def insert_timestamp_header(sheet, col_index: int):
try:
sheet.update_cell(1, col_index, get_current_datetime())
except gspread_exceptions.IncorrectCellLabel:
print(
f"There was an issue inserting a timestamp at position: (1, {col_index}) for sheet: {sheet.title}"
)
def registration():
if request.method == 'POST':
user = {
'id': util.key_generator(),
'registration_time': util.get_current_datetime(),
'username': request.form.get('username'),
'email': request.form.get('email'),
'password': util.hash_password(request.form.get('password')),
'role': 'user'
}
data_handler.add_new_user(user)
return redirect(url_for('route_list'))
return render_template('registration.html',
page_title='Registration',
button_title='Registrate')
def new_question_comment(question_id=None):
if request.method == 'POST':
question_comment = {
'id': util.key_generator(),
'question_id': question_id,
'message': request.form.get('message'),
'submission_time': util.get_current_datetime(),
'edited_count': '0'
}
data_handler.add_new_question_comment(question_comment)
return redirect(url_for('view_question', question_id=question_id))
return render_template('add_edit_question_answer_comments.html',
page_title='Add comment to question',
button_title='Submit comment',
question_id=question_id)
def check():
if session.get('id') is None or session.get('limit') is None:
logout()
return False
if not session['id'].endswith('@teec.in.net') and not users.exists(
session['id']):
logout()
return False
dt = util.get_datetime_with_timezone(session['limit'], _STR_FORMAT,
datetime.timezone.utc)
current = util.get_current_datetime()
if dt <= current:
logout()
return False
return login(session['id'])
def main():
argparser = argparse.ArgumentParser(description=__doc__)
argparser.add_argument(
'-v', '--verbose',
action='store_true',
dest='debug',
help='print debug information')
argparser.add_argument(
'--host',
metavar='H',
default='localhost',
help='IP of the host server (default: localhost)')
argparser.add_argument(
'-p', '--port',
metavar='P',
default=2000,
type=int,
help='TCP port to listen to (default: 2000)')
argparser.add_argument(
'-a', '--autopilot',
action='store_true',
help='enable autopilot')
argparser.add_argument(
'-d', '--depth',
action='store_true',
help='enable depth camera')
argparser.add_argument(
'-l', '--lidar',
action='store_true',
help='enable Lidar')
argparser.add_argument(
'-q', '--quality-level',
choices=['Low', 'Epic'],
type=lambda s: s.title(),
default='Epic',
help='graphics quality level, a lower level makes the simulation run considerably faster.')
argparser.add_argument(
'-i', '--images-to-disk',
action='store_true',
dest='save_images_to_disk',
help='save images (and Lidar data if active) to disk')
argparser.add_argument(
'-c', '--carla-settings',
metavar='PATH',
dest='settings_filepath',
default=None,
help='Path to a "CarlaSettings.ini" file')
argparser.add_argument(
'-r', '--split_ratio',
default=0.8,
type=float,
help='train val split ratio')
argparser.add_argument(
'-e', '--episodes',
default=3,
type=int,
help='# of epsiodes to run')
argparser.add_argument(
'-f', '--frames',
default=300,
type=int,
help='# of frames per episode')
argparser.add_argument(
'--camera_rgb_width',
default=800,
type=int,
help='width of rgb camera')
argparser.add_argument(
'--camera_rgb_height',
default=600,
type=int,
help='height of rgb camera')
args = argparser.parse_args()
log_level = logging.DEBUG if args.debug else logging.INFO
logging.basicConfig(format='%(levelname)s: %(message)s', level=log_level)
logging.info('listening to server %s:%s', args.host, args.port)
current_datetime = get_current_datetime()
args.out_filename_format = 'data/' + current_datetime + '/episode_{:0>4d}/{:s}/{:0>6d}'
args.out_labelname_format = 'data/' + current_datetime + '/episode_{:0>4d}/label.pickle'
while True:
try:
run_carla_client(args)
print('Finished simulation.')
