def test_continue_experiment(self):
recording = Recording(name_to_save='Test1',
continue_experiment=False,
save_images=True)
# A just started case should return the continue experiment case
self.assertEqual(recording._continue_experiment(True)[1], 1)
# If you don't want to continue, should return also one
self.assertEqual(recording._continue_experiment(False)[1], 1)
from carla.driving_benchmark.experiment import Experiment
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
# After writing two experiments it should return 2, so you could start writing os pos 3
self.assertEqual(recording._continue_experiment(True)[1], 3)
# If you dont want to continue, should return also one
self.assertEqual(recording._continue_experiment(False)[1], 1)
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(200, 88)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
if self._city_name == 'Town01':
poses_tasks = self._poses_town01()
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
else:
poses_tasks = self._poses_town02()
vehicles_tasks = [0, 0, 0, 15]
pedestrians_tasks = [0, 0, 0, 50]
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
#weather=14
#poses = [[54, 60]]
#poses=[[37,76]]
#poses = [[80, 29]]
#poses = [[50,43]]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather)
conditions.set(SynchronousMode=True)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1)
experiments_vector.append(experiment)
return experiments_vector
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depends on the selected Town.
"""
# We check the town, based on that we define the town related parameters
# The size of the vector is related to the number of tasks, inside each
# task there is also multiple poses ( start end, positions )
if self._city_name == 'Town01':
poses_tasks = [[[7, 3]], [[138, 17]], [[140, 134]], [[140, 134]]]
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
else:
poses_tasks = [[[4, 2]], [[37, 76]], [[19, 66]], [[19, 66]]]
vehicles_tasks = [0, 0, 0, 15]
pedestrians_tasks = [0, 0, 0, 50]
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
# Based on the parameters, creates a vector with experiment objects.
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather
)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(
Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1
)
experiments_vector.append(experiment)
return experiments_vector
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depends on the selected Town.
"""
# We check the town, based on that we define the town related parameters
# The size of the vector is related to the number of tasks, inside each
# task there is also multiple poses ( start end, positions )
if self._city_name == 'Town01':
poses_tasks = [[[7, 3]], [[138, 17]], [[140, 134]], [[140, 134]]]
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
else:
poses_tasks = [[[4, 2]], [[37, 76]], [[19, 66]], [[19, 66]]]
vehicles_tasks = [0, 0, 0, 15]
pedestrians_tasks = [0, 0, 0, 50]
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
# Based on the parameters, creates a vector with experiment objects.
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather
)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(
Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1
)
experiments_vector.append(experiment)
return experiments_vector
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
if self._city_name == 'Town01':
poses_tasks = self._poses_town01()
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
else:
poses_tasks = self._poses_town02()
vehicles_tasks = [0, 0, 0, 15]
pedestrians_tasks = [0, 0, 0, 50]
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather
)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(
Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1
)
experiments_vector.append(experiment)
return experiments_vector
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
if self._city_name == 'Town01':
poses_tasks = self._poses_town01()
vehicles_tasks = [25]
pedestrians_tasks = [25]
else:
poses_tasks = self._poses_town02()
vehicles_tasks = [0, 25]
pedestrians_tasks = [0, 25]
experiments_vector = []
#weathers = [1,3,6,8]
for weather in self.weathers:
#prinst(weather , vehicles_tasks)
for scenario in range(len(vehicles_tasks)):
for iteration in range(len(poses_tasks)):
#print(f"interation : {iteration} , scenario:{scenario}")
poses = poses_tasks[iteration]
#print("poses re",poses)
vehicles = vehicles_tasks[scenario]
#print("Vehicles: ",vehicles)
pedestrians = pedestrians_tasks[scenario]
#print("pedestrians: ",pedestrians)
conditions = CarlaSettings()
conditions.set(SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1)
experiments_vector.append(experiment)
return experiments_vector
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('rgb')
camera.set(FOV=90)
camera.set_image_size(300, 300)
camera.set_position(0.2, 0.0, 0.85)
camera.set_rotation(-3.0, 0, 0)
poses_tasks = self._poses()
vehicles_tasks = [0, 0, 0, 15]
pedestrians_tasks = [0, 0, 0, 50]
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather,
QualityLevel='Epic'
)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(
Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1
)
experiments_vector.append(experiment)
return experiments_vector
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('rgb')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
poses_tasks = self._poses()
vehicles_tasks = [0, 15, 70]
pedestrians_tasks = [0, 50, 150]
task_names = ['empty', 'normal', 'cluttered']
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather)
conditions.set(DisableTwoWheeledVehicles=True)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(Conditions=conditions,
Poses=poses,
Task=iteration,
TaskName=task_names[iteration],
Repetitions=1)
experiments_vector.append(experiment)
return experiments_vector
def test_write_summary_results(self):
"""
Test writting summary results.
"""
from carla.driving_benchmark.experiment import Experiment
recording = Recording(name_to_save='Test1',
continue_experiment=False,
save_images=True)
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
with open(os.path.join(recording._path, 'summary.csv'), 'r') as f:
header = f.readline().split(',')
# Assert if header is header
self.assertIn('exp_id', header)
self.assertEqual(len(header), len(recording._dict_summary))
# Assert if there is something writen in the row
written_row = f.readline().split(',')
# Assert if the number of collums is correct
self.assertEqual(len(written_row), len(recording._dict_summary))
def teste_write_measurements_results(self):
import os
from carla.driving_benchmark.experiment import Experiment
from carla.carla_server_pb2 import Measurements
from carla.carla_server_pb2 import Control
recording = Recording(name_to_save='Test1',
continue_experiment=False,
save_images=True)
reward_vec = [Measurements().player_measurements for x in range(20)]
control_vec = [Control() for x in range(25)]
recording.write_measurements_results(experiment=Experiment(),
rep=1,
pose=[24, 32],
reward_vec=reward_vec,
control_vec=control_vec)
with open(os.path.join(recording._path, 'measurements.csv'), 'r') as f:
header = f.readline().split(',')
#Assert if header is header
self.assertIn('exp_id', header)
self.assertEqual(len(header), len(recording._dict_measurements))
#Assert if there is something writen in the row
written_row = f.readline().split(',')
#Assert if the number of collums is correct
self.assertEqual(len(written_row),
len(recording._dict_measurements))
def _generate_test_case(self, poses_to_test):
recording = Recording(name_to_save='TestMetric'
, continue_experiment=False, save_images=True
)
from carla.driving_benchmark.experiment import Experiment
from carla.carla_server_pb2 import Measurements
from carla.carla_server_pb2 import Control
for pose in poses_to_test:
experiment = Experiment()
recording.write_summary_results(experiment=experiment, pose=pose, rep=1,
path_distance=200, remaining_distance=0,
final_time=0.2, time_out=49, result=1)
reward_vec = [Measurements().player_measurements for x in range(25)]
control_vec = [Control() for x in range(25)]
recording.write_measurements_results(experiment=experiment,
rep=1, pose=pose, reward_vec=reward_vec,
control_vec=control_vec)
return recording._path
def test_write_summary_results_good_order(self):
"""
Test if the summary results are writen in the same order on a new process
"""
from carla.driving_benchmark.experiment import Experiment
recording = Recording(name_to_save='Test_good_order',
continue_experiment=False,
save_images=True)
for _ in range(0, 10):
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
recording = Recording(name_to_save='Test_good_order',
continue_experiment=True,
save_images=True)
for _ in range(0, 10):
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
recording = Recording(name_to_save='Test_good_order',
continue_experiment=True,
save_images=True)
for _ in range(0, 10):
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
recording = Recording(name_to_save='Test_good_order',
continue_experiment=True,
save_images=True)
for _ in range(0, 10):
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
def test_get_pose_and_experiment_corner(self):
"""
Test getting the pose from multiple cases.
