link(self.vanish_point).group()
# self.draw(self.crossings.link(self.distant_point))
# print(edge_h)
# print(inner_h.group())
# Lines cleansing
# self.draw()
self.map_inner = get_map_inner(self.crossings.points)
self.horizontal, self.lower_edge, self.upper_edge = self.line_cleanse(
self.horizontal, inner=inner_h.group(), edge=edge_h)
self.vertical, self.left_edge, self.right_edge = self.line_cleanse(
self.vertical, inner=inner_v.group(), edge=edge_v)
# self.draw()
# print(self.horizontal)
# print(self.lower_edge, self.upper_edge)
# print(self.vertical)
# print(self.left_edge, self.right_edge)
# Log
time_cost = round(time.time() - start_time, 3)
logger.info('%ss %s Horizontal: %s (%s inner, %s edge)' %
(float2str(time_cost), '_' if self.lower_edge else ' ',
len(self.horizontal), len(horizontal), len(edge_h)))
logger.info(
'Edges: %s%s%s Vertical: %s (%s inner, %s edge)' %
('/' if self.left_edge else ' ', '_' if self.upper_edge else ' ',
'\\' if self.right_edge else ' ', len(
self.vertical), len(vertical), len(edge_v)))
def show_camera(self):
logger.attr_align('Camera', location2node(self.camera))
def update(self, camera=True):
"""Update map image
Args:
camera: True to update camera position and perspective data.
"""
self.device.screenshot()
if not camera:
self.view.update(image=self.device.image)
return True
self._view_init()
try:
self.view.load(self.device.image)
except MapDetectionError as e:
if self.info_bar_count():
logger.info('Perspective error cause by info bar. Waiting.')
self.handle_info_bar()
return self.update(camera=camera)
elif self.appear(GET_ITEMS_1):
logger.warning('Items got. Trying handling mystery.')
self.handle_mystery()
return self.update(camera=camera)
elif self.handle_story_skip():
logger.warning('Perspective error cause by story. Handling.')
self.ensure_no_story(skip_first_screenshot=False)
return self.update(camera=camera)
elif self.is_in_stage():
logger.warning('Image is in stage')
raise CampaignEnd('Image is in stage')
elif self.appear(AUTO_SEARCH_MENU_CONTINUE,
offset=self._auto_search_menu_offset):
logger.warning('Image is in auto search menu')
self.ensure_auto_search_exit()
raise CampaignEnd('Image is in auto search menu')
elif not self.appear(IN_MAP):
logger.warning('Image to detect is not in_map')
if self.appear_then_click(GAME_TIPS, offset=(20, 20)):
logger.warning('Game tips found, retrying')
self.device.screenshot()
self.view.load(self.device.image)
else:
raise e
elif 'Camera outside map' in str(e):
string = str(e)
logger.warning(string)
x, y = string.split('=')[1].strip('() ').split(',')
self._map_swipe((-int(x.strip()), -int(y.strip())))
else:
raise e
if self._prev_view is not None and np.linalg.norm(
self._prev_swipe) > 0:
if self.config.MAP_SWIPE_PREDICT:
swipe = self._prev_view.predict_swipe(
self.view,
with_current_fleet=self.config.
MAP_SWIPE_PREDICT_WITH_CURRENT_FLEET,
with_sea_grids=self.config.MAP_SWIPE_PREDICT_WITH_SEA_GRIDS
)
if swipe is not None:
self._prev_swipe = swipe
self.camera = tuple(np.add(self.camera, self._prev_swipe))
self._prev_view = None
self._prev_swipe = None
self.show_camera()
# Set camera position
if self.view.left_edge:
x = 0 + self.view.center_loca[0]
elif self.view.right_edge:
x = self.map.shape[0] - self.view.shape[0] + self.view.center_loca[
0]
else:
x = self.camera[0]
if self.view.lower_edge:
y = 0 + self.view.center_loca[1]
elif self.view.upper_edge:
y = self.map.shape[1] - self.view.shape[1] + self.view.center_loca[
1]
else:
y = self.camera[1]
if self.camera != (x, y):
logger.attr_align(
'camera_corrected',
f'{location2node(self.camera)} -> {location2node((x, y))}')
self.camera = (x, y)
self.show_camera()
self.predict()
def _update(self, camera=True):
"""Update map image
Args:
camera: True to update camera position and perspective data.
