def detect(self, image):
"""
Args:
image: Screenshot.
Returns:
bool: If success.
"""
start_time = time.time()
image = np.array(image)
self.image = image
# Image initialization
image = rgb2gray(crop(image, self.config.DETECTING_AREA))
# Perspective transform
image_trans = cv2.warpPerspective(image, self.homo_data,
self.homo_size)
# Edge detection
image_edge = cv2.Canny(image_trans, 100, 150)
image_edge = cv2.bitwise_and(image_edge, self.ui_mask_homo_stroke)
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
image_edge = cv2.morphologyEx(image_edge, cv2.MORPH_CLOSE, kernel)
# Image.fromarray(image_edge, mode='L').show()
# Find free tile
if self.search_tile_center(
image_edge,
threshold_good=self.config.HOMO_CENTER_GOOD_THRESHOLD,
threshold=self.config.HOMO_CENTER_THRESHOLD):
pass
elif self.search_tile_corner(
image_edge, threshold=self.config.HOMO_CORNER_THRESHOLD):
pass
elif self.search_tile_rectangle(
image_edge, threshold=self.config.HOMO_RECTANGLE_THRESHOLD):
pass
else:
raise MapDetectionError('Failed to find a free tile')
self.homo_loca %= self.config.HOMO_TILE
# Detect map edges
image_edge = cv2.bitwise_and(
cv2.dilate(image_edge, kernel),
cv2.inRange(image_trans, *self.config.HOMO_EDGE_COLOR_RANGE))
self.detect_edges(image_edge,
hough_th=self.config.HOMO_EDGE_HOUGHLINES_THRESHOLD)
# Log
time_cost = round(time.time() - start_time, 3)
logger.info('%ss %s edge_lines: %s hori, %s vert' %
(float2str(time_cost), '_' if self.lower_edge else ' ',
self._map_edge_count[1], self._map_edge_count[0]))
logger.info(
'Edges: %s%s%s homo_loca: %s' %
('/' if self.left_edge else ' ', '_' if self.upper_edge else ' ',
'\\' if self.right_edge else ' ',
point2str(*self.homo_loca, length=3)))
def load_image(self, image):
"""Method that turns image to monochrome and hide UI.
Args:
image: Screenshot.
Returns:
np.ndarray
"""
image = rgb2gray(crop(image, self.config.DETECTING_AREA))
image = cv2.subtract(255, cv2.bitwise_and(image, ASSETS.ui_mask))
return image
def unpack(image):
"""
Split images vertically.
Args:
image:
Returns:
list: List of np.ndarray.
"""
size = image_size(image)
if size == (1280, 720):
return [image]
else:
if size[0] != 1280 or size[1] % 720 != 0:
raise ImageError(f'Unexpected image size: {size}')
return [crop(image, (0, n * 720, 1280, (n + 1) * 720)) for n in range(size[1] // 720)]
def get_research_status(self, image):
"""
Args:
image: Screenshot
Returns:
list[str]: List of project status
"""
out = []
for index, status, scaling in zip(range(5), RESEARCH_STATUS, TEMPLATE_SCALING):
info = status.crop((0, -40, 200, 0))
piece = rgb2gray(crop(image, info.area))
if TEMPLATE_WAITING.match(piece, scaling=scaling):
out.append('waiting')
elif TEMPLATE_RUNNING.match(piece, scaling=scaling):
out.append('running')
elif TEMPLATE_DETAIL.match(piece, scaling=scaling):
out.append('detail')
else:
out.append('unknown')
logger.info(f'Research status: {out}')
return out
def ui_mask_in_map(self):
DETECTING_AREA = (123, 55, 1280, 720)
area = np.append(np.subtract(0, DETECTING_AREA[:2]), self.ui_mask.shape[::-1])
# area = (-123, -55, 1157, 665)
return crop(self.ui_mask, area)
def ui_mask_os_in_map(self):
area = np.append(np.subtract(0, DETECTING_AREA[:2]),
self.ui_mask.shape[::-1])
# area = (-123, -55, 1157, 665)
return crop(UI_MASK_OS.image, area)
def handle_user_agreement(self, xp, hierarchy):
"""
For CN only.
CN client is bugged. User Agreement and Privacy Policy may popup again even you have agreed with it.
This method scrolls to the bottom and click AGREE.
Returns:
bool: If handled.
"""
if server.server == 'cn':
area_wait_results = self.get_for_any_ele([
XPS('//*[@text="sdk协议"]', xp, hierarchy),
XPS('//*[@content-desc="sdk协议"]', xp, hierarchy)
])
if area_wait_results is False:
return False
agree_wait_results = self.get_for_any_ele([
XPS('//*[@text="同意"]', xp, hierarchy),
XPS('//*[@content-desc="同意"]', xp, hierarchy)
])
start_padding_results = self.get_for_any_ele([
XPS('//*[@text="隐私政策"]', xp, hierarchy),
XPS('//*[@content-desc="隐私政策"]', xp, hierarchy),
XPS('//*[@text="用户协议"]', xp, hierarchy),
XPS('//*[@content-desc="用户协议"]', xp, hierarchy)
])
start_margin_results = self.get_for_any_ele([
XPS('//*[@text="请滑动阅读协议内容"]', xp, hierarchy),
XPS('//*[@content-desc="请滑动阅读协议内容"]', xp, hierarchy)
])
test_image_original = self.device.image
image_handle_crop = crop(
test_image_original,
(start_padding_results[2], 0, start_margin_results[2], 720))
# Image.fromarray(image_handle_crop).show()
sims = color_similarity_2d(image_handle_crop,
color=(182, 189, 202))
points = np.sum(sims >= 255)
if points == 0:
return False
sims_height = np.mean(sims, axis=1)
# pyplot.plot(sims_height, color='r')
# pyplot.show()
peaks, __ = find_peaks(sims_height, height=225)
if len(peaks) == 2:
peaks = (peaks[0] + peaks[1]) / 2
start_pos = [
(start_padding_results[2] + start_margin_results[2]) / 2,
float(peaks)
]
end_pos = [
(start_padding_results[2] + start_margin_results[2]) / 2,
area_wait_results[3]
]
logger.info("user agreement position find result: " +
', '.join('%.2f' % _ for _ in start_pos))
logger.info("user agreement area expect: " +
'x:963-973, y:259-279')
self.device.drag(start_pos,
end_pos,
segments=2,
shake=(0, 25),
point_random=(0, 0, 0, 0),
shake_random=(0, -5, 0, 5))
AGREE = Button(area=agree_wait_results,
color=(),
button=agree_wait_results,
name='AGREE')
self.device.click(AGREE)
return True