"""
from carla.driving_benchmark.experiment import Experiment
recording = Recording(name_to_save='Test1',
continue_experiment=False,
save_images=True)
pose, experiment = recording.get_pose_and_experiment(1)
# An starting experiment should return one
self.assertEqual(pose, 0)
self.assertEqual(experiment, 0)
pose, experiment = recording.get_pose_and_experiment(2)
self.assertEqual(pose, 0)
self.assertEqual(experiment, 0)
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
pose, experiment = recording.get_pose_and_experiment(1)
print(pose, experiment)
self.assertEqual(pose, 0)
self.assertEqual(experiment, 1)
pose, experiment = recording.get_pose_and_experiment(2)
print(pose, experiment)
# An starting experiment should return one
self.assertEqual(pose, 1)
self.assertEqual(experiment, 0)
pose, experiment = recording.get_pose_and_experiment(3)
print(pose, experiment)
# An starting experiment should return one
self.assertEqual(pose, 1)
self.assertEqual(experiment, 0)
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
pose, experiment = recording.get_pose_and_experiment(2)
self.assertEqual(pose, 0)
self.assertEqual(experiment, 1)
pose, experiment = recording.get_pose_and_experiment(3)
self.assertEqual(pose, 2)
self.assertEqual(experiment, 0)
def test_get_pose_and_experiment(self):
"""
Test getting the pose and the experiment from a previous executed benchmark
"""
recording = Recording(name_to_save='Test1',
continue_experiment=False,
save_images=True)
from carla.driving_benchmark.experiment import Experiment
pose, experiment = recording.get_pose_and_experiment(25)
# An starting experiment should return zero zero
self.assertEqual(pose, 0)
self.assertEqual(experiment, 0)
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
pose, experiment = recording.get_pose_and_experiment(25)
self.assertEqual(pose, 2)
self.assertEqual(experiment, 0)
for _ in range(23):
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
pose, experiment = recording.get_pose_and_experiment(25)
self.assertEqual(pose, 0)
self.assertEqual(experiment, 1)
for _ in range(23):
recording.write_summary_results(experiment=Experiment(),
pose=[24, 32],
rep=1,
path_distance=200,
remaining_distance=0,
final_time=0.2,
time_out=49,
result=1)
pose, experiment = recording.get_pose_and_experiment(25)
self.assertEqual(pose, 23)
self.assertEqual(experiment, 1)
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
if self._city_name == 'Town01':
poses_tasks = self._poses_town01()
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
elif self._city_name == 'Town02':
poses_tasks = self._poses_town02()
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
elif self._city_name == 'Town01_nemesis':
poses_tasks = self._poses_town01_nemesis()
vehicles_tasks = [0, 0, 0, 0]
pedestrians_tasks = [0, 0, 0, 0]
elif self._city_name == 'Town02_nemesis':
poses_tasks = self._poses_town02_nemesis()
vehicles_tasks = [0, 0, 0, 0]
pedestrians_tasks = [0, 0, 0, 0]
elif self._city_name == 'Town01_mini':
poses_tasks = self._poses_town01_mini()
vehicles_tasks = [0, 0, 0, 0]
pedestrians_tasks = [0, 0, 0, 0]
experiments_vector = []
"""repeating experiment"""
num_iters = 171
weathers_iters = [1] * num_iters
for weather in weathers_iters:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1)
experiments_vector.append(experiment)
return experiments_vector
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
if self._city_name == 'Town01':
if self._subset == 'keep_lane':
poses_tasks = [self._poses_town01()[0]]
vehicles_tasks = [0]
pedestrians_tasks = [0]
elif self._subset == 'one_turn':
poses_tasks = [self._poses_town01()[1]]
vehicles_tasks = [0]
pedestrians_tasks = [0]
elif self._subset == 'keep_lane_one_turn':
poses_tasks = self._poses_town01()[:2]
vehicles_tasks = [0, 0]
pedestrians_tasks = [0, 0]
elif self._subset == 'no_dynamic_objects':
poses_tasks = self._poses_town01()[:3]
vehicles_tasks = [0, 0, 0]
pedestrians_tasks = [0, 0, 0]
elif self._subset is None:
poses_tasks = self._poses_town01()
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
else:
raise ValueError(
"experiments-subset must be keep_lane or keep_lane_one_turn or no_dynamic_objects or None"
)
else:
raise ValueError("city must be Town01 for training")
experiments_vector = []
for i, iteration in enumerate(range(len(poses_tasks))):
for weather in self.weathers:
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1)
experiments_vector.append(experiment)
return experiments_vector
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
if self._task == 'go-straight':
task_select = 0
elif self._task == 'turn-right':
task_select = 1
elif self._task == 'turn-left':
task_select = 2
elif self._task == 'go-straight-2':
task_select = 3
elif self._task == 'turn-right-2':
task_select = 4
elif self._task == 'turn-left-2':
task_select = 5
if self._city_name == 'Town01':
poses_tasks = self._poses_town01()
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
elif self._city_name == 'Town02':
poses_tasks = self._poses_town02()
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
elif self._city_name[:-1] == 'Town01_nemesis':
poses_tasks = [self._poses_town01_nemesis()[task_select]]
vehicles_tasks = [0, 0, 0, 0, 0, 0]
pedestrians_tasks = [0, 0, 0, 0, 0, 0]
elif self._city_name[:-1] == 'Town02_nemesis':
poses_tasks = [self._poses_town02_nemesis()[task_select]]
vehicles_tasks = [0, 0, 0, 0, 0, 0]
pedestrians_tasks = [0, 0, 0, 0, 0, 0]
experiments_vector = []
"""repeating experiment"""
num_iters = self._iters
weathers_iters = [self._weather] * num_iters
# 0 - Default
# 1 - ClearNoon
# 2 - CloudyNoon
# 3 - WetNoon
# 4 - WetCloudyNoon
# 5 - MidRainyNoon
# 6 - HardRainNoon
# 7 - SoftRainNoon
# 8 - ClearSunset
# 9 - CloudySunset
# 10 - WetSunset
# 11 - WetCloudySunset
# 12 - MidRainSunset
# 13 - HardRainSunset
# 14 - SoftRainSunset
for weather in weathers_iters:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
## add here
# random the scenario
#weather_num_random = int(random.uniform(0,14))
#vehicles_num_random = int(random.uniform(0,1000))
#pedestrain_num_random = int(random.uniform(0,1000))
#vehicles = vehicles_num_random
#pedestrains = pedestrain_num_random
#weather = weather_num_random
vehicles = 400
pedestrains = 400
#weather =
##
conditions = CarlaSettings()
conditions.set(SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1)
experiments_vector.append(experiment)
return experiments_vector
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraMiddle')
camera.set(FOV=90)
camera.set_image_size(768, 576)
camera.set_position(1.5, 0.0, 1.6)
camera.set_rotation(0, 0, 0)
if self._city_name == 'Town01':
poses_tasks = self._poses_town01()
vehicles_tasks = [0, 0, 0, 100]
pedestrians_tasks = [0, 0, 0, 300]
n_samples = [0, 0, 30 // 4, 60 // 4]
#n_samples = [3, 6, 6, 9]
else:
poses_tasks = self._poses_town02()
vehicles_tasks = [0, 0, 0, 50]
pedestrians_tasks = [0, 0, 0, 150]
n_samples = [0, 0, 15, len(poses_tasks[-1])]
#n_samples = [3, 6, 6, 9]
experiments_vector = []
random.seed(1)
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
nsample = n_samples[iteration]
if nsample == 0:
continue
poses = random.sample(poses, nsample)
conditions = CarlaSettings()
conditions.set(SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather,
QualityLevel="Low")
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1)
experiments_vector.append(experiment)
return experiments_vector
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depends on the selected Town.
"""
# We check the town, based on that we define the town related parameters
# The size of the vector is related to the number of tasks, inside each
# task there is also multiple poses ( start end, positions )
if self._city_name == 'Town01':
#poses_tasks = [[[7, 3]], [[138, 17]], [[140, 134]], [[140, 134]]]
poses_tasks = [[[138, 134]]]
vehicles_tasks = [20]
pedestrians_tasks = [10]
else:
right_curves = [[[1, 56], [65, 69], [78, 51], [44, 61], [40, 17],
[71, 16], [74, 38], [46, 12], [19, 18], [26, 74],
[37, 76], [11, 44], [20, 6], [10, 22], [28, 2],
[5, 15], [14, 33], [34, 8]]]
left_curves = [[[57, 82], [72, 43], [52, 79], [70, 66], [43, 14],
