def callback(self, data):
try:
cv_image = self.bridge.imgmsg_to_cv2(data, "bgr8")
except CvBridgeError as e:
print(e)
center_dict = {'blue': 'None', 'red': 'None', 'green': 'None'}
blue_center = Int64MultiArray()
red_center = Int64MultiArray()
green_center = Int64MultiArray()
image, center_dict, blue_center, red_center, green_center = self.image_centers(
cv_image, center_dict, blue_center, red_center, green_center)
try:
blue_direction = direction(blue_center, self.data_K, "blue")
except:
pass
try:
red_direction = direction(red_center, self.data_K, "red")
except:
pass
try:
green_direction = direction(green_center, self.data_K, "green")
except:
pass
try:
self.image_pub.publish(self.bridge.cv2_to_imgmsg(cv_image, "bgr8"))
if blue_direction.layout.dim[0].size != 0:
self.marker_blue.publish(blue_direction)
if red_direction.layout.dim[0].size != 0:
self.marker_red.publish(red_direction)
if green_direction.layout.dim[0].size != 0:
self.marker_green.publish(green_direction)
except CvBridgeError as e:
print(e)
def check_goban_moved(prev_corners, current_corners):
"""Comprobamos si es posible el movimiento de tablero detectado.
:Param prev_corners: corners detectados anteriormente
:Type prev_corners: list
:Param current_corners: corners detectados actualmente
:Type current_corners: list
:Return: True si el tablero se ha movido
:Rtype: bool """
if not prev_corners or not current_corners:
return True
# dist_min_of_movement = get_max_edge(prev_corners)/(2*GOBAN_SIZE)
" Comprobamos primero si existe mucho movimiento. "
dist = []
directions = []
for i in xrange(NUM_EDGES):
dist.append(abs(distance(prev_corners[i], current_corners[i])))
directions.append(direction(prev_corners[i], current_corners[i]))
f = lambda x: x>1
dist_list = filter(f, dist)
if len(dist_list) > 2:
# min_mov=1/3 square TODO check impossible movement (Direcction)
min_mov = get_max_edge(prev_corners)/((GOBAN_SIZE-1)*3.0)
dist_list.sort()
if (dist_list[-1] - dist_list[0]) < min_mov:
return check_directions(directions)
elif (dist_list[-1] - dist_list[-3]) < min_mov:
return check_directions(directions)
else:
return False
else:
return False
def check_goban_moved(prev_corners, current_corners):
"""Comprobamos si es posible el movimiento de tablero detectado.
:Param prev_corners: corners detectados anteriormente
:Type prev_corners: list
:Param current_corners: corners detectados actualmente
:Type current_corners: list
:Return: True si el tablero se ha movido
:Rtype: bool """
if not prev_corners or not current_corners:
return True
dist_min_of_movement = get_max_edge(prev_corners) / (2 * GOBAN_SIZE)
" Comprobamos primero si existe mucho movimiento. "
dist = []
directions = []
for i in xrange(NUM_EDGES):
dist.append(abs(distance(prev_corners[i], current_corners[i])))
directions.append(direction(prev_corners[i], current_corners[i]))
f = lambda x: x > 1
dist_list = filter(f, dist)
if len(dist_list) > 2:
# min_mov=1/3 square TODO check impossible movement (Direcction)
min_mov = get_max_edge(prev_corners) / ((GOBAN_SIZE - 1) * 3.0)
dist_list.sort()
if (dist_list[-1] - dist_list[0]) < min_mov:
return check_directions(directions)
elif (dist_list[-1] - dist_list[-3]) < min_mov:
return check_directions(directions)
else:
return False
else:
return False
def get_velocity(filename, unique_id, savename):
data = pd.read_csv(filename, encoding='utf-8')
# extract columns
hit_x = data['hit_x']
hit_y = data['hit_y']
hit_area = data['hit_area']
landing_x = data['landing_x']
landing_y = data['landing_y']
landing_area = data['landing_area']
time = data['time']
lose_reason = data['lose_reason']
ball_type = data['type']
data_num = data.shape[0]
velocity = []
direction = []
for i in range(data_num):
if type(lose_reason[i]) != float:
velocity.append('0')
direction.append('')
continue
# velocity
v = functions.velocity(time[i], time[i + 1], hit_x[i], hit_y[i],
landing_x[i], landing_y[i])
velocity.append(v)
# direction (first para means diagonal angle)
d = functions.direction(30, hit_x[i], hit_y[i], hit_area[i],
landing_x[i], landing_y[i], landing_area[i])
direction.append(d)
data['velocity'] = velocity
data['direction'] = direction
data.insert(loc=0, column='unique_id', value=unique_id)
data.to_csv(savename, index=False, encoding='utf-8')
npoints = nose_point(frame, predictor, detector)
w, h = 25, 20
multiple = 1
if npoints != None:
if start:
x, y = npoints
start = False
else:
cv2.rectangle(frame, (x - w, y - h), (x + w, y + h),
GREEN_COLOR, 2)
cv2.line(frame, (x, y), npoints, BLUE_COLOR, 2)
dir = direction(npoints, (x, y), w, h)
drag = 17
scrollDrag = 1
# Diagonal moves
if dir == 'leftdown':
if not SCROLL_MODE:
pyautogui.moveRel(-drag, drag)
elif dir == 'leftup':
if not SCROLL_MODE:
pyautogui.moveRel(-drag, -drag)
elif dir == 'rightdown':
if not SCROLL_MODE:
pyautogui.moveRel(drag, drag)
elif dir == 'rightup':
if not SCROLL_MODE: