def process_event(event):
"""Pretty prints events.
Prints all events that occur with two spaces between each new
conversation and a single space between turns of a conversation.
Args:
event(event.Event): The current event to process.
"""
if event.type == EventType.ON_CONVERSATION_TURN_STARTED:
print()
print(event)
if (event.type == EventType.ON_CONVERSATION_TURN_FINISHED and
event.args and not event.args['with_follow_on_turn']):
print()
if event.type == EventType.ON_DEVICE_ACTION:
for command, params in event.actions:
print('Do command', command, 'with params', str(params))
if command == 'action.devices.commands.OnOff':
threads[1].join()
if command == 'luxo.command.LookAtMe':
t = vision.Camera(feed, 0)
threads.append(t)
t.start()
def look_at_object(subject):
if len(threads) > 0:
threads[0].join()
del threads[0]
if subject == 'me':
t = vision.Camera(feed, 0)
threads.append(t)
t.start()
return statement('Looking at you')
if subject == 'this':
t = vision.Camera(feed, 2)
threads.append(t)
t.start()
return statement('Looking for it')
if subject == 'my desk':
t = vision.Camera(feed, 2)
threads.append(t)
t.start()
return statement('Looking at your desk')
def __init__(self, sid, log):
import vision
self.log = log
# Initialise camera
self.cam = vision.Camera(sid=sid, log=log)
# Initialise servos
self.servo = vision.Servo(sid=sid,
log=log,
img_width=self.cam.cam.resolution[0],
img_height=self.cam.cam.resolution[1])
# Should return data dictionary and the modified frame to the drawing utilities.
return data, modified_frame
# Test tracking objects of certain color
if __name__ == '__main__':
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("pitch", help="[0] Main pitch, [1] Secondary pitch")
# parser.add_argument("color", help="The color to adjust")
args = parser.parse_args()
pitch_number = int(args.pitch)
capture = vision.Camera(pitch=pitch_number)
#capture = cv2.VideoCapture('output.avi')
calibration = tools.get_colors(pitch=pitch_number)
croppings = tools.get_croppings(pitch=pitch_number)
tracker = MyTracker(calibration=calibration, pitch_number=pitch_number)
while True:
frame = capture.get_frame()
#re,frame = capture.read()
data, modified_frame = tracker.get_world_state(frame)
cv2.imshow('Tracker', modified_frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
viz.defaultAxisSetup(ax) R = rb.roty(math.pi/2.0) @ rb.rotz(-math.pi/2.0) print(R) line1 = vsn.Line(ax, [6,3,0], [6,3,2], color = np.array([255, 0, 0])) line2 = vsn.Line(ax, [6,3,2], [7,4,2], color = np.array([0, 255, 0])) line3 = vsn.Line(ax, [7,4,2], [7,4,0], color = np.array([0,0,255])) line4 = vsn.Line(ax, [7,4,0], [6,3,0], color = np.array([255,0, 255])) print(R) t = np.array([1,3,1]) p1 = np.array([6.0, 4.0, 2.0, 1.0]) viz.plotHomgPoint(ax, p1) intrinsic = np.array([[1500, 0, 640], [0, 1500, 512], [0,0,1]]) cam1 = vsn.Camera(ax, R, t, intrinsic,name = "c") cam1.drawBody() cam1.takePicture([line1, line2, line3, line4]) cam1.showNormalizedImagePlane(ax) #ax.scatter(2,2,2) plt.show()
if __name__ == '__main__':
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("pitch", help="[0] Main pitch, [1] Secondary pitch")
args = parser.parse_args()
pitch_number = int(args.pitch)
# Initialize calibration window
colors = ['red', 'blue', 'bright_green', 'pink', 'yellow']
calibration = tools.get_colors(pitch=pitch_number)
print calibration['yellow']
# Initializecamera
cam = vision.Camera(pitch=pitch_number)
auto_brightness = True
settings = calibration['camera']
desired = 50
while (auto_brightness):
print "Getting best brightness"
best_brightness = 0
best_distance = 100
for test_brightness in range(100):
settings['brightness'] = test_brightness
# Update camera settings
print(R2)
print("t1")
print(t1)
print("t2")
print(t2)
R = rb.roty(math.pi / 2)
T = rb.makeTrans(R1, t1)
print("T")
print(T)
print("Norm of t:")
print(np.linalg.norm(t1))
cam1 = vsn.Camera(ax)
cam2 = vsn.Camera(ax, R2, t1)
s1 = np.array([0.0098, 0.1004, 1.0])
s2 = np.array([0.1920, 0.1078, 1.0])
line1 = np.concatenate((s1, np.array([.0, .0, .0])))
l2 = R2.transpose() @ s2
l2_dash = -R2.transpose() @ (np.cross(t1, s2))
print("l2")
print(l2)
print("l2 dash")
print(l2_dash)
line2 = np.hstack((l2, l2_dash))