[11, 47], [79, 32], [37, 75], [75, 16], [26, 73],
[39, 5], [2, 37], [34, 13], [6, 35], [10, 19],
[23, 6], [5, 30], [16, 2]]]
special_test = [[[19, 66], [79, 14], [42, 13], [31, 71], [54, 30],
[10, 61], [66, 3], [27, 12], [2, 29], [16, 14],
[70, 73], [46, 67], [51, 81], [56, 65], [43, 54]]]
corl_task2 = [[[19, 66], [79, 14], [19, 57], [23, 1], [53, 76],
[42, 13], [31, 71], [33, 5], [54, 30], [10, 61],
[66, 3], [27, 12], [79, 19], [2, 29], [16, 14],
[5, 57], [70, 73], [46, 67], [57, 50], [61, 49],
[21, 12], [51, 81], [77, 68], [56, 65], [43, 54]]]
#poses_tasks = corl_task2
poses_tasks = [[[10, 19]]]
vehicles_tasks = [0] #*len(poses_tasks[0])
pedestrians_tasks = [0] #*len(poses_tasks[0])
# We set the camera
# This single RGB camera is used on every experiment
'''camera = Camera('CameraRGB')
camera.set(FOV=90)
camera.set_image_size(800, 600)
camera.set_position(1.44, 0.0, 1.2)
camera.set_rotation(0, 0, 0)'''
camera0 = Camera('CameraRGB0')
camera0.set(FOV=90)
camera0.set_image_size(400, 300)
camera0.set_position(1.7, 0.0, 1.3)
camera0.set_rotation(0, 0, 0)
camera1 = Camera('CameraRGB1')
camera1.set(FOV=90)
camera1.set_image_size(400, 300)
camera1.set_position(1.7, 0.0, 1.3)
camera1.set_rotation(0, -45, 0)
camera2 = Camera('CameraRGB2')
camera2.set(FOV=90)
camera2.set_image_size(400, 300)
camera2.set_position(1.7, 0.0, 1.3)
camera2.set_rotation(0, +45, 0)
# Based on the parameters, creates a vector with experiment objects.
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera0)
conditions.add_sensor(camera1)
conditions.add_sensor(camera2)
experiment = Experiment()
experiment.set(Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1)
experiments_vector.append(experiment)
'''path0=os.listdir('CameraRGB0')
path1=os.listdir('CameraRGB1')
path2=os.listdir('CameraRGB2')
os.mkdir('CameraRGB')
width=400
height=300
total_width = width*3
max_height = height
i = 0
images=[]
images.append(Image.open('CameraRGB1/'+path1[i]))
images.append(Image.open('CameraRGB0/'+path0[i]))
images.append(Image.open('CameraRGB2/'+path2[i]))
new_im = Image.new('RGB', (total_width, max_height))
x_offset = 0
for im in images:
new_im.paste(im, (x_offset,0))
x_offset += im.size[0]
new_im.save('CameraRGB/'+path0[i])
i = i+1'''
return experiments_vector
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depends on the selected Town.
"""
# We check the town, based on that we define the town related parameters
# The size of the vector is related to the number of tasks, inside each
# task there is also multiple poses ( start end, positions )
if self._city_name == 'Town01':
poses_tasks = [[[7, 3]], [[138, 17]], [[140, 134]], [[140, 134]]]
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
else:
right_curves = [[[1,56],[65,69],[78,51],[44,61],[40,17],[71,16],[74,38],[46,12],
[19,18],[26,74],[37,76],[11,44],[20,6],[10,22],[28,2],[5,15],
[14,33],[34,8]]]
left_curves = [[[57,82],[72,43],[52,79],[70,66],[43,14],[11,47],[79,32],[37,75],
[75,16],[26,73],[39,5],[2,37],[34,13],[6,35],[10,19],[23,6],
[5,30],[16,2]]]
special_test = [[[19, 66], [79, 14],[42, 13], [31, 71],
[54, 30], [10, 61], [66, 3], [27, 12],
[2, 29], [16, 14],[70, 73], [46, 67],
[51, 81], [56, 65], [43, 54]]]
corl_task2 = [[[19, 66], [79, 14], [19, 57], [23, 1],
[53, 76], [42, 13], [31, 71], [33, 5],
[54, 30], [10, 61], [66, 3], [27, 12],
[79, 19], [2, 29], [16, 14], [5, 57],
[70, 73], [46, 67], [57, 50], [61, 49], [21, 12],
[51, 81], [77, 68], [56, 65], [43, 54]]]
poses_tasks = corl_task2
vehicles_tasks = [0]*len(poses_tasks[0])
pedestrians_tasks = [0]*len(poses_tasks[0])
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=90)
camera.set_image_size(800, 600)
camera.set_position(1.44, 0.0, 1.2)
camera.set_rotation(0, 0, 0)
# Based on the parameters, creates a vector with experiment objects.
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather
)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(
Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1
)
experiments_vector.append(experiment)
return experiments_vector