diff --git a/Deprecated/PythonClient/.pylintrc b/Deprecated/PythonClient/.pylintrc deleted file mode 100644 index a8085ad7b..000000000 --- a/Deprecated/PythonClient/.pylintrc +++ /dev/null @@ -1,4 +0,0 @@ -[TYPECHECK] -ignore=carla_server_pb2.py -ignored-modules=ConfigParser,numpy,numpy.random,pygame,shutil -ignored-classes=_socketobject,EpisodeReady,SceneDescription,Sensor diff --git a/Deprecated/PythonClient/MANIFEST.in b/Deprecated/PythonClient/MANIFEST.in deleted file mode 100644 index 824b0ad1d..000000000 --- a/Deprecated/PythonClient/MANIFEST.in +++ /dev/null @@ -1,2 +0,0 @@ -include carla/planner/*.txt -include carla/planner/*.png diff --git a/Deprecated/PythonClient/carla/__init__.py b/Deprecated/PythonClient/carla/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/Deprecated/PythonClient/carla/agent/__init__.py b/Deprecated/PythonClient/carla/agent/__init__.py deleted file mode 100644 index 102f0155a..000000000 --- a/Deprecated/PythonClient/carla/agent/__init__.py +++ /dev/null @@ -1,2 +0,0 @@ -from .forward_agent import ForwardAgent -from .agent import Agent diff --git a/Deprecated/PythonClient/carla/agent/agent.py b/Deprecated/PythonClient/carla/agent/agent.py deleted file mode 100644 index c6a5d8a71..000000000 --- a/Deprecated/PythonClient/carla/agent/agent.py +++ /dev/null @@ -1,24 +0,0 @@ -# -*- coding: utf-8 -*- -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . -# @author: german,felipecode - - -from __future__ import print_function -import abc - - -class Agent(object): - def __init__(self): - self.__metaclass__ = abc.ABCMeta - - @abc.abstractmethod - def run_step(self, measurements, sensor_data, directions, target): - """ - Function to be redefined by an agent. - :param The measurements like speed, the image data and a target - :returns A carla Control object, with the steering/gas/brake for the agent - """ diff --git a/Deprecated/PythonClient/carla/agent/forward_agent.py b/Deprecated/PythonClient/carla/agent/forward_agent.py deleted file mode 100644 index 9836b19ed..000000000 --- a/Deprecated/PythonClient/carla/agent/forward_agent.py +++ /dev/null @@ -1,15 +0,0 @@ - -from carla.agent.agent import Agent -from carla.client import VehicleControl - - -class ForwardAgent(Agent): - """ - Simple derivation of Agent Class, - A trivial agent agent that goes straight - """ - def run_step(self, measurements, sensor_data, directions, target): - control = VehicleControl() - control.throttle = 0.9 - - return control diff --git a/Deprecated/PythonClient/carla/carla_server_pb2.py b/Deprecated/PythonClient/carla/carla_server_pb2.py deleted file mode 100644 index 1e9c0231f..000000000 --- a/Deprecated/PythonClient/carla/carla_server_pb2.py +++ /dev/null @@ -1,1059 +0,0 @@ -# Generated by the protocol buffer compiler. DO NOT EDIT! -# source: carla_server.proto - -import sys -_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) -from google.protobuf import descriptor as _descriptor -from google.protobuf import message as _message -from google.protobuf import reflection as _reflection -from google.protobuf import symbol_database as _symbol_database -from google.protobuf import descriptor_pb2 -# @@protoc_insertion_point(imports) - -_sym_db = _symbol_database.Default() - - - - -DESCRIPTOR = _descriptor.FileDescriptor( - name='carla_server.proto', - package='carla_server', - syntax='proto3', - serialized_pb=_b('\n\x12\x63\x61rla_server.proto\x12\x0c\x63\x61rla_server\"+\n\x08Vector3D\x12\t\n\x01x\x18\x01 \x01(\x02\x12\t\n\x01y\x18\x02 \x01(\x02\x12\t\n\x01z\x18\x03 \x01(\x02\"6\n\nRotation3D\x12\r\n\x05pitch\x18\x01 \x01(\x02\x12\x0b\n\x03yaw\x18\x02 \x01(\x02\x12\x0c\n\x04roll\x18\x03 \x01(\x02\"\x92\x01\n\tTransform\x12(\n\x08location\x18\x01 \x01(\x0b\x32\x16.carla_server.Vector3D\x12/\n\x0borientation\x18\x02 \x01(\x0b\x32\x16.carla_server.Vector3DB\x02\x18\x01\x12*\n\x08rotation\x18\x03 \x01(\x0b\x32\x18.carla_server.Rotation3D\"a\n\x0b\x42oundingBox\x12*\n\ttransform\x18\x01 \x01(\x0b\x32\x17.carla_server.Transform\x12&\n\x06\x65xtent\x18\x02 \x01(\x0b\x32\x16.carla_server.Vector3D\"\x80\x01\n\x06Sensor\x12\n\n\x02id\x18\x01 \x01(\x07\x12\'\n\x04type\x18\x02 \x01(\x0e\x32\x19.carla_server.Sensor.Type\x12\x0c\n\x04name\x18\x03 \x01(\t\"3\n\x04Type\x12\x0b\n\x07UNKNOWN\x10\x00\x12\n\n\x06\x43\x41MERA\x10\x01\x12\x12\n\x0eLIDAR_RAY_CAST\x10\x02\"}\n\x07Vehicle\x12*\n\ttransform\x18\x01 \x01(\x0b\x32\x17.carla_server.Transform\x12/\n\x0c\x62ounding_box\x18\x04 \x01(\x0b\x32\x19.carla_server.BoundingBox\x12\x15\n\rforward_speed\x18\x03 \x01(\x02\"\x80\x01\n\nPedestrian\x12*\n\ttransform\x18\x01 \x01(\x0b\x32\x17.carla_server.Transform\x12/\n\x0c\x62ounding_box\x18\x04 \x01(\x0b\x32\x19.carla_server.BoundingBox\x12\x15\n\rforward_speed\x18\x03 \x01(\x02\"\x94\x01\n\x0cTrafficLight\x12*\n\ttransform\x18\x01 \x01(\x0b\x32\x17.carla_server.Transform\x12/\n\x05state\x18\x02 \x01(\x0e\x32 .carla_server.TrafficLight.State\"\'\n\x05State\x12\t\n\x05GREEN\x10\x00\x12\n\n\x06YELLOW\x10\x01\x12\x07\n\x03RED\x10\x02\"Q\n\x0eSpeedLimitSign\x12*\n\ttransform\x18\x01 \x01(\x0b\x32\x17.carla_server.Transform\x12\x13\n\x0bspeed_limit\x18\x02 \x01(\x02\"\xe5\x01\n\x05\x41gent\x12\n\n\x02id\x18\x01 \x01(\x07\x12(\n\x07vehicle\x18\x02 \x01(\x0b\x32\x15.carla_server.VehicleH\x00\x12.\n\npedestrian\x18\x03 \x01(\x0b\x32\x18.carla_server.PedestrianH\x00\x12\x33\n\rtraffic_light\x18\x04 \x01(\x0b\x32\x1a.carla_server.TrafficLightH\x00\x12\x38\n\x10speed_limit_sign\x18\x05 \x01(\x0b\x32\x1c.carla_server.SpeedLimitSignH\x00\x42\x07\n\x05\x61gent\"%\n\x11RequestNewEpisode\x12\x10\n\x08ini_file\x18\x01 \x01(\t\"\x80\x01\n\x10SceneDescription\x12\x10\n\x08map_name\x18\x03 \x01(\t\x12\x33\n\x12player_start_spots\x18\x01 \x03(\x0b\x32\x17.carla_server.Transform\x12%\n\x07sensors\x18\x02 \x03(\x0b\x32\x14.carla_server.Sensor\"/\n\x0c\x45pisodeStart\x12\x1f\n\x17player_start_spot_index\x18\x01 \x01(\r\"\x1d\n\x0c\x45pisodeReady\x12\r\n\x05ready\x18\x01 \x01(\x08\"^\n\x07\x43ontrol\x12\r\n\x05steer\x18\x01 \x01(\x02\x12\x10\n\x08throttle\x18\x02 \x01(\x02\x12\r\n\x05\x62rake\x18\x03 \x01(\x02\x12\x12\n\nhand_brake\x18\x04 \x01(\x08\x12\x0f\n\x07reverse\x18\x05 \x01(\x08\"\xd1\x04\n\x0cMeasurements\x12\x14\n\x0c\x66rame_number\x18\x05 \x01(\x04\x12\x1a\n\x12platform_timestamp\x18\x01 \x01(\r\x12\x16\n\x0egame_timestamp\x18\x02 \x01(\r\x12J\n\x13player_measurements\x18\x03 \x01(\x0b\x32-.carla_server.Measurements.PlayerMeasurements\x12.\n\x11non_player_agents\x18\x04 \x03(\x0b\x32\x13.carla_server.Agent\x1a\xfa\x02\n\x12PlayerMeasurements\x12*\n\ttransform\x18\x01 \x01(\x0b\x32\x17.carla_server.Transform\x12/\n\x0c\x62ounding_box\x18\x0c \x01(\x0b\x32\x19.carla_server.BoundingBox\x12,\n\x0c\x61\x63\x63\x65leration\x18\x03 \x01(\x0b\x32\x16.carla_server.Vector3D\x12\x15\n\rforward_speed\x18\x04 \x01(\x02\x12\x1a\n\x12\x63ollision_vehicles\x18\x05 \x01(\x02\x12\x1d\n\x15\x63ollision_pedestrians\x18\x06 \x01(\x02\x12\x17\n\x0f\x63ollision_other\x18\x07 \x01(\x02\x12\x1e\n\x16intersection_otherlane\x18\x08 \x01(\x02\x12\x1c\n\x14intersection_offroad\x18\t \x01(\x02\x12\x30\n\x11\x61utopilot_control\x18\n \x01(\x0b\x32\x15.carla_server.ControlB\x03\xf8\x01\x01\x62\x06proto3') -) - - - -_SENSOR_TYPE = _descriptor.EnumDescriptor( - name='Type', - full_name='carla_server.Sensor.Type', - filename=None, - file=DESCRIPTOR, - values=[ - _descriptor.EnumValueDescriptor( - name='UNKNOWN', index=0, number=0, - options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='CAMERA', index=1, number=1, - options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='LIDAR_RAY_CAST', index=2, number=2, - options=None, - type=None), - ], - containing_type=None, - options=None, - serialized_start=463, - serialized_end=514, -) -_sym_db.RegisterEnumDescriptor(_SENSOR_TYPE) - -_TRAFFICLIGHT_STATE = _descriptor.EnumDescriptor( - name='State', - full_name='carla_server.TrafficLight.State', - filename=None, - file=DESCRIPTOR, - values=[ - _descriptor.EnumValueDescriptor( - name='GREEN', index=0, number=0, - options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='YELLOW', index=1, number=1, - options=None, - type=None), - _descriptor.EnumValueDescriptor( - name='RED', index=2, number=2, - options=None, - type=None), - ], - containing_type=None, - options=None, - serialized_start=884, - serialized_end=923, -) -_sym_db.RegisterEnumDescriptor(_TRAFFICLIGHT_STATE) - - -_VECTOR3D = _descriptor.Descriptor( - name='Vector3D', - full_name='carla_server.Vector3D', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='x', full_name='carla_server.Vector3D.x', index=0, - number=1, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='y', full_name='carla_server.Vector3D.y', index=1, - number=2, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='z', full_name='carla_server.Vector3D.z', index=2, - number=3, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=36, - serialized_end=79, -) - - -_ROTATION3D = _descriptor.Descriptor( - name='Rotation3D', - full_name='carla_server.Rotation3D', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='pitch', full_name='carla_server.Rotation3D.pitch', index=0, - number=1, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='yaw', full_name='carla_server.Rotation3D.yaw', index=1, - number=2, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='roll', full_name='carla_server.Rotation3D.roll', index=2, - number=3, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=81, - serialized_end=135, -) - - -_TRANSFORM = _descriptor.Descriptor( - name='Transform', - full_name='carla_server.Transform', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='location', full_name='carla_server.Transform.location', index=0, - number=1, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='orientation', full_name='carla_server.Transform.orientation', index=1, - number=2, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\030\001'))), - _descriptor.FieldDescriptor( - name='rotation', full_name='carla_server.Transform.rotation', index=2, - number=3, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=138, - serialized_end=284, -) - - -_BOUNDINGBOX = _descriptor.Descriptor( - name='BoundingBox', - full_name='carla_server.BoundingBox', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='transform', full_name='carla_server.BoundingBox.transform', index=0, - number=1, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='extent', full_name='carla_server.BoundingBox.extent', index=1, - number=2, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=286, - serialized_end=383, -) - - -_SENSOR = _descriptor.Descriptor( - name='Sensor', - full_name='carla_server.Sensor', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='id', full_name='carla_server.Sensor.id', index=0, - number=1, type=7, cpp_type=3, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='type', full_name='carla_server.Sensor.type', index=1, - number=2, type=14, cpp_type=8, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='name', full_name='carla_server.Sensor.name', index=2, - number=3, type=9, cpp_type=9, label=1, - has_default_value=False, default_value=_b("").decode('utf-8'), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - _SENSOR_TYPE, - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=386, - serialized_end=514, -) - - -_VEHICLE = _descriptor.Descriptor( - name='Vehicle', - full_name='carla_server.Vehicle', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='transform', full_name='carla_server.Vehicle.transform', index=0, - number=1, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='bounding_box', full_name='carla_server.Vehicle.bounding_box', index=1, - number=4, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='forward_speed', full_name='carla_server.Vehicle.forward_speed', index=2, - number=3, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=516, - serialized_end=641, -) - - -_PEDESTRIAN = _descriptor.Descriptor( - name='Pedestrian', - full_name='carla_server.Pedestrian', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='transform', full_name='carla_server.Pedestrian.transform', index=0, - number=1, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='bounding_box', full_name='carla_server.Pedestrian.bounding_box', index=1, - number=4, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='forward_speed', full_name='carla_server.Pedestrian.forward_speed', index=2, - number=3, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=644, - serialized_end=772, -) - - -_TRAFFICLIGHT = _descriptor.Descriptor( - name='TrafficLight', - full_name='carla_server.TrafficLight', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='transform', full_name='carla_server.TrafficLight.transform', index=0, - number=1, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='state', full_name='carla_server.TrafficLight.state', index=1, - number=2, type=14, cpp_type=8, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - _TRAFFICLIGHT_STATE, - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=775, - serialized_end=923, -) - - -_SPEEDLIMITSIGN = _descriptor.Descriptor( - name='SpeedLimitSign', - full_name='carla_server.SpeedLimitSign', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='transform', full_name='carla_server.SpeedLimitSign.transform', index=0, - number=1, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='speed_limit', full_name='carla_server.SpeedLimitSign.speed_limit', index=1, - number=2, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=925, - serialized_end=1006, -) - - -_AGENT = _descriptor.Descriptor( - name='Agent', - full_name='carla_server.Agent', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='id', full_name='carla_server.Agent.id', index=0, - number=1, type=7, cpp_type=3, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='vehicle', full_name='carla_server.Agent.vehicle', index=1, - number=2, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='pedestrian', full_name='carla_server.Agent.pedestrian', index=2, - number=3, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='traffic_light', full_name='carla_server.Agent.traffic_light', index=3, - number=4, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='speed_limit_sign', full_name='carla_server.Agent.speed_limit_sign', index=4, - number=5, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - _descriptor.OneofDescriptor( - name='agent', full_name='carla_server.Agent.agent', - index=0, containing_type=None, fields=[]), - ], - serialized_start=1009, - serialized_end=1238, -) - - -_REQUESTNEWEPISODE = _descriptor.Descriptor( - name='RequestNewEpisode', - full_name='carla_server.RequestNewEpisode', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='ini_file', full_name='carla_server.RequestNewEpisode.ini_file', index=0, - number=1, type=9, cpp_type=9, label=1, - has_default_value=False, default_value=_b("").decode('utf-8'), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=1240, - serialized_end=1277, -) - - -_SCENEDESCRIPTION = _descriptor.Descriptor( - name='SceneDescription', - full_name='carla_server.SceneDescription', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='map_name', full_name='carla_server.SceneDescription.map_name', index=0, - number=3, type=9, cpp_type=9, label=1, - has_default_value=False, default_value=_b("").decode('utf-8'), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='player_start_spots', full_name='carla_server.SceneDescription.player_start_spots', index=1, - number=1, type=11, cpp_type=10, label=3, - has_default_value=False, default_value=[], - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='sensors', full_name='carla_server.SceneDescription.sensors', index=2, - number=2, type=11, cpp_type=10, label=3, - has_default_value=False, default_value=[], - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=1280, - serialized_end=1408, -) - - -_EPISODESTART = _descriptor.Descriptor( - name='EpisodeStart', - full_name='carla_server.EpisodeStart', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='player_start_spot_index', full_name='carla_server.EpisodeStart.player_start_spot_index', index=0, - number=1, type=13, cpp_type=3, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=1410, - serialized_end=1457, -) - - -_EPISODEREADY = _descriptor.Descriptor( - name='EpisodeReady', - full_name='carla_server.EpisodeReady', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='ready', full_name='carla_server.EpisodeReady.ready', index=0, - number=1, type=8, cpp_type=7, label=1, - has_default_value=False, default_value=False, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=1459, - serialized_end=1488, -) - - -_CONTROL = _descriptor.Descriptor( - name='Control', - full_name='carla_server.Control', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='steer', full_name='carla_server.Control.steer', index=0, - number=1, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='throttle', full_name='carla_server.Control.throttle', index=1, - number=2, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='brake', full_name='carla_server.Control.brake', index=2, - number=3, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='hand_brake', full_name='carla_server.Control.hand_brake', index=3, - number=4, type=8, cpp_type=7, label=1, - has_default_value=False, default_value=False, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='reverse', full_name='carla_server.Control.reverse', index=4, - number=5, type=8, cpp_type=7, label=1, - has_default_value=False, default_value=False, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=1490, - serialized_end=1584, -) - - -_MEASUREMENTS_PLAYERMEASUREMENTS = _descriptor.Descriptor( - name='PlayerMeasurements', - full_name='carla_server.Measurements.PlayerMeasurements', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='transform', full_name='carla_server.Measurements.PlayerMeasurements.transform', index=0, - number=1, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='bounding_box', full_name='carla_server.Measurements.PlayerMeasurements.bounding_box', index=1, - number=12, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='acceleration', full_name='carla_server.Measurements.PlayerMeasurements.acceleration', index=2, - number=3, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='forward_speed', full_name='carla_server.Measurements.PlayerMeasurements.forward_speed', index=3, - number=4, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='collision_vehicles', full_name='carla_server.Measurements.PlayerMeasurements.collision_vehicles', index=4, - number=5, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='collision_pedestrians', full_name='carla_server.Measurements.PlayerMeasurements.collision_pedestrians', index=5, - number=6, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='collision_other', full_name='carla_server.Measurements.PlayerMeasurements.collision_other', index=6, - number=7, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='intersection_otherlane', full_name='carla_server.Measurements.PlayerMeasurements.intersection_otherlane', index=7, - number=8, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='intersection_offroad', full_name='carla_server.Measurements.PlayerMeasurements.intersection_offroad', index=8, - number=9, type=2, cpp_type=6, label=1, - has_default_value=False, default_value=float(0), - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='autopilot_control', full_name='carla_server.Measurements.PlayerMeasurements.autopilot_control', index=9, - number=10, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=1802, - serialized_end=2180, -) - -_MEASUREMENTS = _descriptor.Descriptor( - name='Measurements', - full_name='carla_server.Measurements', - filename=None, - file=DESCRIPTOR, - containing_type=None, - fields=[ - _descriptor.FieldDescriptor( - name='frame_number', full_name='carla_server.Measurements.frame_number', index=0, - number=5, type=4, cpp_type=4, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='platform_timestamp', full_name='carla_server.Measurements.platform_timestamp', index=1, - number=1, type=13, cpp_type=3, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='game_timestamp', full_name='carla_server.Measurements.game_timestamp', index=2, - number=2, type=13, cpp_type=3, label=1, - has_default_value=False, default_value=0, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='player_measurements', full_name='carla_server.Measurements.player_measurements', index=3, - number=3, type=11, cpp_type=10, label=1, - has_default_value=False, default_value=None, - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - _descriptor.FieldDescriptor( - name='non_player_agents', full_name='carla_server.Measurements.non_player_agents', index=4, - number=4, type=11, cpp_type=10, label=3, - has_default_value=False, default_value=[], - message_type=None, enum_type=None, containing_type=None, - is_extension=False, extension_scope=None, - options=None), - ], - extensions=[ - ], - nested_types=[_MEASUREMENTS_PLAYERMEASUREMENTS, ], - enum_types=[ - ], - options=None, - is_extendable=False, - syntax='proto3', - extension_ranges=[], - oneofs=[ - ], - serialized_start=1587, - serialized_end=2180, -) - -_TRANSFORM.fields_by_name['location'].message_type = _VECTOR3D -_TRANSFORM.fields_by_name['orientation'].message_type = _VECTOR3D -_TRANSFORM.fields_by_name['rotation'].message_type = _ROTATION3D -_BOUNDINGBOX.fields_by_name['transform'].message_type = _TRANSFORM -_BOUNDINGBOX.fields_by_name['extent'].message_type = _VECTOR3D -_SENSOR.fields_by_name['type'].enum_type = _SENSOR_TYPE -_SENSOR_TYPE.containing_type = _SENSOR -_VEHICLE.fields_by_name['transform'].message_type = _TRANSFORM -_VEHICLE.fields_by_name['bounding_box'].message_type = _BOUNDINGBOX -_PEDESTRIAN.fields_by_name['transform'].message_type = _TRANSFORM -_PEDESTRIAN.fields_by_name['bounding_box'].message_type = _BOUNDINGBOX -_TRAFFICLIGHT.fields_by_name['transform'].message_type = _TRANSFORM -_TRAFFICLIGHT.fields_by_name['state'].enum_type = _TRAFFICLIGHT_STATE -_TRAFFICLIGHT_STATE.containing_type = _TRAFFICLIGHT -_SPEEDLIMITSIGN.fields_by_name['transform'].message_type = _TRANSFORM -_AGENT.fields_by_name['vehicle'].message_type = _VEHICLE -_AGENT.fields_by_name['pedestrian'].message_type = _PEDESTRIAN -_AGENT.fields_by_name['traffic_light'].message_type = _TRAFFICLIGHT -_AGENT.fields_by_name['speed_limit_sign'].message_type = _SPEEDLIMITSIGN -_AGENT.oneofs_by_name['agent'].fields.append( - _AGENT.fields_by_name['vehicle']) -_AGENT.fields_by_name['vehicle'].containing_oneof = _AGENT.oneofs_by_name['agent'] -_AGENT.oneofs_by_name['agent'].fields.append( - _AGENT.fields_by_name['pedestrian']) -_AGENT.fields_by_name['pedestrian'].containing_oneof = _AGENT.oneofs_by_name['agent'] -_AGENT.oneofs_by_name['agent'].fields.append( - _AGENT.fields_by_name['traffic_light']) -_AGENT.fields_by_name['traffic_light'].containing_oneof = _AGENT.oneofs_by_name['agent'] -_AGENT.oneofs_by_name['agent'].fields.append( - _AGENT.fields_by_name['speed_limit_sign']) -_AGENT.fields_by_name['speed_limit_sign'].containing_oneof = _AGENT.oneofs_by_name['agent'] -_SCENEDESCRIPTION.fields_by_name['player_start_spots'].message_type = _TRANSFORM -_SCENEDESCRIPTION.fields_by_name['sensors'].message_type = _SENSOR -_MEASUREMENTS_PLAYERMEASUREMENTS.fields_by_name['transform'].message_type = _TRANSFORM -_MEASUREMENTS_PLAYERMEASUREMENTS.fields_by_name['bounding_box'].message_type = _BOUNDINGBOX -_MEASUREMENTS_PLAYERMEASUREMENTS.fields_by_name['acceleration'].message_type = _VECTOR3D -_MEASUREMENTS_PLAYERMEASUREMENTS.fields_by_name['autopilot_control'].message_type = _CONTROL -_MEASUREMENTS_PLAYERMEASUREMENTS.containing_type = _MEASUREMENTS -_MEASUREMENTS.fields_by_name['player_measurements'].message_type = _MEASUREMENTS_PLAYERMEASUREMENTS -_MEASUREMENTS.fields_by_name['non_player_agents'].message_type = _AGENT -DESCRIPTOR.message_types_by_name['Vector3D'] = _VECTOR3D -DESCRIPTOR.message_types_by_name['Rotation3D'] = _ROTATION3D -DESCRIPTOR.message_types_by_name['Transform'] = _TRANSFORM -DESCRIPTOR.message_types_by_name['BoundingBox'] = _BOUNDINGBOX -DESCRIPTOR.message_types_by_name['Sensor'] = _SENSOR -DESCRIPTOR.message_types_by_name['Vehicle'] = _VEHICLE -DESCRIPTOR.message_types_by_name['Pedestrian'] = _PEDESTRIAN -DESCRIPTOR.message_types_by_name['TrafficLight'] = _TRAFFICLIGHT -DESCRIPTOR.message_types_by_name['SpeedLimitSign'] = _SPEEDLIMITSIGN -DESCRIPTOR.message_types_by_name['Agent'] = _AGENT -DESCRIPTOR.message_types_by_name['RequestNewEpisode'] = _REQUESTNEWEPISODE -DESCRIPTOR.message_types_by_name['SceneDescription'] = _SCENEDESCRIPTION -DESCRIPTOR.message_types_by_name['EpisodeStart'] = _EPISODESTART -DESCRIPTOR.message_types_by_name['EpisodeReady'] = _EPISODEREADY -DESCRIPTOR.message_types_by_name['Control'] = _CONTROL -DESCRIPTOR.message_types_by_name['Measurements'] = _MEASUREMENTS -_sym_db.RegisterFileDescriptor(DESCRIPTOR) - -Vector3D = _reflection.GeneratedProtocolMessageType('Vector3D', (_message.Message,), dict( - DESCRIPTOR = _VECTOR3D, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.Vector3D) - )) -_sym_db.RegisterMessage(Vector3D) - -Rotation3D = _reflection.GeneratedProtocolMessageType('Rotation3D', (_message.Message,), dict( - DESCRIPTOR = _ROTATION3D, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.Rotation3D) - )) -_sym_db.RegisterMessage(Rotation3D) - -Transform = _reflection.GeneratedProtocolMessageType('Transform', (_message.Message,), dict( - DESCRIPTOR = _TRANSFORM, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.Transform) - )) -_sym_db.RegisterMessage(Transform) - -BoundingBox = _reflection.GeneratedProtocolMessageType('BoundingBox', (_message.Message,), dict( - DESCRIPTOR = _BOUNDINGBOX, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.BoundingBox) - )) -_sym_db.RegisterMessage(BoundingBox) - -Sensor = _reflection.GeneratedProtocolMessageType('Sensor', (_message.Message,), dict( - DESCRIPTOR = _SENSOR, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.Sensor) - )) -_sym_db.RegisterMessage(Sensor) - -Vehicle = _reflection.GeneratedProtocolMessageType('Vehicle', (_message.Message,), dict( - DESCRIPTOR = _VEHICLE, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.Vehicle) - )) -_sym_db.RegisterMessage(Vehicle) - -Pedestrian = _reflection.GeneratedProtocolMessageType('Pedestrian', (_message.Message,), dict( - DESCRIPTOR = _PEDESTRIAN, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.Pedestrian) - )) -_sym_db.RegisterMessage(Pedestrian) - -TrafficLight = _reflection.GeneratedProtocolMessageType('TrafficLight', (_message.Message,), dict( - DESCRIPTOR = _TRAFFICLIGHT, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.TrafficLight) - )) -_sym_db.RegisterMessage(TrafficLight) - -SpeedLimitSign = _reflection.GeneratedProtocolMessageType('SpeedLimitSign', (_message.Message,), dict( - DESCRIPTOR = _SPEEDLIMITSIGN, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.SpeedLimitSign) - )) -_sym_db.RegisterMessage(SpeedLimitSign) - -Agent = _reflection.GeneratedProtocolMessageType('Agent', (_message.Message,), dict( - DESCRIPTOR = _AGENT, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.Agent) - )) -_sym_db.RegisterMessage(Agent) - -RequestNewEpisode = _reflection.GeneratedProtocolMessageType('RequestNewEpisode', (_message.Message,), dict( - DESCRIPTOR = _REQUESTNEWEPISODE, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.RequestNewEpisode) - )) -_sym_db.RegisterMessage(RequestNewEpisode) - -SceneDescription = _reflection.GeneratedProtocolMessageType('SceneDescription', (_message.Message,), dict( - DESCRIPTOR = _SCENEDESCRIPTION, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.SceneDescription) - )) -_sym_db.RegisterMessage(SceneDescription) - -EpisodeStart = _reflection.GeneratedProtocolMessageType('EpisodeStart', (_message.Message,), dict( - DESCRIPTOR = _EPISODESTART, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.EpisodeStart) - )) -_sym_db.RegisterMessage(EpisodeStart) - -EpisodeReady = _reflection.GeneratedProtocolMessageType('EpisodeReady', (_message.Message,), dict( - DESCRIPTOR = _EPISODEREADY, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.EpisodeReady) - )) -_sym_db.RegisterMessage(EpisodeReady) - -Control = _reflection.GeneratedProtocolMessageType('Control', (_message.Message,), dict( - DESCRIPTOR = _CONTROL, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.Control) - )) -_sym_db.RegisterMessage(Control) - -Measurements = _reflection.GeneratedProtocolMessageType('Measurements', (_message.Message,), dict( - - PlayerMeasurements = _reflection.GeneratedProtocolMessageType('PlayerMeasurements', (_message.Message,), dict( - DESCRIPTOR = _MEASUREMENTS_PLAYERMEASUREMENTS, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.Measurements.PlayerMeasurements) - )) - , - DESCRIPTOR = _MEASUREMENTS, - __module__ = 'carla_server_pb2' - # @@protoc_insertion_point(class_scope:carla_server.Measurements) - )) -_sym_db.RegisterMessage(Measurements) -_sym_db.RegisterMessage(Measurements.PlayerMeasurements) - - -DESCRIPTOR.has_options = True -DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), _b('\370\001\001')) -_TRANSFORM.fields_by_name['orientation'].has_options = True -_TRANSFORM.fields_by_name['orientation']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\030\001')) -# @@protoc_insertion_point(module_scope) diff --git a/Deprecated/PythonClient/carla/client.py b/Deprecated/PythonClient/carla/client.py deleted file mode 100644 index d2700924e..000000000 --- a/Deprecated/PythonClient/carla/client.py +++ /dev/null @@ -1,232 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""CARLA Client.""" - -import logging -import struct - -from contextlib import contextmanager - -from . import sensor -from . import tcp -from . import util - -try: - from . import carla_server_pb2 as carla_protocol -except ImportError: - raise RuntimeError('cannot import "carla_server_pb2.py", run the protobuf compiler to generate this file') - -try: - import numpy -except ImportError: - raise RuntimeError('cannot import numpy, make sure numpy package is installed.') - - -VehicleControl = carla_protocol.Control - - -@contextmanager -def make_carla_client(host, world_port, timeout=15): - """Context manager for creating and connecting a CarlaClient.""" - with util.make_connection(CarlaClient, host, world_port, timeout) as client: - yield