"""
self.device.screenshot()
if not camera:
self.view.update(image=self.device.image)
return True
self._view_init()
try:
if not self.is_in_map() \
and not self.is_in_strategy_submarine_move():
logger.warning('Image to detect is not in_map')
raise MapDetectionError('Image to detect is not in_map')
self.view.load(self.device.image)
except MapDetectionError as e:
if self.info_bar_count():
logger.warning('Perspective error caused by info bar')
self.handle_info_bar()
return False
elif self.appear(GET_ITEMS_1):
logger.warning('Perspective error caused by get_items')
self.handle_mystery()
return False
elif self.handle_story_skip():
logger.warning('Perspective error caused by story')
self.ensure_no_story(skip_first_screenshot=False)
return False
elif self.is_in_stage():
logger.warning('Image is in stage')
raise CampaignEnd('Image is in stage')
elif self.appear(AUTO_SEARCH_MENU_CONTINUE,
offset=self._auto_search_menu_offset):
logger.warning('Image is in auto search menu')
self.ensure_auto_search_exit()
raise CampaignEnd('Image is in auto search menu')
elif self.appear(GLOBE_GOTO_MAP, offset=(20, 20)):
logger.warning('Image is in OS globe map')
self.ui_click(GLOBE_GOTO_MAP,
check_button=self.is_in_map,
offset=(20, 20),
retry_wait=3,
skip_first_screenshot=True)
return False
elif self.appear(AUTO_SEARCH_REWARD, offset=(50, 50)):
logger.warning(
'Perspective error caused by AUTO_SEARCH_REWARD')
if hasattr(self, 'os_auto_search_quit'):
self.os_auto_search_quit()
return False
else:
logger.warning(
'Cannot find method os_auto_search_quit(), use ui_click() instead'
)
self.ui_click(AUTO_SEARCH_REWARD,
check_button=self.is_in_map,
offset=(50, 50),
retry_wait=3,
skip_first_screenshot=True)
return False
elif 'opsi' in self.config.task.command.lower(
) and self.handle_popup_confirm('OPSI'):
# Always confirm popups in OpSi, same popups in os_map_goto_globe()
logger.warning('Perspective error caused by popups')
return False
elif not self.is_in_map() \
and not self.is_in_strategy_submarine_move():
if self.appear(GAME_TIPS, offset=(20, 20)):
logger.warning('Perspective error caused by game tips')
self.device.click(GAME_TIPS)
return False
else:
raise e
elif 'Camera outside map' in str(e):
string = str(e)
logger.warning(string)
x, y = string.split('=')[1].strip('() ').split(',')
self._map_swipe((-int(x.strip()), -int(y.strip())))
else:
raise e
if self._prev_view is not None and np.linalg.norm(
self._prev_swipe) > 0:
if self.config.MAP_SWIPE_PREDICT:
swipe = self._prev_view.predict_swipe(
self.view,
with_current_fleet=self.config.
MAP_SWIPE_PREDICT_WITH_CURRENT_FLEET,
with_sea_grids=self.config.MAP_SWIPE_PREDICT_WITH_SEA_GRIDS
)
if swipe is not None:
self._prev_swipe = swipe
self.camera = tuple(np.add(self.camera, self._prev_swipe))
self._prev_view = None
self._prev_swipe = None
self.show_camera()
# Set camera position
if self.view.left_edge:
x = 0 + self.view.center_loca[0]
elif self.view.right_edge:
x = self.map.shape[0] - self.view.shape[0] + self.view.center_loca[
0]
else:
x = self.camera[0]
if self.view.upper_edge:
y = self.map.shape[1] - self.view.shape[1] + self.view.center_loca[
1]
elif self.view.lower_edge:
y = 0 + self.view.center_loca[1]
else:
y = self.camera[1]
if self.camera != (x, y):
logger.attr_align(
'camera_corrected',
f'{location2node(self.camera)} -> {location2node((x, y))}')
self.camera = (x, y)
self.show_camera()
self.predict()
return True
def update(self, camera=True):
"""Update map image
Args:
camera: True to update camera position and perspective data.
"""
self.device.screenshot()
if not camera:
self.view.update(image=self.device.image)
return True
self._view_init()
try:
self.view.load(self.device.image)
except (MapDetectionError, AttributeError) as e:
if self.info_bar_count():
logger.info('Perspective error cause by info bar. Waiting.')
self.handle_info_bar()
return self.update(camera=camera)
elif self.appear(GET_ITEMS_1):
logger.warning('Items got. Trying handling mystery.')
self.handle_mystery()
return self.update(camera=camera)
elif self.is_in_stage():
logger.warning('Image is in stage')
raise CampaignEnd('Image is in stage')
elif not self.appear(IN_MAP):
logger.warning('Image to detect is not in_map')
if self.appear_then_click(GAME_TIPS, offset=(20, 20)):
logger.warning('Game tips found, retrying')
self.device.screenshot()
self.view.load(self.device.image)
else:
raise e
elif 'Camera outside map' in str(e):
string = str(e)
logger.warning(string)
x, y = string.split('=')[1].strip('() ').split(',')
self._map_swipe((-int(x.strip()), -int(y.strip())))
else:
raise e
if self._prev_view is not None and np.linalg.norm(
self._prev_swipe) > 0:
swipe = self._prev_view.predict_swipe(self.view)
if swipe is not None:
self._prev_swipe = swipe
self.camera = tuple(np.add(self.camera, self._prev_swipe))
self._prev_view = None
self._prev_swipe = None
self.show_camera()
if not self._correct_camera:
self.show_camera()
return False
# Set camera position
if self.view.left_edge:
x = 0 + self.view.center_loca[0]
elif self.view.right_edge:
x = self.map.shape[0] - self.view.shape[0] + self.view.center_loca[
0]
else:
x = self.camera[0]
if self.view.lower_edge:
y = 0 + self.view.center_loca[1]
elif self.view.upper_edge:
y = self.map.shape[1] - self.view.shape[1] + self.view.center_loca[
1]
else:
y = self.camera[1]
if self.camera != (x, y):
logger.attr_align(
'camera_corrected',
f'{location2node(self.camera)} -> {location2node((x, y))}')
self.camera = (x, y)
self.show_camera()
