def main():
# Configure LSL streams
lsl_streams = StreamsObj()
# Create Tobii glasses Controller
tobiiglasses = TobiiGlassesController("192.168.71.50")
# Start Streaming
tobiiglasses.start_streaming()
print("Please wait ...")
time.sleep(1.0)
input("Press any key to start streaming")
old_time = time.time()
try:
while True:
data = tobiiglasses.get_data()
if time.time() - old_time > 0.020: # Send data every 20ms/50Hz
lsl_streams.sendData('mems', data['mems'])
lsl_streams.sendData('left_eye', data['left_eye'])
lsl_streams.sendData('right_eye', data['right_eye'])
lsl_streams.sendData('gp', data['gp'])
lsl_streams.sendData('gp3', data['gp3'])
old_time = time.time()
except Exception:
trace = traceback.format_exc()
print(trace)
finally:
tobiiglasses.stop_streaming()
tobiiglasses.close()
def main():
"""
How to connect with the tobii glasses
0. Automatic discovery of the device
TobiiGlassesController()
1. If you know the IPv6 addr of the tobii glasses
TobiiGlassesController("fe80::76fe:48ff:ff00:hell")
2. If you know the IPv6 addr of the tobii glasses and the net interface
of your host system (in case of multiple interfaces)
TobiiGlassesController("fe80::76fe:48ff:ff00:ff00%eth0")
3. If you know the IPv4 addr of the tobii glasses (WLAN or LAN connections)
TobiiGlassesController("192.168.71.50")
"""
TobiiGlassesController()
def main():
tobiiglasses = TobiiGlassesController()
tobiiglasses.start_streaming()
raw_input("Press a key to start streaming (1000 samples will be shown)")
for i in range(1000):
print "Head unit: %s" % tobiiglasses.get_data()['mems']
print "Left Eye: %s " % tobiiglasses.get_data()['left_eye']
print "Right Eye: %s " % tobiiglasses.get_data()['right_eye']
print "Gaze Position: %s " % tobiiglasses.get_data()['gp']
print "Gaze Position 3D: %s " % tobiiglasses.get_data()['gp3']
tobiiglasses.stop_streaming()
def demo(opt):
def find_ellipses_parallel(img):
gray_frame = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
retval, gray_frame = cv2.threshold(gray_frame, 170, 235, 0)
contours, hier = cv2.findContours(gray_frame, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
elps = []
for cnt in contours:
try:
elp = cv2.fitEllipse(cnt)
elps.append(elp)
except:
pass
return elps
os.environ['CUDA_VISIBLE_DEVICES'] = opt.gpus_str
opt.debug = max(opt.debug, 1)
Detector = detector_factory[opt.task]
detector = Detector(opt)
detector.pause = False
wait_signal = False
# Wait for the UDP message to start
wait_start_signal = wait_signal
if wait_start_signal:
import socket
from socket import gethostbyname
UDP_PORT_NO = 9013
UDP_IP_ADDRESS = gethostbyname("0.0.0.0")
serverSock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
serverSock.bind((UDP_IP_ADDRESS, UDP_PORT_NO))
while True:
print("Waiting for the start message...")
data, addr = serverSock.recvfrom(1024)
print("Message: " + data.decode())
if data.decode().startswith("START:"):
_, game_id, session = data.decode().split(':')
game_id = int(game_id)
#session = int (session)
print("Received game id %d." % (game_id))
break
# Decide the camera source
if opt.demo == 'tobii':
ipv4_address = "192.168.0.109"
cap = cv2.VideoCapture("rtsp://%s:8554/live/scene" % ipv4_address)
tobiiglasses = TobiiGlassesController(ipv4_address, video_scene=True)
video_freq = tobiiglasses.get_video_freq()
frame_duration = 1000.0 / float(video_freq)
tobiiglasses.start_streaming()
elif opt.demo == 'webcam' or \
opt.demo[opt.demo.rfind('.') + 1:].lower() in video_ext:
cap = cv2.VideoCapture(0 if opt.demo == 'webcam' else opt.demo)
# Check if camera opened successfully
if (cap.isOpened() == False):
print("Error opening video stream or file")
# Set up the threading mechanism for factobiiglasses.start_streaming() recognition and stopp signal receiving.
with concurrent.futures.ThreadPoolExecutor(max_workers=5) as pool:
# Wait for the UDP message to end
wait_stopp_signal = wait_signal
if wait_start_signal and wait_stopp_signal:
def wait_stopp():
while True:
print("Waiting for the end message...")
