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collect_data_make_collisions.py
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collect_data_make_collisions.py
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import os,sys,random,time
import carla
import numpy as np
import cv2
#settings
IM_W,IM_H = (420,280)
time_step = 1.5
image_save_path ='_data'
seq_len = 15
number_env_vehicles = 35
if not os.path.exists(os.path.join(image_save_path)):
os.makedirs(os.path.join(image_save_path))
#create main carla objects
client = carla.Client('localhost',2000)
client.set_timeout(5)
world = client.get_world()
blueprint_library = world.get_blueprint_library()
class Carla_session:
def __init__(self):
self.actors = []
self.counter = 0
self.n_seq = len(os.listdir(image_save_path))
self.collision_flag = False
self.episode_images = []
self.track_cleanup =[]
self.env_actors = []
def add_vehicles(self):
env_vehicles_bp = blueprint_library.filter('vehicle.*')
env_vehicles_bp = [x for x in env_vehicles_bp if int(x.get_attribute('number_of_wheels')) == 4]
env_vehicles_bp = [x for x in env_vehicles_bp if not x.id.endswith('isetta')]
env_vehicles_bp = [x for x in env_vehicles_bp if not x.id.endswith('carlacola')]
spawn_points = world.get_map().get_spawn_points()
SpawnActor = carla.command.SpawnActor
SetAutopilot = carla.command.SetAutopilot
FutureActor = carla.command.FutureActor
self.env_actors = []
for n, transform in enumerate(spawn_points):
if n >= number_env_vehicles:
break
env_vehicle_bp = random.choice(env_vehicles_bp)
if env_vehicle_bp.has_attribute('color'):
env_vehicle_bp.set_attribute('color', random.choice(env_vehicle_bp.get_attribute('color').recommended_values))
env_vehicle_bp.set_attribute('role_name', 'autopilot')
env_vehicle = world.spawn_actor(env_vehicle_bp,transform)
env_vehicle.set_autopilot(True)
self.env_actors.append(env_vehicle)
def add_actors(self):
start_point = random.choice(world.get_map().get_spawn_points())
#set vehicle
vehicle_bp = blueprint_library.find('vehicle.ford.mustang')
self.vehicle = world.spawn_actor(vehicle_bp,start_point)
#self.vehicle.set_autopilot(True)
#get and set sensors
collision_sensor_bp = blueprint_library.find('sensor.other.collision')
lane_invasion_sensor_bp = blueprint_library.find('sensor.other.lane_invasion')
camera_sensor_bp = blueprint_library.find('sensor.camera.rgb')
camera_sensor_bp.set_attribute('image_size_x',str(IM_W))
camera_sensor_bp.set_attribute('image_size_y',str(IM_H))
#camera_sensor_bp.set_attribute('sensor_tick',str(time_step))
camera_sensor_bp.set_attribute('fov',str(100))
sensor_location = carla.Transform(carla.Location(x=4,y=0,z=2.5))
self.camera = world.spawn_actor(camera_sensor_bp, sensor_location, attach_to = self.vehicle)
self.collision_sensor = world.spawn_actor(collision_sensor_bp, sensor_location, attach_to = self.vehicle)
#self.lane_invasion_sensor = world.spawn_actor(lane_invasion_sensor_bp, sensor_location, attach_to = self.vehicle)
self.actors.extend([self.vehicle,self.camera,self.collision_sensor])
self.camera.listen(lambda image: self.add_image(image))
self.collision_sensor.listen(lambda collision: self.end_seq(collision,'collision'))
#self.lane_invasion_sensor.listen(lambda lane_inv: self.end_seq(lane_inv,'crossed lane'))
def start_new_seq(self):
self.add_actors()
self.collision_flag = False
print('starting new seq')
self.counter = 0
self.n_seq+=1
self.track_cleanup.append(self.n_seq)
if not os.path.exists(os.path.join(image_save_path,str(self.n_seq))):
os.makedirs(os.path.join(image_save_path,str(self.n_seq)))
def add_image(self,image):
self.counter += 1
img = np.reshape(image.raw_data,(IM_H,IM_W,4))
img = img[:,:,:3][:]
#self.episode_images.append(img)
cv2.imwrite(os.path.join(image_save_path,str(self.n_seq),'{}.png'.format(self.counter)),img)
'''if self.counter%15 == 0:
self.n_seq += 1
self.counter = 0
if not os.path.exists(os.path.join(image_save_path,str(self.n_seq))):
os.makedirs(os.path.join(image_save_path,str(self.n_seq)))'''
#cv2.imshow("live",img)
#cv2.waitKey(1)
def delete_images(self):
imagestodelete = self.counter-seq_len
for i in range(imagestodelete):
os.remove(os.path.join(image_save_path,str(self.n_seq),'{}.png'.format(i+1)))
def save_images(self):
#print(os.path.join(image_save_path,str(self.n_seq),'{}.png'.format(self.counter)))
for ind,img in enumerate(self.episode_images[-seq_len:]):
cv2.imwrite(os.path.join(image_save_path,str(self.n_seq),'{}.png'.format(ind)),img)
def end_seq(self,cause_obj,cause):
self.destroy_actors()
self.collision_flag =True
print("collision happened")
self.delete_images()
def destroy_actors(self):
for actor in self.actors:
print(actor)
actor.destroy()
#self.save_images()
self.actors = []
#self.episode_images =[]
def get_directions(self):
thr = random.choice([0.8,0.7,0.6])
steer = random.choice([-0.3,0.0,0.0,0.0,0.3,0.1,-0.1])
return carla.VehicleControl(thr,steer)
def drive_around(self,episodes):
self.add_vehicles()
for i in range(episodes):
try:
self.start_new_seq()
for j in range(200):
self.vehicle.apply_control(self.get_directions())
time.sleep(1)
if self.collision_flag == True:
break
except Exception as e:
print(e)
continue
'''for i in self.env_actors:
i.destory()
self.env_actors =[]'''
c = Carla_session()
c.drive_around(10)