split_data(f'data/{current_datetime}', args.episodes, args.split_ratio)
print('Done.')
return
except TCPConnectionError as error:
logging.error(error)
time.sleep(1)
def login(uid):
session['id'] = uid
session['limit'] = (util.get_current_datetime() +
_LIMIT).strftime(_STR_FORMAT)
return True
def main(args):
actor_list = []
# In this tutorial script, we are going to add a vehicle to the simulation
# and let it drive in autopilot. We will also create a camera attached to
# that vehicle, and save all the images generated by the camera to disk.
try:
# First of all, we need to create the client that will send the requests
# to the simulator. Here we'll assume the simulator is accepting
# requests in the localhost at port 2000.
client = carla.Client('localhost', 2000)
client.set_timeout(2.0)
# Once we have a client we can retrieve the world that is currently
# running.
world = client.get_world()
world = client.load_world('Town04')
world.set_weather(carla.WeatherParameters.ClearNoon)
original_settings = world.get_settings()
settings = world.get_settings()
settings.fixed_delta_seconds = 0.1 # https://carla.readthedocs.io/en/latest/adv_synchrony_timestep/#time-step-limitations
settings.synchronous_mode = True
world.apply_settings(settings)
# The world contains the list blueprints that we can use for adding new
# actors into the simulation.
blueprint_library = world.get_blueprint_library()
# Now let's filter all the blueprints of type 'vehicle' and choose one
# at random. Exclude all bikes
vehicles = blueprint_library.filter('vehicle.*')
cars = [
v for v in vehicles
if int(v.get_attribute('number_of_wheels')) != 2
]
bp = random.choice(cars)
# A blueprint contains the list of attributes that define a vehicle's
# instance, we can read them and modify some of them. For instance,
# let's randomize its color.
if bp.has_attribute('color'):
color = random.choice(bp.get_attribute('color').recommended_values)
bp.set_attribute('color', color)
# Now we need to give an initial transform to the vehicle. We choose a
# random transform from the list of recommended spawn points of the map.
transform = random.choice(world.get_map().get_spawn_points())
# So let's tell the world to spawn the vehicle.
vehicle = world.spawn_actor(bp, transform)
# It is important to note that the actors we create won't be destroyed
# unless we call their "destroy" function. If we fail to call "destroy"
# they will stay in the simulation even after we quit the Python script.
# For that reason, we are storing all the actors we create so we can
# destroy them afterwards.
actor_list.append(vehicle)
print('created my %s' % vehicle.type_id)
# RGB Blueprint
camera_bp = blueprint_library.find('sensor.camera.rgb')
camera_bp.set_attribute(
'sensor_tick', '0.1') # take frame every 1/10 of sec i.e. 10fps
camera_bp.set_attribute('enable_postprocess_effects', 'True')
# Get current datetime for versioning
current_datetime = get_current_datetime()
# CenterRGB
camera_transform = carla.Transform(carla.Location(x=1.6, z=1.7))
center_rgb = world.spawn_actor(camera_bp,
camera_transform,
attach_to=vehicle)
actor_list.append(center_rgb)
print('created %s' % center_rgb.type_id)
center_rgb.listen(lambda image: image.save_to_disk(
f'data/{current_datetime}/CenterRGB/{image.frame:06d}.png', carla.
ColorConverter.Raw))
# LeftRGB
camera_transform = carla.Transform(
carla.Location(x=1.6, y=-1.25, z=1.7))
left_rgb = world.spawn_actor(camera_bp,
camera_transform,
attach_to=vehicle)
actor_list.append(left_rgb)
print('created %s' % left_rgb.type_id)
left_rgb.listen(lambda image: image.save_to_disk(
f'data/{current_datetime}/LeftRGB/{image.frame:06d}.png', carla.
ColorConverter.Raw))
# RightRGB
camera_transform = carla.Transform(carla.Location(x=1.6, y=1.25,
z=1.7))
right_rgb = world.spawn_actor(camera_bp,
camera_transform,
attach_to=vehicle)
actor_list.append(right_rgb)
print('created %s' % right_rgb.type_id)
right_rgb.listen(lambda image: image.save_to_disk(
f'data/{current_datetime}/RightRGB/{image.frame:06d}.png', carla.
ColorConverter.Raw))
# But the city now is probably quite empty, let's add a few more
# vehicles.
# transform.location += carla.Location(x=40, y=-3.2)
# transform.rotation.yaw = -180.0
num_of_npcs = 20
npc_list = []
for _ in range(num_of_npcs):
# transform.location.x += 8.0
npc_bp = random.choice(blueprint_library.filter('vehicle'))
npc_transform = random.choice(world.get_map().get_spawn_points())
# This time we are using try_spawn_actor. If the spot is already
# occupied by another object, the function will return None.
npc = world.try_spawn_actor(npc_bp, npc_transform)
if npc is not None:
actor_list.append(npc)
npc_list.append(npc)
npc.set_autopilot(True)
print('created %s' % npc.type_id)
label = {}
for _ in range(args.frames):
# TODO: 'remind' these guys to move!
vehicle.set_autopilot(True)
for a in npc_list:
a.set_autopilot(True)
world.tick()
w_frame = world.get_snapshot().frame
control_dict = generate_control_dict(vehicle.get_control(),
offset='center')
label[f'CenterRGB/{w_frame:06d}'] = control_dict
control_dict = generate_control_dict(vehicle.get_control(),
offset='left')
label[f'LeftRGB/{w_frame:06d}'] = control_dict
control_dict = generate_control_dict(vehicle.get_control(),
offset='right')
label[f'RightRGB/{w_frame:06d}'] = control_dict
# print("\nWorld's frame: %d" % w_frame)
# print(vehicle.get_control())
print('all frames collected')
with open(f'data/{current_datetime}/label.pickle', 'wb') as f:
pickle.dump(label, f, pickle.HIGHEST_PROTOCOL)
print('label saved')
finally:
world.apply_settings(original_settings)
print('destroying actors')
for actor in actor_list:
actor.destroy()
print('done.')
def main():
argparser = argparse.ArgumentParser()
argparser.add_argument('-r',
'--split_ratio',
default=0.8,
type=float,
help='train val split ratio')
argparser.add_argument('-t',
'--time_to_run',
default=5,
type=int,
help='time for data collection vehicle to run')
argparser.add_argument('-m',
'--map',
default='Town04',
type=str,
help='town to drive in')
argparser.add_argument('-e',
'--episodes',
default=3,
type=int,
help='# of epsiodes to run')
argparser.add_argument('-f',
'--frames',
default=100,
type=int,
help='# of frames')
args = argparser.parse_args()
actor_list = []
client = carla.Client('localhost', 2000)
client.set_timeout(2.0)
world = client.get_world()
world = client.load_world(args.map)
world.set_weather(carla.WeatherParameters.ClearNoon)
# Get current datetime for versioning
current_datetime = get_current_datetime()
m = world.get_map()
spawn_point = m.get_spawn_points()
# good_spawn_indices = [224, 186, 320, 321, 220, 221, 273, 307, 298, 338, 308, 343, 342, 230] # curves
# good_spawn_indices = [348, 223, 227, 370, 366, 328] # dotted lanes
# good_spawn_indices = list(range(100)) # just random
good_spawn_indices = [
224, 186, 320, 321, 220, 221, 273, 307, 298, 338, 308, 343, 342, 230
] + [348, 223, 227, 370, 366, 328, 132, 133, 305, 304, 371, 318, 315, 125]
spawn_index = 0
random.shuffle(good_spawn_indices)
blueprint_library = world.get_blueprint_library()
bp = blueprint_library.find('vehicle.tesla.model3')
# vehicle_transform = random.choice(m.get_spawn_points())
vehicle_transform = spawn_point[good_spawn_indices[spawn_index]]
# Spawn test vehicle at start pose
vehicle = world.spawn_actor(bp, vehicle_transform)
actor_list.append(vehicle)
print(f'created my {vehicle.type_id}')
vehicle.set_autopilot(True)
# RGB Blueprint
camera_bp = blueprint_library.find('sensor.camera.rgb')
camera_bp.set_attribute('enable_postprocess_effects', 'True')
# CenterRGB
camera_transform = carla.Transform(carla.Location(x=1.6, z=1.7))
center_rgb = world.spawn_actor(camera_bp,
camera_transform,
attach_to=vehicle)
actor_list.append(center_rgb)
print(f'created center {center_rgb.type_id}')
# LeftRGB
camera_transform = carla.Transform(carla.Location(x=1.6, y=-1.25, z=1.7))
left_rgb = world.spawn_actor(camera_bp,
camera_transform,
attach_to=vehicle)
actor_list.append(left_rgb)
print(f'created left {left_rgb.type_id}')
# RightRGB
camera_transform = carla.Transform(carla.Location(x=1.6, y=1.25, z=1.7))
right_rgb = world.spawn_actor(camera_bp,
camera_transform,
attach_to=vehicle)
actor_list.append(right_rgb)
print(f'created right {right_rgb.type_id}')
# Init sensor list
sensor_name = ['CenterRGB', 'LeftRGB', 'RightRGB']
# Set data parent folder
parent_dir = f'data'
# Create a synchronous mode context.
with CarlaSyncMode(world, center_rgb, left_rgb, right_rgb,
fps=10) as sync_mode:
for e in range(args.episodes):
print(f'Episode {e}')
episode_label = {}
episode_dir = f'episode_{e:0>4d}'
for f in trange(args.frames):
# Advance the simulation and wait for the data.
sensor_data = sync_mode.tick(timeout=5.0)
# No more stops at red light
if vehicle.is_at_traffic_light():
traffic_light = vehicle.get_traffic_light()
if traffic_light.get_state(
) == carla.TrafficLightState.Red:
traffic_light.set_state(carla.TrafficLightState.Green)
center_control_dict = generate_control_dict(
vehicle.get_control())
left_control_dict = generate_control_dict(
vehicle.get_control(), steer=0.25)
right_control_dict = generate_control_dict(
vehicle.get_control(), steer=-0.25)
control_data = [
center_control_dict, left_control_dict, right_control_dict
]
for name, control_dict, img_data in zip(
sensor_name, control_data, sensor_data[1:]):
label_key = f'{current_datetime}/{episode_dir}/{name}/{f:06d}'
filename = f'{parent_dir}/{label_key}.png'
img_data.save_to_disk(filename, carla.ColorConverter.Raw)
episode_label[label_key] = control_dict
# Data Augmentation
img = Image.open(filename)
translated_img, translated_steering_angle = translate_img(
img, control_dict['steer'], 100, 0)
control_dict['steer'] = translated_steering_angle
augmented_filename = f'{parent_dir}/{label_key}_augmented.png'
translated_img.save(augmented_filename)
episode_label[f'{label_key}_augmented'] = control_dict
# Save episode label dict.
with open(f'data/{current_datetime}/episode_{e:0>4d}/label.pickle',
'wb') as f:
pickle.dump(episode_label, f, pickle.HIGHEST_PROTOCOL)
# Move vehicle to another random spawn point for the next episode
vehicle.set_simulate_physics(False)
spawn_index += 1
vehicle.set_transform(spawn_point[good_spawn_indices[spawn_index]])
vehicle.set_simulate_physics(True)
print('data collection finished')
print('destroying actors.')
for actor in actor_list:
actor.destroy()
print('done.')