data, addr = serverSock.recvfrom(1024)
print("Message: " + data.decode())
if data.decode().startswith("STOPP:"):
break
return
udp_end_received = pool.submit(wait_stopp)
ret, img = cap.read()
future = pool.submit(find_ellipses_parallel, img)
# Setup the HTTP patch method
send_back = wait_signal
if wait_start_signal and send_back:
import requests
import time
ip = '192.168.0.58'
port = ':3000'
address = 'http://' + ip + port + '/game/' + str(game_id) + '/'
save_log = True
if wait_start_signal and save_log:
infolog = open("log_" + str(game_id) + ".txt", "w+")
infolog.write(str(datetime.datetime.now()))
infolog.write("\n")
infolog.write("START: ")
infolog.write("\n")
# Set up the face recognition
detection_cnt = 0
recognized = False
MA = 0
ma = 0
elps = []
head_degrees = np.array([0, 0, 0])
screen_probability = -1.0
tablet_probability = -1.0
while (cap.isOpened()):
data_update_ready = False
info["focus"]["robot"]["gaze_focused"] = False
info["focus"]["screen"]["gaze_focused"] = False
info["focus"]["tablet"]["gaze_focused"] = False
info["focus"]["robot"]["probability"] = -1.0
info["focus"]["screen"]["probability"] = -1.0
info["focus"]["tablet"]["probability"] = -1.0
#if opt.demo == 'tobii':
# data_gy = tobiiglasses.get_data()['mems']['gy']['gy']
#print(data_gy)
#nput()
# head_degrees = head_degrees + np.array(data_gy)
# print(head_degrees)
# Detect all the things in the scene
detection_cnt = detection_cnt + 1
ret, img = cap.read()
if detection_cnt % 8 == 0:
height, width = img.shape[:2]
if ret == True:
# Detect everything
centernet_results = detector.run(img)
detect_robot = True
if detect_robot:
if future.done():
elps = future.result()
future = pool.submit(find_ellipses_parallel, img)
# Draw everyting
draw_robot = True
if draw_robot:
margin = 2.6
for elp in elps:
(x, y), (MA, ma), angle = elp
if 100 < MA < 440 and 100 < ma < 330 and 80264 < np.pi * ma * MA < 270000:
cv2.ellipse(
img, ((x, y),
(MA * margin, ma * margin), angle),
(0, 255, 0), 3)
detect_gaze = True
if opt.demo == 'tobii' and detect_gaze:
data_gp = tobiiglasses.get_data()['gp']
data_pts = tobiiglasses.get_data()['pts']
data_gy = tobiiglasses.get_data()['mems']['gy']
data_ac = tobiiglasses.get_data()['mems']['ac']
data_lpd = tobiiglasses.get_data()['left_eye']['pd']
data_rpd = tobiiglasses.get_data()['right_eye']['pd']
offset = data_gp['ts'] / 1000000.0 - data_pts[
'ts'] / 1000000.0
gaze_detected = offset > 0.0 and offset <= frame_duration
if gaze_detected:
cv2.circle(img, (int(data_gp['gp'][0] * width),
int(data_gp['gp'][1] * height)),
30, (0, 0, 255), 2)
gaze_x = int(data_gp['gp'][0] * width)
gaze_y = int(data_gp['gp'][1] * height)
results = centernet_results["results"]
for j in [63, 64]:
for bbox in results[j]:
if bbox[4] > detector.opt.vis_thresh:
confidence = bbox[4]
name = coco_class_name[j - 1]
if name == "laptop" or name == "tv":
if (bbox[2] - bbox[0])**2 + (
bbox[3] -
bbox[1])**2 < screen_criteria:
gaze_on_tablet = True
add_coco_bbox(bbox,
j,
"tablet",
img,
conf=confidence,
show_txt=True)
else:
gaze_on_screen = True
add_coco_bbox(bbox,
j,
"screen",
img,
conf=confidence,
show_txt=True)
# Forming the sending informaiton
send_numbers = True
detect_gaze_on_robot = True
if detection_cnt % 8 == 0:
gaze_on_robot = False
if opt.demo == 'tobii' and detect_gaze and gaze_detected and detect_robot and draw_robot and detect_gaze_on_robot and elps is not []:
for elp in elps:
(x, y), (MA, ma), angle = elp
try:
#if 80264 <np.pi * ma *MA < 270000:
if 100 < MA < 440 and 100 < ma < 330 and 80264 < np.pi * ma * MA < 270000:
gaze_on_robot = ((gaze_y - y)**2 /
(ma * margin)**2 +
(gaze_x - x)**2 /
(MA * margin)**2 <= 1)
except ZeroDivisionError:
print(
"Zero Division happened, probabolly no face detected or detected wrong area."
)
if gaze_on_robot:
print("Gaze on robot")
gaze_on_screen = False
gaze_on_tablet = False
detect_gaze_on_object = True
if opt.demo == 'tobii' and detect_gaze and gaze_detected and not gaze_on_robot:
results = centernet_results["results"]
# tv63 and laptop 64
for j in [63, 64]:
for bbox in results[j]:
if bbox[4] > detector.opt.vis_thresh:
confidence = bbox[4]
name = coco_class_name[j - 1]
if name == "laptop" or name == "tv":
x_in_range = bbox[0] <= gaze_x <= bbox[
2] if bbox[2] >= bbox[0] else bbox[
2] <= gaze_x <= bbox[0]
y_in_range = bbox[1] <= gaze_y <= bbox[
3] if bbox[3] >= bbox[1] else bbox[
3] <= gaze_x <= bbox[1]
gaze_on_object = x_in_range and y_in_range
if gaze_on_object:
if (bbox[2] - bbox[0])**2 + (
bbox[3] -
bbox[1])**2 < screen_criteria:
gaze_on_tablet = True
tablet_probability = confidence
else:
gaze_on_screen = True
screen_probability = confidence
if gaze_on_tablet:
print("Gaze on tablet")
if gaze_on_screen:
print("Gaze on screen")
cv2.imshow("demo", img)
if not gaze_on_robot and not gaze_on_screen and not gaze_on_tablet:
print("Gaze on no where")
if screen_probability != None and tablet_probability != None:
data_update_ready = True
print("data upgrade", data_update_ready)
if send_numbers and data_update_ready: #and screen_probability == None and and tablet_coordinates None and tablet_probability is not None:
# Check whether the gaze is in the rectangle of the of the robot face
# Start
info["focus"]["robot"]["gaze_focused"] = bool(
gaze_on_robot)
info["focus"]["screen"]["gaze_focused"] = bool(
gaze_on_screen)
info["focus"]["tablet"]["gaze_focused"] = bool(
gaze_on_tablet)
info["focus"]["robot"]["probability"] = -1.0
info["focus"]["screen"]["probability"] = float(
screen_probability)
info["focus"]["tablet"]["probability"] = float(
tablet_probability)
if wait_start_signal and save_log:
infolog.write(str(datetime.datetime.now()))
infolog.write("\n")
infolog.write(json.dumps(info))
infolog.write("\n")
infolog.write(json.dumps(data_gp))
infolog.write("\n")
infolog.write(json.dumps(data_gy))
infolog.write("\n")
infolog.write(json.dumps(data_ac))
infolog.write("\n")
infolog.write(json.dumps(data_lpd))
infolog.write("\n")
infolog.write(json.dumps(data_rpd))
infolog.write("\n")
if send_back:
if not data_update_ready:
print("Not updated")
print(info)
r = requests.patch(address, data=json.dumps(info))
#print(r.status_code)
if cv2.waitKey(1) & 0xFF == ord('q'):
return
if wait_stopp_signal:
if udp_end_received.done():
if save_log:
infolog.write(str(datetime.datetime.now()))
infolog.write("\n")
infolog.write("END: ")
infolog.write("\n")
infolog.close()
cap.release()
cv2.destroyAllWindows()
return
bytes += self.stream.raw.read(1024)
a = bytes.find('\xff\xd8')
b = bytes.find('\xff\xd9')
if a != -1 and b != -1:
jpg = bytes[a:b + 2]
bytes = bytes[b + 2:]
img = cv2.imdecode(np.fromstring(jpg, dtype=np.uint8),
cv2.IMREAD_COLOR)
cv2.imshow('cam', img)
if cv2.waitKey(1) == 27:
exit(0)
except ThreadError:
self.thread_cancelled = True
def is_running(self):
return self.thread.isAlive()
def shut_down(self):
self.thread_cancelled = True
#block while waiting for thread to terminate
while self.thread.isAlive():
time.sleep(1)
return True
if __name__ == "__main__":
tobiiglasses = TobiiGlassesController()
url = "rtsp://" + tobiiglasses.address + ":8554/live/scene"
cam = Cam(url)
cam.start()
def demo(opt):
def find_ellipses_parallel(img):
gray_frame = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
retval, gray_frame = cv2.threshold(gray_frame, 170, 235, 0)
contours, hier = cv2.findContours(gray_frame, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
elps = []
for cnt in contours:
try:
elp = cv2.fitEllipse(cnt)
elps.append(elp)
except:
pass
return elps
os.environ['CUDA_VISIBLE_DEVICES'] = opt.gpus_str
opt.debug = max(opt.debug, 1)
Detector = detector_factory[opt.task]
detector = Detector(opt)
detector.pause = False
# Decide the camera source
if opt.demo == 'tobii':
ipv4_address = "192.168.0.109"
cap = cv2.VideoCapture("rtsp://%s:8554/live/scene" % ipv4_address)
tobiiglasses = TobiiGlassesController(ipv4_address, video_scene=True)
video_freq = tobiiglasses.get_video_freq()
frame_duration = 1000.0 / float(video_freq)
tobiiglasses.start_streaming()
elif opt.demo == 'webcam' or \
opt.demo[opt.demo.rfind('.') + 1:].lower() in config.video_ext:
cap = cv2.VideoCapture(0 if opt.demo == 'webcam' else opt.demo)
# Check if camera opened successfully
if (cap.isOpened() == False):
print("Error opening video stream or file")
ret, img = cap.read()
elps_candidates = find_ellipses_parallel(img)
# Set up the face recognition
detection_cnt = 0
recognized = False
MA = 0
ma = 0
elps = []
head_degrees = np.array([0, 0, 0])
# Read gaze from file
gaze_df = pd.read_csv('./gaze_labels.cvs', ',')
system_labels = []
print(gaze_df)
# Set up the recognition probability
screen_probability = -1.0
tablet_probability = -1.0
while (cap.isOpened()):
data_update_ready = False
info["focus"]["robot"]["gaze_focused"] = False
info["focus"]["screen"]["gaze_focused"] = False
info["focus"]["tablet"]["gaze_focused"] = False
info["focus"]["robot"]["probability"] = -1.0
info["focus"]["screen"]["probability"] = -1.0
info["focus"]["tablet"]["probability"] = -1.0
#if opt.demo == 'tobii':
# data_gy = tobiiglasses.get_data()['mems']['gy']['gy']
#print(data_gy)
#nput()
# head_degrees = head_degrees + np.array(data_gy)
# print(head_degrees)
# Detect all the things in the scene
detection_cnt = detection_cnt + 1
ret, img = cap.read()
if not ret:
break
height, width = img.shape[:2]
if detection_cnt % 1 == 0:
# Detect everything
centernet_results = detector.run(img)
detect_robot = True
if detect_robot:
elps = find_ellipses_parallel(img)
# Get gaze
# 10268th frame is when the game starts
gaze_x = gaze_df['gaze_x'][detection_cnt + 10268 - 1]
gaze_y = gaze_df['gaze_y'][detection_cnt + 10268 - 1]
# Draw everyting
draw_robot = True
if draw_robot:
margin = 2.6
for elp in elps:
(x, y), (MA, ma), angle = elp
if 120 < MA < 440 and 120 < ma < 330 and 80264 < np.pi * ma * MA < 270000:
cv2.ellipse(img, ((x, y),
(MA * margin, ma * margin), angle),
(0, 255, 0), 3)
gaze_detected = True
print("here")
if gaze_detected:
cv2.circle(img, (gaze_x, gaze_y), 30, (0, 0, 255), 2)
results = centernet_results["results"]
for j in [63, 64]:
for bbox in results[j]:
if bbox[4] > detector.opt.vis_thresh:
confidence = bbox[4]
name = config.coco_class_name[j - 1]
if name == "laptop" or name == "tv":
if (bbox[2] - bbox[0])**2 + (
bbox[3] - bbox[1])**2 < screen_criteria:
gaze_on_tablet = True
add_coco_bbox(bbox,
j,
"tablet",
img,
conf=confidence,
