def _view_init(self):
if not hasattr(self, 'view'):
storage = ((10, 7), [(110.307, 103.657), (1012.311, 103.657),
(-32.959, 600.567), (1113.057, 600.567)])
view = View(self.config, mode='os', grid_class=OSGrid)
view.detector_set_backend('homography')
view.backend.load_homography(storage=storage)
self.view = view
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 os_default_view(self):
"""
Returns:
View:
"""
def empty(*args, **kwargs):
pass
storage = ((10, 7), [(110.307, 103.657), (1012.311, 103.657),
(-32.959, 600.567), (1113.057, 600.567)])
view = View(self.config, mode='os')
view.detector_set_backend('homography')
view.backend.load_homography(storage=storage)
view.backend.load = empty
view.backend.left_edge = None
view.backend.right_edge = None
view.backend.upper_edge = None
view.backend.lower_edge = None
view.backend.homo_loca = (53, 60)
view.load(self.device.image)
return view
NAME: Siren name, images will save in <FOLDER>/<NAME>
NODE: Node in local map view, that you are going to crop.
"""
CONFIG = 'alas'
FOLDER = ''
NAME = 'Deutschland'
NODE = 'D5'
if __name__ == '__main__':
for folder in [FOLDER, os.path.join(FOLDER, NAME)]:
if not os.path.exists(folder):
os.mkdir(folder)
cfg = AzurLaneConfig(CONFIG).merge(Config())
al = ModuleBase(cfg)
view = View(cfg)
al.device.screenshot()
view.load(al.device.image)
grid = view[node2location(NODE.upper())]
print('Please check if it is cropping the right area')
image = rgb2gray(grid.relative_crop((-0.5, -1, 0.5, 0), shape=(60, 60)))
image = Image.fromarray(image, mode='L').show()
images = []
for n in range(300):
print(n)
images.append(al.device.screenshot())
for n, image in enumerate(images):
grid.image = np.array(image)
image = rgb2gray(grid.relative_crop((-0.5, -1, 0.5, 0), shape=(60, 60)))
def _view_init(self):
if not hasattr(self, 'view'):
self.view = View(self.config, grid_class=self.grid_class)
def _view_init(self):
if not hasattr(self, 'view'):
self.view = View(self.config)
# cfg = Config()
# cfg.DETECTION_BACKEND = 'perspective'
# view = View(AzurLaneConfig('template').merge(cfg))
# view.load(image)
# view.predict()
# view.show()
# view.backend.draw()
# ==============================
# Method 2:
# Homography with real-time perspective calculation.
# This is the default method in Alas currently.
# ==============================
cfg = Config()
cfg.DETECTION_BACKEND = 'homography'
view = View(AzurLaneConfig('template').merge(cfg))
view.load(image)
view.predict()
view.show()
view.backend.draw()
# ==============================
# Method 3:
# Homography with hard-coded perspective data (HOMO_STORAGE).
# Get HOMO_STORAGE from log or from method 2.
# ==============================
# cfg = Config()
# cfg.DETECTION_BACKEND = 'homography'
# view = View(AzurLaneConfig('template').merge(cfg))
# homo_storage = () # Paste your HOMO_STORAGE here.
# view.backend.load_homography(storage=homo_storage)
class Config:
"""
Paste the config of map file here
"""
pass
from module.os.config import OSConfig
cfg = AzurLaneConfig('alas').merge(OSConfig())
# Folder to save temp images
folder = './screenshots/relative_crop'
# Put Screenshot here
file = ''
i = load_image(file)
grids = View(cfg)
grids.load(np.array(i))
grids.predict()
grids.show()
os.makedirs(folder, exist_ok=True)
for grid in grids:
# Find more relative_crop area in module/map/grid_predictor.py
# This one is for `predict_enemy_genre`
piece = rgb2gray(grid.relative_crop((-0.5, -1, 0.5, 0), shape=(60, 60)))
file = '%s_%s_%s.png' % (int(time.time()), grid.location[0], grid.location[1])
file = os.path.join(folder, file)
Image.fromarray(piece).save(file)