show_txt=True)
else:
gaze_on_screen = True
add_coco_bbox(bbox,
j,
"screen",
img,
conf=confidence,
show_txt=True)
# Forming the sending informaiton
detect_gaze_on_robot = True
if detection_cnt % 1 == 0:
gaze_on_screen = False
gaze_on_tablet = False
detect_gaze_on_object = True
results = centernet_results["results"]
# tv 63 and laptop 64
for j in [63, 64]:
for bbox in results[j]:
if bbox[4] > detector.opt.vis_thresh:
confidence = bbox[4]
name = config.coco_class_name[j - 1]
if name == "laptop" or name == "tv":
x_in_range = bbox[0] <= gaze_x <= bbox[2] if bbox[
2] >= bbox[0] else bbox[2] <= gaze_x <= bbox[0]
y_in_range = bbox[1] <= gaze_y <= bbox[3] if bbox[
3] >= bbox[1] else bbox[3] <= gaze_x <= bbox[1]
gaze_on_object = x_in_range and y_in_range
if gaze_on_object:
if (bbox[2] - bbox[0])**2 + (
bbox[3] -
bbox[1])**2 < screen_criteria:
gaze_on_tablet = True
tablet_probability = confidence
else:
gaze_on_screen = True
screen_probability = confidence
# Detect Screen and Tablet first and then the robot
gaze_on_robot = False
if not gaze_on_screen and not gaze_on_tablet and gaze_detected and detect_robot and draw_robot and detect_gaze_on_robot and elps is not []:
for elp in elps:
(x, y), (MA, ma), angle = elp
try:
#if 80264 <np.pi * ma *MA < 270000:
if 100 < MA < 440 and 100 < ma < 330 and 80264 < np.pi * ma * MA < 270000:
gaze_on_robot = ((gaze_y - y)**2 /
(ma * margin)**2 +
(gaze_x - x)**2 /
(MA * margin)**2 <= 1)
except ZeroDivisionError:
print(
"Zero Division happened, probabolly no face detected or detected wrong area."
)
if gaze_on_robot:
print("Gaze on robot")
system_labels.append("Robot")
if gaze_on_tablet:
print("Gaze on tablet")
system_labels.append("Tablet")
elif gaze_on_screen:
print("Gaze on screen")
system_labels.append("Screen")
cv2.imshow("demo", img)
out.write(img)
if not gaze_on_robot and not gaze_on_screen and not gaze_on_tablet:
print("Gaze on no where")
system_labels.append("No where")
if screen_probability != None and tablet_probability != None:
data_update_ready = True
print("data upgrade", data_update_ready)
if data_update_ready: #and screen_probability == None and and tablet_coordinates None and tablet_probability is not None:
# Check whether the gaze is in the rectangle of the of the robot face
# Start
info["focus"]["robot"]["gaze_focused"] = bool(gaze_on_robot)
info["focus"]["screen"]["gaze_focused"] = bool(gaze_on_screen)
info["focus"]["tablet"]["gaze_focused"] = bool(gaze_on_tablet)
info["focus"]["robot"]["probability"] = -1.0
info["focus"]["screen"]["probability"] = float(
screen_probability)
info["focus"]["tablet"]["probability"] = float(
tablet_probability)
#print(r.status_code)
if cv2.waitKey(1) & 0xFF == ord('q'):
return
out.release()
df = pd.DataFrame(system_labels)
df.to_csv('./system_labels.cvs')
def main(): TobiiGlassesController() """
def main():
tobiiglasses = TobiiGlassesController("192.168.71.50")
print(tobiiglasses.get_battery_status())
#Get the bounds of the viewable range
print("Enter x upperbound:")
x_upper = float(input())
print("Enter x lowerbound:")
x_lower = float(input())
print("Enter y upperbound:")
y_upper = float(input())
print("Enter y lowerbound:")
y_lower = float(input())
print("Enter time to run in seconds:")
tt = int(input())
tobiiglasses.start_streaming()
print("Please wait ...")
time.sleep(3.0)
for i in range(tt):
time.sleep(1.0)
# print("Head unit: %s" % tobiiglasses.get_data()['mems'])
# print("Left Eye: %s " % tobiiglasses.get_data()['left_eye'])
# print("Right Eye: %s " % tobiiglasses.get_data()['right_eye'])
# print("Gaze Position: %s " % tobiiglasses.get_data()['gp'])
x_pos = tobiiglasses.get_data()['gp']['gp'][0]
y_pos = tobiiglasses.get_data()['gp']['gp'][1]
print("Test number %s " % i)
print("X Position: %s " % x_pos)
print("Y Position: %s " % y_pos)
#if out of bounds in the x axis
if (x_pos > x_upper or x_pos < x_lower):
print('X out of bounds')
print('\a') #makes a beeping noise
elif (y_pos > y_upper or y_pos < y_lower):
print('Y out of bounds')
print('\a') #makes a beeping noise
else:
print('In bounds')
print("Gaze Position 3D: %s " % tobiiglasses.get_data()['gp3'])
tobiiglasses.stop_streaming()
tobiiglasses.close()
def main():
tobiiglasses = TobiiGlassesController()
print tobiiglasses.get_battery_info()
print tobiiglasses.get_storage_info()
if tobiiglasses.is_recording():
rec_id = tobiiglasses.get_current_recording_id()
tobiiglasses.stop_recording(rec_id)
project_name = raw_input("Please insert the project's name: ")
project_id = tobiiglasses.create_project(project_name)
participant_name = raw_input("Please insert the participant's name: ")
participant_id = tobiiglasses.create_participant(project_id,
participant_name)
calibration_id = tobiiglasses.create_calibration(project_id,
participant_id)
raw_input(
"Put the calibration marker in front of the user, then press enter to calibrate"
)
tobiiglasses.start_calibration(calibration_id)
res = tobiiglasses.wait_until_calibration_is_done(calibration_id)
if res is False:
print("Calibration failed!")
exit(1)
recording_id = tobiiglasses.create_recording(participant_id)
print "Important! The recording will be stored in the SD folder projects/%s/recordings/%s" % (
project_id, recording_id)
raw_input("Press enter to start recording")
tobiiglasses.start_recording(recording_id)
tobiiglasses.send_event("start_recording", "Start of the recording ")
raw_input("Press enter to stop recording")
tobiiglasses.send_event("stop_recording",
"Stop of the recording " + str(recording_id))
tobiiglasses.stop_recording(recording_id)
if res is False:
print("Recording failed!")
exit(1)
from tobiiglassesctrl import TobiiGlassesController
import cv2 as cv
import numpy as np
import sys
import time
import json
address = "192.168.71.50"
tobiiglasses = TobiiGlassesController(address)
# getting livestream video with opencv
address_rtsp = "rtsp://" + address + ":8554/live/scene"
vcap = cv.VideoCapture(address_rtsp)
#save video output
out = cv.VideoWriter('output.avi', cv.cv.CV_FOURCC(*'MJPG'), 20.0,
(int(vcap.get(3)), int(vcap.get(4))))
# calibration
if tobiiglasses.is_recording():
rec_id = tobiiglasses.get_current_recording_id()
tobiiglasses.stop_recording(rec_id)
project_name = raw_input("Please insert the project's name: ")
project_id = tobiiglasses.create_project(project_name)
participant_name = raw_input("Please insert the participant's name: ")
participant_id = tobiiglasses.create_participant(project_id, participant_name)
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>
import cv2
import numpy as np
if hasattr(__builtins__, 'raw_input'):
input = raw_input
from tobiiglassesctrl import TobiiGlassesController
ipv4_address = "192.168.71.50"
tobiiglasses = TobiiGlassesController(ipv4_address, video_scene=True)
project_id = tobiiglasses.create_project("Test live_scene_and_gaze.py")
participant_id = tobiiglasses.create_participant(project_id,
"participant_test")
calibration_id = tobiiglasses.create_calibration(project_id, participant_id)
input(
"Put the calibration marker in front of the user, then press enter to calibrate"
)
tobiiglasses.start_calibration(calibration_id)
res = tobiiglasses.wait_until_calibration_is_done(calibration_id)
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>
import av
import cv2
import numpy as np
from tobiiglassesctrl import TobiiGlassesController
ipv4_address = "192.168.100.10"
tobiiglasses = TobiiGlassesController(ipv4_address)
video = av.open("rtsp://%s:8554/live/scene" % ipv4_address, "r")
tobiiglasses.start_streaming()
try:
for packet in video.demux():
for frame in packet.decode():
if isinstance(frame, av.video.frame.VideoFrame):
#print(frame.pts)
img = frame.to_ndarray(format='bgr24')
height, width = img.shape[:2]
data_gp = tobiiglasses.get_data()['gp']
if data_gp['ts'] > 0:
cv2.circle(img, (int(data_gp['gp'][0] * width),
int(data_gp['gp'][1] * height)), 60,
def main():
#Configure LSL streams
lsl_streams = StreamsObj()
#Create Tobii glasses Controller
tobiiglasses = TobiiGlassesController("192.168.71.50")
print("Sampling frequency: ", tobiiglasses.get_et_freq())
print(tobiiglasses.get_battery_status())
#Calibrate
# calibration(tobiiglasses)
#Start Streaming
tobiiglasses.start_streaming()
print("Please wait ...")
time.sleep(3.0)
input("Press any key to start streaming")
current_gidx = -9999
startTime = time.time()
old_time = time.time()
time.sleep(0.1)
try:
while True:
data = tobiiglasses.get_data()
#Send data to LSL only there is a new data point
if current_gidx < data['gp']['gidx']:
current_gidx = data['gp']['gidx']
print(data['gp'])
#Send data
lsl_streams.sendData('left_eye', data['left_eye'])
lsl_streams.sendData('right_eye', data['right_eye'])
lsl_streams.sendData('gp', data['gp'])
lsl_streams.sendData('gp3', data['gp3'])
#Print Battery status
# print(tobiiglasses.get_battery_status())
if time.time() - old_time > 0.02: #Send data every 20ms
lsl_streams.sendData('mems', data['mems'])
old_time = time.time()
except Exception as e:
print(e)
print("Closing Tobii")
trace = traceback.format_exc()
print(trace)
finally:
file.close()
tobiiglasses.stop_streaming()
tobiiglasses.close()
print("Closing programme")
def main():
tobiiglasses = TobiiGlassesController("192.168.71.50")
print(tobiiglasses.get_battery_status())
tobiiglasses.start_streaming()
print("Please wait ...")
time.sleep(3.0)
for i in range(1000):
print("Head unit: %s" % tobiiglasses.get_data()['mems'])
print("Left Eye: %s " % tobiiglasses.get_data()['left_eye'])
print("Right Eye: %s " % tobiiglasses.get_data()['right_eye'])
print("Gaze Position: %s " % tobiiglasses.get_data()['gp'])
print("Gaze Position 3D: %s " % tobiiglasses.get_data()['gp3'])
tobiiglasses.stop_streaming()
tobiiglasses.close()