client - - -class CarlaClient(object): - """The CARLA client. Manages communications with the CARLA server.""" - - def __init__(self, host, world_port, timeout=15): - self._world_client = tcp.TCPClient(host, world_port, timeout) - self._stream_client = tcp.TCPClient(host, world_port + 1, timeout) - self._control_client = tcp.TCPClient(host, world_port + 2, timeout) - self._current_settings = None - self._is_episode_requested = False - self._sensors = {} - - def connect(self, connection_attempts=10): - """ - Try to establish a connection to a CARLA server at the given host:port. - """ - self._world_client.connect(connection_attempts) - - def disconnect(self): - """Disconnect from server.""" - self._control_client.disconnect() - self._stream_client.disconnect() - self._world_client.disconnect() - - def connected(self): - """Return whether there is an active connection.""" - return self._world_client.connected() - - def load_settings(self, carla_settings): - """ - Load new settings and request a new episode based on these settings. - carla_settings object must be convertible to a str holding the contents - of a CarlaSettings.ini file. - - Return a protobuf object holding the scene description. - """ - self._current_settings = carla_settings - return self._request_new_episode(carla_settings) - - def start_episode(self, player_start_index): - """ - Start the new episode at the player start given by the - player_start_index. The list of player starts is retrieved by - "load_settings". - - The new episode is started based on the last settings loaded by - "load_settings". - - This function waits until the server answers with an EpisodeReady. - """ - if self._current_settings is None: - raise RuntimeError('no settings loaded, cannot start episode') - - # if no new settings are loaded, request new episode with previous - if not self._is_episode_requested: - self._request_new_episode(self._current_settings) - - try: - pb_message = carla_protocol.EpisodeStart() - pb_message.player_start_spot_index = player_start_index - self._world_client.write(pb_message.SerializeToString()) - # Wait for EpisodeReady. - data = self._world_client.read() - if not data: - raise RuntimeError('failed to read data from server') - pb_message = carla_protocol.EpisodeReady() - pb_message.ParseFromString(data) - if not pb_message.ready: - raise RuntimeError('cannot start episode: server failed to start episode') - # We can start the agent clients now. - self._stream_client.connect() - self._control_client.connect() - # Set again the status for no episode requested - finally: - self._is_episode_requested = False - - def read_data(self): - """ - Read the data sent from the server this frame. The episode must be - started. Return a pair containing the protobuf object containing the - measurements followed by the raw data of the sensors. - """ - # Read measurements. - data = self._stream_client.read() - if not data: - raise RuntimeError('failed to read data from server') - pb_message = carla_protocol.Measurements() - pb_message.ParseFromString(data) - # Read sensor data. - return pb_message, dict(x for x in self._read_sensor_data()) - - def send_control(self, *args, **kwargs): - """ - Send the VehicleControl to be applied this frame. - - If synchronous mode was requested, the server will pause the simulation - until this message is received. - """ - if isinstance(args[0] if args else None, carla_protocol.Control): - pb_message = args[0] - else: - pb_message = carla_protocol.Control() - pb_message.steer = kwargs.get('steer', 0.0) - pb_message.throttle = kwargs.get('throttle', 0.0) - pb_message.brake = kwargs.get('brake', 0.0) - pb_message.hand_brake = kwargs.get('hand_brake', False) - pb_message.reverse = kwargs.get('reverse', False) - self._control_client.write(pb_message.SerializeToString()) - - def _request_new_episode(self, carla_settings): - """ - Internal function to request a new episode. Prepare the client for a new - episode by disconnecting agent clients. - """ - # Disconnect agent clients. - self._stream_client.disconnect() - self._control_client.disconnect() - # Send new episode request. - pb_message = carla_protocol.RequestNewEpisode() - pb_message.ini_file = str(carla_settings) - self._world_client.write(pb_message.SerializeToString()) - # Read scene description. - data = self._world_client.read() - if not data: - raise RuntimeError('failed to read data from server') - pb_message = carla_protocol.SceneDescription() - pb_message.ParseFromString(data) - self._sensors = dict((sensor.id, sensor) \ - for sensor in _make_sensor_parsers(pb_message.sensors)) - self._is_episode_requested = True - return pb_message - - def _read_sensor_data(self): - while True: - data = self._stream_client.read() - if not data: - raise StopIteration - yield self._parse_sensor_data(data) - - def _parse_sensor_data(self, data): - sensor_id = struct.unpack(' id else 'Unknown' - getint32 = lambda data, index: struct.unpack('. - - -import abc -import logging -import math -import time - -from carla.client import VehicleControl -from carla.client import make_carla_client -from carla.driving_benchmark.metrics import Metrics -from carla.planner.planner import Planner -from carla.settings import CarlaSettings -from carla.tcp import TCPConnectionError - -from . import results_printer -from .recording import Recording - - -def sldist(c1, c2): - return math.sqrt((c2[0] - c1[0]) ** 2 + (c2[1] - c1[1]) ** 2) - - -class DrivingBenchmark(object): - """ - The Benchmark class, controls the execution of the benchmark interfacing - an Agent class with a set Suite. - - - The benchmark class must be inherited by a class that defines the - all the experiments to be run by the agent - """ - - def __init__( - self, - city_name='Town01', - name_to_save='Test', - continue_experiment=False, - save_images=False, - distance_for_success=2.0 - ): - - self.__metaclass__ = abc.ABCMeta - - self._city_name = city_name - self._base_name = name_to_save - # The minimum distance for arriving into the goal point in - # order to consider ir a success - self._distance_for_success = distance_for_success - # The object used to record the benchmark and to able to continue after - self._recording = Recording(name_to_save=name_to_save, - continue_experiment=continue_experiment, - save_images=save_images - ) - - # We have a default planner instantiated that produces high level commands - self._planner = Planner(city_name) - - def benchmark_agent(self, experiment_suite, agent, client): - """ - Function to benchmark the agent. - It first checks the log file of this benchmark. - if it exists, it continues from the experiment where it stopped. - - - Args: - experiment_suite - agent: an agent object with the run step class implemented. - client: - - - Return: - A dictionary with all the metrics computed from the - agent running the set of experiments. - """ - - # Instantiate a metric object that will be used to compute the metrics for - # the benchmark afterwards. - metrics_object = Metrics(experiment_suite.metrics_parameters, - experiment_suite.dynamic_tasks) - - # Function returns the current pose and task for this benchmark. - start_pose, start_experiment = self._recording.get_pose_and_experiment( - experiment_suite.get_number_of_poses_task()) - - logging.info('START') - - for experiment in experiment_suite.get_experiments()[int(start_experiment):]: - - positions = client.load_settings( - experiment.conditions).player_start_spots - - self._recording.log_start(experiment.task) - - for pose in experiment.poses[start_pose:]: - for rep in range(experiment.repetitions): - - start_index = pose[0] - end_index = pose[1] - - client.start_episode(start_index) - # Print information on - logging.info('======== !!!! ==========') - logging.info(' Start Position %d End Position %d ', - start_index, end_index) - - self._recording.log_poses(start_index, end_index, - experiment.Conditions.WeatherId) - - # Calculate the initial distance for this episode - initial_distance = \ - sldist( - [positions[start_index].location.x, positions[start_index].location.y], - [positions[end_index].location.x, positions[end_index].location.y]) - - time_out = experiment_suite.calculate_time_out( - self._get_shortest_path(positions[start_index], positions[end_index])) - - # running the agent - (result, reward_vec, control_vec, final_time, remaining_distance) = \ - self._run_navigation_episode( - agent, client, time_out, positions[end_index], - str(experiment.Conditions.WeatherId) + '_' - + str(experiment.task) + '_' + str(start_index) - + '.' + str(end_index)) - - # Write the general status of the just ran episode - self._recording.write_summary_results( - experiment, pose, rep, initial_distance, - remaining_distance, final_time, time_out, result) - - # Write the details of this episode. - self._recording.write_measurements_results(experiment, rep, pose, reward_vec, - control_vec) - if result > 0: - logging.info('+++++ Target achieved in %f seconds! +++++', - final_time) - else: - logging.info('----- Timeout! -----') - - start_pose = 0 - - self._recording.log_end() - - return metrics_object.compute(self._recording.path) - - def get_path(self): - """ - Returns the path where the log was saved. - """ - return self._recording.path - - def _get_directions(self, current_point, end_point): - """ - Class that should return the directions to reach a certain goal - """ - - directions = self._planner.get_next_command( - (current_point.location.x, - current_point.location.y, 0.22), - (current_point.orientation.x, - current_point.orientation.y, - current_point.orientation.z), - (end_point.location.x, end_point.location.y, 0.22), - (end_point.orientation.x, end_point.orientation.y, end_point.orientation.z)) - return directions - - def _get_shortest_path(self, start_point, end_point): - """ - Calculates the shortest path between two points considering the road network - """ - - return self._planner.get_shortest_path_distance( - [ - start_point.location.x, start_point.location.y, 0.22], [ - start_point.orientation.x, start_point.orientation.y, 0.22], [ - end_point.location.x, end_point.location.y, end_point.location.z], [ - end_point.orientation.x, end_point.orientation.y, end_point.orientation.z]) - - def _run_navigation_episode( - self, - agent, - client, - time_out, - target, - episode_name): - """ - Runs one episode of the benchmark (Pose) for a certain agent. - - - Args: - agent: the agent object - client: an object of the carla client to communicate - with the CARLA simulator - time_out: the time limit to complete this episode - target: the target to reach - episode_name: The name for saving images of this episode - - """ - - # Send an initial command. - measurements, sensor_data = client.read_data() - client.send_control(VehicleControl()) - - initial_timestamp = measurements.game_timestamp - current_timestamp = initial_timestamp - - # The vector containing all measurements produced on this episode - measurement_vec = [] - # The vector containing all controls produced on this episode - control_vec = [] - frame = 0 - distance = 10000 - success = False - - while (current_timestamp - initial_timestamp) < (time_out * 1000) and not success: - - # Read data from server with the client - measurements, sensor_data = client.read_data() - # The directions to reach the goal are calculated. - directions = self._get_directions(measurements.player_measurements.transform, target) - # The agent processes the data. - control = agent.run_step(measurements, sensor_data, directions, target) - # Send the control commands to the vehicle - client.send_control(control) - - # save images if the flag is activated - self._recording.save_images(sensor_data, episode_name, frame) - - current_x = measurements.player_measurements.transform.location.x - current_y = measurements.player_measurements.transform.location.y - - logging.info("Controller is Inputting:") - logging.info('Steer = %f Throttle = %f Brake = %f ', - control.steer, control.throttle, control.brake) - - current_timestamp = measurements.game_timestamp - # Get the distance travelled until now - distance = sldist([current_x, current_y], - [target.location.x, target.location.y]) - # Write status of the run on verbose mode - logging.info('Status:') - logging.info( - '[d=%f] c_x = %f, c_y = %f ---> t_x = %f, t_y = %f', - float(distance), current_x, current_y, target.location.x, - target.location.y) - # Check if reach the target - if distance < self._distance_for_success: - success = True - - # Increment the vectors and append the measurements and controls. - frame += 1 - measurement_vec.append(measurements.player_measurements) - control_vec.append(control) - - if success: - return 1, measurement_vec, control_vec, float( - current_timestamp - initial_timestamp) / 1000.0, distance - return 0, measurement_vec, control_vec, time_out, distance - - -def run_driving_benchmark(agent, - experiment_suite, - city_name='Town01', - log_name='Test', - continue_experiment=False, - host='127.0.0.1', - port=2000 - ): - while True: - try: - - with make_carla_client(host, port) as client: - # Hack to fix for the issue 310, we force a reset, so it does not get - # the positions on first server reset. - client.load_settings(CarlaSettings()) - client.start_episode(0) - - # We instantiate the driving benchmark, that is the engine used to - # benchmark an agent. The instantiation starts the log process, sets - - benchmark = DrivingBenchmark(city_name=city_name, - name_to_save=log_name + '_' - + type(experiment_suite).__name__ - + '_' + city_name, - continue_experiment=continue_experiment) - # This function performs the benchmark. It returns a dictionary summarizing - # the entire execution. - - benchmark_summary = benchmark.benchmark_agent(experiment_suite, agent, client) - - print("") - print("") - print("----- Printing results for training weathers (Seen in Training) -----") - print("") - print("") - results_printer.print_summary(benchmark_summary, experiment_suite.train_weathers, - benchmark.get_path()) - - print("") - print("") - print("----- Printing results for test weathers (Unseen in Training) -----") - print("") - print("") - - results_printer.print_summary(benchmark_summary, experiment_suite.test_weathers, - benchmark.get_path()) - - break - - except TCPConnectionError as error: - logging.error(error) - time.sleep(1) diff --git a/Deprecated/PythonClient/carla/driving_benchmark/experiment.py b/Deprecated/PythonClient/carla/driving_benchmark/experiment.py deleted file mode 100644 index 439dd8e81..000000000 --- a/Deprecated/PythonClient/carla/driving_benchmark/experiment.py +++ /dev/null @@ -1,53 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -from carla.settings import CarlaSettings - - -class Experiment(object): - """ - Experiment defines a certain task, under conditions - A task is associated with a set of poses, containing start and end pose. - - Conditions are associated with a carla Settings and describe the following: - - Number Of Vehicles - Number Of Pedestrians - Weather - Random Seed of the agents, describing their behaviour. - - """ - - def __init__(self): - self.Task = 0 - self.Conditions = CarlaSettings() - self.Poses = [[]] - self.Repetitions = 1 - - def set(self, **kwargs): - for key, value in kwargs.items(): - if not hasattr(self, key): - raise ValueError('Experiment: no key named %r' % key) - setattr(self, key, value) - - if self.Repetitions != 1: - raise NotImplementedError() - - @property - def task(self): - return self.Task - - @property - def conditions(self): - return self.Conditions - - @property - def poses(self): - return self.Poses - - @property - def repetitions(self): - return self.Repetitions diff --git a/Deprecated/PythonClient/carla/driving_benchmark/experiment_suites/__init__.py b/Deprecated/PythonClient/carla/driving_benchmark/experiment_suites/__init__.py deleted file mode 100644 index dbbe633c1..000000000 --- a/Deprecated/PythonClient/carla/driving_benchmark/experiment_suites/__init__.py +++ /dev/null @@ -1,2 +0,0 @@ -from .basic_experiment_suite import BasicExperimentSuite -from .corl_2017 import CoRL2017 diff --git a/Deprecated/PythonClient/carla/driving_benchmark/experiment_suites/basic_experiment_suite.py b/Deprecated/PythonClient/carla/driving_benchmark/experiment_suites/basic_experiment_suite.py deleted file mode 100644 index e56d2b10e..000000000 --- a/Deprecated/PythonClient/carla/driving_benchmark/experiment_suites/basic_experiment_suite.py +++ /dev/null @@ -1,83 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - - -from __future__ import print_function - -from carla.driving_benchmark.experiment import Experiment -from carla.sensor import Camera -from carla.settings import CarlaSettings - -from .experiment_suite import ExperimentSuite - - -class BasicExperimentSuite(ExperimentSuite): - - @property - def train_weathers(self): - return [1] - - @property - def test_weathers(self): - return [1] - - 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 diff --git a/Deprecated/PythonClient/carla/driving_benchmark/experiment_suites/corl_2017.py b/Deprecated/PythonClient/carla/driving_benchmark/experiment_suites/corl_2017.py deleted file mode 100644 index 3a2e36853..000000000 --- a/Deprecated/PythonClient/carla/driving_benchmark/experiment_suites/corl_2017.py +++ /dev/null @@ -1,144 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -# CORL experiment set. - -from __future__ import print_function - -from carla.driving_benchmark.experiment import Experiment -from carla.sensor import Camera -from carla.settings import CarlaSettings -from carla.driving_benchmark.experiment_suites.experiment_suite import ExperimentSuite - - -class CoRL2017(ExperimentSuite): - - @property - def train_weathers(self): - return [1, 3, 6, 8] - - @property - def test_weathers(self): - return [4, 14] - - def _poses_town01(self): - """ - Each matrix is a new task. We have all the four tasks - - """ - - def _poses_straight(): - return [[36, 40], [39, 35], [110, 114], [7, 3], [0, 4], - [68, 50], [61, 59], [47, 64], [147, 90], [33, 87], - [26, 19], [80, 76], [45, 49], [55, 44], [29, 107], - [95, 104], [84, 34], [53, 67], [22, 17], [91, 148], - [20, 107], [78, 70], [95, 102], [68, 44], [45, 69]] - - def _poses_one_curve(): - return [[138, 17], [47, 16], [26, 9], [42, 49], [140, 124], - [85, 98], [65, 133], [137, 51], [76, 66], [46, 39], - [40, 60], [0, 29], [4, 129], [121, 140], [2, 129], - [78, 44], [68, 85], [41, 102], [95, 70], [68, 129], - [84, 69], [47, 79], [110, 15], [130, 17], [0, 17]] - - def _poses_navigation(): - return [[105, 29], [27, 130], [102, 87], [132, 27], [24, 44], - [96, 26], [34, 67], [28, 1], [140, 134], [105, 9], - [148, 129], [65, 18], [21, 16], [147, 97], [42, 51], - [30, 41], [18, 107], [69, 45], [102, 95], [18, 145], - [111, 64], [79, 45], [84, 69], [73, 31], [37, 81]] - - return [_poses_straight(), - _poses_one_curve(), - _poses_navigation(), - _poses_navigation()] - - def _poses_town02(self): - - def _poses_straight(): - return [[38, 34], [4, 2], [12, 10], [62, 55], [43, 47], - [64, 66], [78, 76], [59, 57], [61, 18], [35, 39], - [12, 8], [0, 18], [75, 68], [54, 60], [45, 49], - [46, 42], [53, 46], [80, 29], [65, 63], [0, 81], - [54, 63], [51, 42], [16, 19], [17, 26], [77, 68]] - - def _poses_one_curve(): - return [[37, 76], [8, 24], [60, 69], [38, 10], [21, 1], - [58, 71], [74, 32], [44, 0], [71, 16], [14, 24], - [34, 11], [43, 14], [75, 16], [80, 21], [3, 23], - [75, 59], [50, 47], [11, 19], [77, 34], [79, 25], - [40, 63], [58, 76], [79, 55], [16, 61], [27, 11]] - - def _poses_navigation(): - return [[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]] - - return [_poses_straight(), - _poses_one_curve(), - _poses_navigation(), - _poses_navigation() - ] - - 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 diff --git a/Deprecated/PythonClient/carla/driving_benchmark/experiment_suites/experiment_suite.py b/Deprecated/PythonClient/carla/driving_benchmark/experiment_suites/experiment_suite.py deleted file mode 100644 index c79823bdc..000000000 --- a/Deprecated/PythonClient/carla/driving_benchmark/experiment_suites/experiment_suite.py +++ /dev/null @@ -1,102 +0,0 @@ -# To be redefined on subclasses on how to calculate timeout for an episode -import abc - - -class ExperimentSuite(object): - - def __init__(self, city_name): - - self._city_name = city_name - self._experiments = self.build_experiments() - - def calculate_time_out(self, path_distance): - """ - Function to return the timeout ,in milliseconds, - that is calculated based on distance to goal. - This is the same timeout as used on the CoRL paper. - """ - return ((path_distance / 1000.0) / 10.0) * 3600.0 + 10.0 - - def get_number_of_poses_task(self): - """ - Get the number of poses a task have for this benchmark - """ - - # Warning: assumes that all tasks have the same size - - return len(self._experiments[0].poses) - - def get_experiments(self): - """ - Getter for the experiment set. - """ - return self._experiments - - @property - def dynamic_tasks(self): - """ - Returns the episodes that contain dynamic obstacles - """ - dynamic_tasks = set() - for exp in self._experiments: - if exp.conditions.NumberOfVehicles > 0 or exp.conditions.NumberOfPedestrians > 0: - dynamic_tasks.add(exp.task) - - return list(dynamic_tasks) - - @property - def metrics_parameters(self): - """ - Property to return the parameters for the metric module - Could be redefined depending on the needs of the user. - """ - return { - - 'intersection_offroad': {'frames_skip': 10, - 'frames_recount': 20, - 'threshold': 0.3 - }, - 'intersection_otherlane': {'frames_skip': 10, - 'frames_recount': 20, - 'threshold': 0.4 - }, - 'collision_other': {'frames_skip': 10, - 'frames_recount': 20, - 'threshold': 400 - }, - 'collision_vehicles': {'frames_skip': 10, - 'frames_recount': 30, - 'threshold': 400 - }, - 'collision_pedestrians': {'frames_skip': 5, - 'frames_recount': 100, - 'threshold': 300 - }, - - } - - @property - def weathers(self): - weathers = set(self.train_weathers) - weathers.update(self.test_weathers) - return weathers - - @abc.abstractmethod - def build_experiments(self): - """ - Returns a set of experiments to be evaluated - Must be redefined in an inherited class. - - """ - - @abc.abstractproperty - def train_weathers(self): - """ - Return the weathers that are considered as training conditions - """ - - @abc.abstractproperty - def test_weathers(self): - """ - Return the weathers that are considered as testing conditions - """ diff --git a/Deprecated/PythonClient/carla/driving_benchmark/metrics.py b/Deprecated/PythonClient/carla/driving_benchmark/metrics.py deleted file mode 100644 index f4e1b2266..000000000 --- a/Deprecated/PythonClient/carla/driving_benchmark/metrics.py +++ /dev/null @@ -1,335 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - - -import numpy as np -import math -import os - -sldist = lambda c1, c2: math.sqrt((c2[0] - c1[0]) ** 2 + (c2[1] - c1[1]) ** 2) -flatten = lambda l: [item for sublist in l for item in sublist] - - -class Metrics(object): - """ - The metrics class is made to take the driving measurements - and calculate some specific performance metrics. - - """ - - def __init__(self, parameters, dynamic_tasks): - """ - Args - parameters: A dictionary with the used parameters for checking how to count infractions - dynamic_tasks: A list of the all dynamic tasks (That contain dynamic objects) - """ - - self._parameters = parameters - self._parameters['dynamic_tasks'] = dynamic_tasks - - def _divide_by_episodes(self, measurements_matrix, header): - - """ - Divides the measurements matrix on different episodes. - - Args: - measurements_matrix: The full measurements matrix - header: The header from the measurements matrix - - """ - - # Read previous for position zero - prev_start = measurements_matrix[0, header.index('start_point')] - prev_end = measurements_matrix[0, header.index('end_point')] - prev_exp_id = measurements_matrix[0, header.index('exp_id')] - - # Start at the position 1. - i = 1 - prev_i_position = 0 - episode_matrix_metrics = [] - - while i < measurements_matrix.shape[0]: - - current_start = measurements_matrix[i, header.index('start_point')] - current_end = measurements_matrix[i, header.index('end_point')] - current_exp_id = measurements_matrix[i, header.index('exp_id')] - - # If there is a change in the position it means it is a new episode for sure. - if (current_start != prev_start and current_end != prev_end) \ - or current_exp_id != prev_exp_id: - episode_matrix_metrics.append(measurements_matrix[prev_i_position:i, :]) - prev_i_position = i - - prev_start = current_start - prev_end = current_end - prev_exp_id = current_exp_id - - i += 1 - - episode_matrix_metrics.append(measurements_matrix[prev_i_position:-1, :]) - - return episode_matrix_metrics - - def _get_collisions(self, selected_matrix, header): - """ - Get the number of collisions for pedestrians, vehicles or other - Args: - selected_matrix: The matrix with all the experiments summary - header: The header , to know the positions of details - - - """ - count_collisions_general = 0 - count_collisions_pedestrian = 0 - count_collisions_vehicle = 0 - i = 1 - # Computing general collisions - while i < selected_matrix.shape[0]: - if (selected_matrix[i, header.index('collision_other')] - - selected_matrix[ - (i - self._parameters['collision_other']['frames_skip']), header.index( - 'collision_other')]) > \ - self._parameters['collision_other']['threshold']: - count_collisions_general += 1 - i += self._parameters['collision_other']['frames_recount'] - i += 1 - - i = 1 - # Computing collisions for vehicles - while i < selected_matrix.shape[0]: - if (selected_matrix[i, header.index('collision_vehicles')] - - selected_matrix[ - (i - self._parameters['collision_vehicles']['frames_skip']), header.index( - 'collision_vehicles')]) > \ - self._parameters['collision_vehicles']['threshold']: - count_collisions_vehicle += 1 - i += self._parameters['collision_vehicles']['frames_recount'] - i += 1 - - i = 1 - - # Computing the collisions for pedestrians - while i < selected_matrix.shape[0]: - if (selected_matrix[i, header.index('collision_pedestrians')] - - selected_matrix[i - self._parameters['collision_pedestrians']['frames_skip'], - header.index('collision_pedestrians')]) > \ - self._parameters['collision_pedestrians']['threshold']: - count_collisions_pedestrian += 1 - i += self._parameters['collision_pedestrians']['frames_recount'] - i += 1 - - return count_collisions_general, count_collisions_vehicle, count_collisions_pedestrian - - def _get_distance_traveled(self, selected_matrix, header): - """ - Compute the total distance travelled - Args: - selected_matrix: The matrix with all the experiments summary - header: The header , to know the positions of details - - - """ - - prev_x = selected_matrix[0, header.index('pos_x')] - prev_y = selected_matrix[0, header.index('pos_y')] - - i = 1 - acummulated_distance = 0 - - while i < selected_matrix.shape[0]: - x = selected_matrix[i, header.index('pos_x')] - y = selected_matrix[i, header.index('pos_y')] - - acummulated_distance += sldist((x, y), (prev_x, prev_y)) - - prev_x = x - prev_y = y - - i += 1 - - return acummulated_distance / (1000.0) - - def _get_out_of_road_lane(self, selected_matrix, header): - - """ - Check for the situations were the agent goes out of the road. - Args: - selected_matrix: The matrix with all the experiments summary - header: The header , to know the positions of details - - - """ - - count_sidewalk_intersect = 0 - count_lane_intersect = 0 - - i = 0 - - while i < selected_matrix.shape[0]: - - if (selected_matrix[i, header.index('intersection_offroad')] - - selected_matrix[(i - self._parameters['intersection_offroad']['frames_skip']), - header.index('intersection_offroad')]) \ - > self._parameters['intersection_offroad']['threshold']: - count_sidewalk_intersect += 1 - i += self._parameters['intersection_offroad']['frames_recount'] - if i >= selected_matrix.shape[0]: - break - - if (selected_matrix[i, header.index('intersection_otherlane')] - - selected_matrix[(i - self._parameters['intersection_otherlane']['frames_skip']), - header.index('intersection_otherlane')]) \ - > self._parameters['intersection_otherlane']['threshold']: - count_lane_intersect += 1 - i += self._parameters['intersection_otherlane']['frames_recount'] - - i += 1 - - return count_lane_intersect, count_sidewalk_intersect - - def compute(self, path): - - """ - Compute a dictionary containing the following metrics - - * Off Road Intersection: The number of times the agent goes out of the road. - The intersection is only counted if the area of the vehicle outside - of the road is bigger than a *threshold*. - - * Other Lane Intersection: The number of times the agent goes to the other - lane. The intersection is only counted if the area of the vehicle on the - other lane is bigger than a *threshold*. - - * Vehicle Collisions: The number of collisions with vehicles that have - an impact bigger than a *threshold*. - - * Pedestrian Collisions: The number of collisions with pedestrians - that have an impact bigger than a threshold. - - * General Collisions: The number of collisions with all other - objects. - - - Args: - path: Path where the log files are. - - """ - - with open(os.path.join(path, 'summary.csv'), "rU") as f: - header = f.readline() - header = header.split(',') - header[-1] = header[-1][:-1] - - with open(os.path.join(path, 'measurements.csv'), "rU") as f: - - header_metrics = f.readline() - header_metrics = header_metrics.split(',') - header_metrics[-1] = header_metrics[-1][:-1] - - result_matrix = np.loadtxt(os.path.join(path, 'summary.csv'), delimiter=",", skiprows=1) - - # Corner Case: The presented test just had one episode - if result_matrix.ndim == 1: - result_matrix = np.expand_dims(result_matrix, axis=0) - - tasks = np.unique(result_matrix[:, header.index('exp_id')]) - - all_weathers = np.unique(result_matrix[:, header.index('weather')]) - - measurements_matrix = np.loadtxt(os.path.join(path, 'measurements.csv'), delimiter=",", - skiprows=1) - - metrics_dictionary = {'episodes_completion': {w: [0] * len(tasks) for w in all_weathers}, - 'intersection_offroad': {w: [[] for i in range(len(tasks))] for w in - all_weathers}, - 'intersection_otherlane': {w: [[] for i in range(len(tasks))] for w in - all_weathers}, - 'collision_pedestrians': {w: [[] for i in range(len(tasks))] for w in - all_weathers}, - 'collision_vehicles': {w: [[] for i in range(len(tasks))] for w in - all_weathers}, - 'collision_other': {w: [[] for i in range(len(tasks))] for w in - all_weathers}, - 'episodes_fully_completed': {w: [0] * len(tasks) for w in - all_weathers}, - 'average_speed': {w: [0] * len(tasks) for w in all_weathers}, - 'driven_kilometers': {w: [0] * len(tasks) for w in all_weathers} - } - - for t in range(len(tasks)): - experiment_results_matrix = result_matrix[ - result_matrix[:, header.index('exp_id')] == tasks[t]] - - weathers = np.unique(experiment_results_matrix[:, header.index('weather')]) - - for w in weathers: - - experiment_results_matrix = result_matrix[ - np.logical_and(result_matrix[:, header.index( - 'exp_id')] == tasks[t], result_matrix[:, header.index('weather')] == w)] - - experiment_metrics_matrix = measurements_matrix[ - np.logical_and(measurements_matrix[:, header_metrics.index( - 'exp_id')] == float(tasks[t]), - measurements_matrix[:, header_metrics.index('weather')] == float( - w))] - - metrics_dictionary['episodes_fully_completed'][w][t] = \ - experiment_results_matrix[:, header.index('result')].tolist() - - metrics_dictionary['episodes_completion'][w][t] = \ - ((experiment_results_matrix[:, header.index('initial_distance')] - - experiment_results_matrix[:, header.index('final_distance')]) - / experiment_results_matrix[:, header.index('initial_distance')]).tolist() - - # Now we divide the experiment metrics matrix - - episode_experiment_metrics_matrix = self._divide_by_episodes( - experiment_metrics_matrix, header_metrics) - - count = 0 - - for episode_experiment_metrics in episode_experiment_metrics_matrix: - - km_run_episodes = self._get_distance_traveled( - episode_experiment_metrics, header_metrics) - metrics_dictionary['driven_kilometers'][w][t] += km_run_episodes - metrics_dictionary['average_speed'][w][t] = \ - km_run_episodes / (experiment_results_matrix[count, - header.index( - 'final_time')] / 3600.0) - count += 1 - - lane_road = self._get_out_of_road_lane( - episode_experiment_metrics, header_metrics) - - metrics_dictionary['intersection_otherlane'][ - w][t].append(lane_road[0]) - metrics_dictionary['intersection_offroad'][ - w][t].append(lane_road[1]) - - if tasks[t] in set(self._parameters['dynamic_tasks']): - - collisions = self._get_collisions(episode_experiment_metrics, - header_metrics) - - metrics_dictionary['collision_pedestrians'][ - w][t].append(collisions[2]) - metrics_dictionary['collision_vehicles'][ - w][t].append(collisions[1]) - metrics_dictionary['collision_other'][ - w][t].append(collisions[0]) - - else: - - metrics_dictionary['collision_pedestrians'][ - w][t].append(0) - metrics_dictionary['collision_vehicles'][ - w][t].append(0) - metrics_dictionary['collision_other'][ - w][t].append(0) - - return metrics_dictionary diff --git a/Deprecated/PythonClient/carla/driving_benchmark/recording.py b/Deprecated/PythonClient/carla/driving_benchmark/recording.py deleted file mode 100644 index b5e44c8cc..000000000 --- a/Deprecated/PythonClient/carla/driving_benchmark/recording.py +++ /dev/null @@ -1,276 +0,0 @@ -import csv -import datetime -import os - - -class Recording(object): - """ - Class to record all the logs for the benchmark. It records individual episodes measurements - and also summary for each episodes. - """ - - def __init__(self, name_to_save, continue_experiment, save_images): - """ - Recorder constructors - Args: - name_to_save: Name of the log - continue_experiment: If you want to continue a previous experiment with the same names - save_images: If you want to save images to the disk. - """ - - self._dict_summary = {'exp_id': -1, - 'rep': -1, - 'weather': -1, - 'start_point': -1, - 'end_point': -1, - 'result': -1, - 'initial_distance': -1, - 'final_distance': -1, - 'final_time': -1, - 'time_out': -1 - } - self._dict_measurements = {'exp_id': -1, - 'rep': -1, - 'weather': -1, - 'start_point': -1, - 'end_point': -1, - 'collision_other': -1, - 'collision_pedestrians': -1, - 'collision_vehicles': -1, - 'intersection_otherlane': -1, - 'intersection_offroad': -1, - 'pos_x': -1, - 'pos_y': -1, - 'steer': -1, - 'throttle': -1, - 'brake': -1 - } - - # Just in the case is the first time and there is no benchmark results folder - if not os.path.exists('_benchmarks_results'): - os.mkdir('_benchmarks_results') - - # Generate the full path for the log files - self._path = os.path.join('_benchmarks_results', name_to_save) - - # Check for continuation of experiment, also returns the last line, used for test purposes - # If you don't want to continue it will create a new path name with a number. - # Also returns the fieldnames for both measurements and summary, so you can keep the - # previous order - self._path, _, self._summary_fieldnames, self._measurements_fieldnames \ - = self._continue_experiment(continue_experiment) - - self._create_log_files() - - # A log with a date file: to show when was the last access and log what was tested, - now = datetime.datetime.now() - self._internal_log_name = os.path.join(self._path, 'log_' + now.strftime("%Y%m%d%H%M")) - open(self._internal_log_name, 'w').close() - - # store the save images flag, and already store the format for image saving - self._save_images = save_images - self._image_filename_format = os.path.join( - self._path, '_images/episode_{:s}/{:s}/image_{:0>5d}.jpg') - - @property - def path(self): - return self._path - - def log_poses(self, start_index, end_index, weather_id): - """ - Log tested poses by the benchmark - """ - with open(self._internal_log_name, 'a+') as log: - log.write(' Start Poses (%d %d ) on weather %d \n ' % - (start_index, end_index, weather_id)) - - def log_poses_finish(self): - """ - Log when a set of poses (task) is finished by the benchmark - """ - with open(self._internal_log_name, 'a+') as log: - log.write('Finished Task') - - def log_start(self, id_experiment): - """ - Log when a set of poses (task) is started by the benchmark - """ - with open(self._internal_log_name, 'a+') as log: - log.write('Start Task %d \n' % id_experiment) - - def log_end(self): - """ - Log when the benchmark is finished - """ - with open(self._internal_log_name, 'a+') as log: - log.write('====== Finished Entire Benchmark ======') - - def write_summary_results(self, experiment, pose, rep, - path_distance, remaining_distance, - final_time, time_out, result): - """ - Method to record the summary of an episode(pose) execution - """ - - self._dict_summary['exp_id'] = experiment.task - self._dict_summary['rep'] = rep - self._dict_summary['weather'] = experiment.Conditions.WeatherId - self._dict_summary['start_point'] = pose[0] - self._dict_summary['end_point'] = pose[1] - self._dict_summary['result'] = result - self._dict_summary['initial_distance'] = path_distance - self._dict_summary['final_distance'] = remaining_distance - self._dict_summary['final_time'] = final_time - self._dict_summary['time_out'] = time_out - - with open(os.path.join(self._path, 'summary.csv'), 'a+') as ofd: - w = csv.DictWriter(ofd, self._dict_summary.keys()) - w.fieldnames = self._summary_fieldnames - w.writerow(self._dict_summary) - - def write_measurements_results(self, experiment, rep, pose, reward_vec, control_vec): - """ - Method to record the measurements, sensors, - controls and status of the entire benchmark. - """ - with open(os.path.join(self._path, 'measurements.csv'), 'a+') as rfd: - mw = csv.DictWriter(rfd, self._dict_measurements.keys()) - mw.fieldnames = self._measurements_fieldnames - for i in range(len(reward_vec)): - self._dict_measurements['exp_id'] = experiment.task - self._dict_measurements['rep'] = rep - self._dict_measurements['start_point'] = pose[0] - self._dict_measurements['end_point'] = pose[1] - self._dict_measurements['weather'] = experiment.Conditions.WeatherId - self._dict_measurements['collision_other'] = reward_vec[ - i].collision_other - self._dict_measurements['collision_pedestrians'] = reward_vec[ - i].collision_pedestrians - self._dict_measurements['collision_vehicles'] = reward_vec[ - i].collision_vehicles - self._dict_measurements['intersection_otherlane'] = reward_vec[ - i].intersection_otherlane - self._dict_measurements['intersection_offroad'] = reward_vec[ - i].intersection_offroad - self._dict_measurements['pos_x'] = reward_vec[ - i].transform.location.x - self._dict_measurements['pos_y'] = reward_vec[ - i].transform.location.y - self._dict_measurements['steer'] = control_vec[ - i].steer - self._dict_measurements['throttle'] = control_vec[ - i].throttle - self._dict_measurements['brake'] = control_vec[ - i].brake - - mw.writerow(self._dict_measurements) - - def _create_log_files(self): - """ - Just create the log files and add the necessary header for it. - """ - - if not self._experiment_exist(): - os.mkdir(self._path) - - with open(os.path.join(self._path, 'summary.csv'), 'w') as ofd: - sw = csv.DictWriter(ofd, self._dict_summary.keys()) - sw.writeheader() - if self._summary_fieldnames is None: - self._summary_fieldnames = sw.fieldnames - - with open(os.path.join(self._path, 'measurements.csv'), 'w') as rfd: - mw = csv.DictWriter(rfd, self._dict_measurements.keys()) - mw.writeheader() - if self._measurements_fieldnames is None: - self._measurements_fieldnames = mw.fieldnames - - def _continue_experiment(self, continue_experiment): - """ - Get the line on the file for the experiment. - If continue_experiment is false and experiment exist, generates a new file path - - """ - - def get_non_existent_path(f_name_path): - """ - Get the path to a filename which does not exist by incrementing path. - """ - if not os.path.exists(f_name_path): - return f_name_path - filename, file_extension = os.path.splitext(f_name_path) - i = 1 - new_f_name = "{}-{}{}".format(filename, i, file_extension) - while os.path.exists(new_f_name): - i += 1 - new_f_name = "{}-{}{}".format(filename, i, file_extension) - return new_f_name - - # start the new path as the same one as before - new_path = self._path - summary_fieldnames = None - measurements_fieldnames = None - - # if the experiment exist - if self._experiment_exist(): - - # If you want to continue just get the last position - if continue_experiment: - line_on_file = self._get_last_position() - # Get the previously used fileorder - with open(os.path.join(self._path, 'summary.csv'), 'r') as ofd: - summary_reader = csv.DictReader(ofd) - summary_fieldnames = summary_reader.fieldnames - with open(os.path.join(self._path, 'measurements.csv'), 'r') as ofd: - measurements_reader = csv.DictReader(ofd) - measurements_fieldnames = measurements_reader.fieldnames - - else: - # Get a new non_conflicting path name - new_path = get_non_existent_path(new_path) - line_on_file = 1 - - else: - line_on_file = 1 - return new_path, line_on_file, summary_fieldnames, measurements_fieldnames - - def save_images(self, sensor_data, episode_name, frame): - """ - Save a image during the experiment - """ - if self._save_images: - for name, image in sensor_data.items(): - image.save_to_disk(self._image_filename_format.format( - episode_name, name, frame)) - - def get_pose_and_experiment(self, number_poses_task): - """ - Based on the line in log file, return the current pose and experiment. - If the line is zero, create new log files. - - """ - # Warning: assumes that all tasks have the same size - line_on_file = self._get_last_position() - 1 - if line_on_file == 0: - return 0, 0 - - return line_on_file % number_poses_task, line_on_file // number_poses_task - - def _experiment_exist(self): - """ Check if the experiment exists""" - return os.path.exists(self._path) - - def _get_last_position(self): - """ - Get the last position on the summary experiment file - With this you are able to continue from there - - Returns: - int, position: - """ - # Try to open, if the file is not found - try: - with open(os.path.join(self._path, 'summary.csv')) as f: - return sum(1 for _ in f) - except IOError: - return 0 diff --git a/Deprecated/PythonClient/carla/driving_benchmark/results_printer.py b/Deprecated/PythonClient/carla/driving_benchmark/results_printer.py deleted file mode 100644 index e7af469c4..000000000 --- a/Deprecated/PythonClient/carla/driving_benchmark/results_printer.py +++ /dev/null @@ -1,124 +0,0 @@ -import os -import numpy as np -import json - - -def print_summary(metrics_summary, weathers, path): - """ - We plot the summary of the testing for the set selected weathers. - - We take the raw data and print the way it was described on CORL 2017 paper - - """ - - # Improve readability by adding a weather dictionary - weather_name_dict = {1: 'Clear Noon', 3: 'After Rain Noon', - 6: 'Heavy Rain Noon', 8: 'Clear Sunset', - 4: 'Cloudy After Rain', 14: 'Soft Rain Sunset'} - - # First we write the entire dictionary on the benchmark folder. - with open(os.path.join(path, 'metrics.json'), 'w') as fo: - fo.write(json.dumps(metrics_summary)) - - # Second we plot the metrics that are already ready by averaging - - metrics_to_average = [ - 'episodes_fully_completed', - 'episodes_completion' - - ] - # We compute the number of episodes based on size of average completion - number_of_episodes = len(list(metrics_summary['episodes_fully_completed'].items())[0][1]) - - for metric in metrics_to_average: - - if metric == 'episodes_completion': - print ("Average Percentage of Distance to Goal Travelled ") - else: - print ("Percentage of Successful Episodes") - - print ("") - values = metrics_summary[metric] - - metric_sum_values = np.zeros(number_of_episodes) - for weather, tasks in values.items(): - if weather in set(weathers): - print(' Weather: ', weather_name_dict[weather]) - count = 0 - for t in tasks: - # if isinstance(t, np.ndarray) or isinstance(t, list): - if t == []: - print(' Metric Not Computed') - else: - print(' Task:', count, ' -> ', float(sum(t)) / float(len(t))) - metric_sum_values[count] += (float(sum(t)) / float(len(t))) * 1.0 / float( - len(weathers)) - - count += 1 - - print (' Average Between Weathers') - for i in range(len(metric_sum_values)): - print(' Task ', i, ' -> ', metric_sum_values[i]) - print ("") - - infraction_metrics = [ - 'collision_pedestrians', - 'collision_vehicles', - 'collision_other', - 'intersection_offroad', - 'intersection_otherlane' - - ] - - # We need to collect the total number of kilometers for each task - - for metric in infraction_metrics: - values_driven = metrics_summary['driven_kilometers'] - values = metrics_summary[metric] - metric_sum_values = np.zeros(number_of_episodes) - summed_driven_kilometers = np.zeros(number_of_episodes) - - if metric == 'collision_pedestrians': - print ('Avg. Kilometers driven before a collision to a PEDESTRIAN') - elif metric == 'collision_vehicles': - print('Avg. Kilometers driven before a collision to a VEHICLE') - elif metric == 'collision_other': - print('Avg. Kilometers driven before a collision to a STATIC OBSTACLE') - elif metric == 'intersection_offroad': - print('Avg. Kilometers driven before going OUTSIDE OF THE ROAD') - else: - print('Avg. Kilometers driven before invading the OPPOSITE LANE') - - # print (zip(values.items(), values_driven.items())) - for items_metric, items_driven in zip(values.items(), values_driven.items()): - weather = items_metric[0] - tasks = items_metric[1] - tasks_driven = items_driven[1] - - if weather in set(weathers): - print(' Weather: ', weather_name_dict[weather]) - count = 0 - for t, t_driven in zip(tasks, tasks_driven): - # if isinstance(t, np.ndarray) or isinstance(t, list): - if t == []: - print('Metric Not Computed') - else: - if sum(t) > 0: - print(' Task ', count, ' -> ', t_driven / float(sum(t))) - else: - print(' Task ', count, ' -> more than', t_driven) - - metric_sum_values[count] += float(sum(t)) - summed_driven_kilometers[count] += t_driven - - count += 1 - print (' Average Between Weathers') - for i in range(len(metric_sum_values)): - if metric_sum_values[i] == 0: - print(' Task ', i, ' -> more than ', summed_driven_kilometers[i]) - else: - print(' Task ', i, ' -> ', summed_driven_kilometers[i] / metric_sum_values[i]) - print ("") - - print("") - print("") diff --git a/Deprecated/PythonClient/carla/image_converter.py b/Deprecated/PythonClient/carla/image_converter.py deleted file mode 100644 index d1dcf1ac9..000000000 --- a/Deprecated/PythonClient/carla/image_converter.py +++ /dev/null @@ -1,162 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -""" -Handy conversions for CARLA images. - -The functions here are provided for real-time display, if you want to save the -converted images, save the images from Python without conversion and convert -them afterwards with the C++ implementation at "Util/ImageConverter" as it -provides considerably better performance. -""" - -import math - -try: - import numpy - from numpy.matlib import repmat -except ImportError: - raise RuntimeError('cannot import numpy, make sure numpy package is installed') - - -from . import sensor - - -def to_bgra_array(image): - """Convert a CARLA raw image to a BGRA numpy array.""" - if not isinstance(image, sensor.Image): - raise ValueError("Argument must be a carla.sensor.Image") - array = numpy.frombuffer(image.raw_data, dtype=numpy.dtype("uint8")) - array = numpy.reshape(array, (image.height, image.width, 4)) - return array - - -def to_rgb_array(image): - """Convert a CARLA raw image to a RGB numpy array.""" - array = to_bgra_array(image) - # Convert BGRA to RGB. - array = array[:, :, :3] - array = array[:, :, ::-1] - return array - - -def labels_to_array(image): - """ - Convert an image containing CARLA semantic segmentation labels to a 2D array - containing the label of each pixel. - """ - return to_bgra_array(image)[:, :, 2] - - -def labels_to_cityscapes_palette(image): - """ - Convert an image containing CARLA semantic segmentation labels to - Cityscapes palette. - """ - classes = { - 0: [0, 0, 0], # None - 1: [70, 70, 70], # Buildings - 2: [190, 153, 153], # Fences - 3: [72, 0, 90], # Other - 4: [220, 20, 60], # Pedestrians - 5: [153, 153, 153], # Poles - 6: [157, 234, 50], # RoadLines - 7: [128, 64, 128], # Roads - 8: [244, 35, 232], # Sidewalks - 9: [107, 142, 35], # Vegetation - 10: [0, 0, 255], # Vehicles - 11: [102, 102, 156], # Walls - 12: [220, 220, 0] # TrafficSigns - } - array = labels_to_array(image) - result = numpy.zeros((array.shape[0], array.shape[1], 3)) - for key, value in classes.items(): - result[numpy.where(array == key)] = value - return result - - -def depth_to_array(image): - """ - Convert an image containing CARLA encoded depth-map to a 2D array containing - the depth value of each pixel normalized between [0.0, 1.0]. - """ - array = to_bgra_array(image) - array = array.astype(numpy.float32) - # Apply (R + G * 256 + B * 256 * 256) / (256 * 256 * 256 - 1). - normalized_depth = numpy.dot(array[:, :, :3], [65536.0, 256.0, 1.0]) - normalized_depth /= 16777215.0 # (256.0 * 256.0 * 256.0 - 1.0) - return normalized_depth - - -def depth_to_logarithmic_grayscale(image): - """ - Convert an image containing CARLA encoded depth-map to a logarithmic - grayscale image array. - "max_depth" is used to omit the points that are far enough. - """ - normalized_depth = depth_to_array(image) - # Convert to logarithmic depth. - logdepth = numpy.ones(normalized_depth.shape) + \ - (numpy.log(normalized_depth) / 5.70378) - logdepth = numpy.clip(logdepth, 0.0, 1.0) - logdepth *= 255.0 - # Expand to three colors. - return numpy.repeat(logdepth[:, :, numpy.newaxis], 3, axis=2) - - -def depth_to_local_point_cloud(image, color=None, max_depth=0.9): - """ - Convert an image containing CARLA encoded depth-map to a 2D array containing - the 3D position (relative to the camera) of each pixel and its corresponding - RGB color of an array. - "max_depth" is used to omit the points that are far enough. - """ - far = 1000.0 # max depth in meters. - normalized_depth = depth_to_array(image) - - # (Intrinsic) K Matrix - k = numpy.identity(3) - k[0, 2] = image.width / 2.0 - k[1, 2] = image.height / 2.0 - k[0, 0] = k[1, 1] = image.width / \ - (2.0 * math.tan(image.fov * math.pi / 360.0)) - - # 2d pixel coordinates - pixel_length = image.width * image.height - u_coord = repmat(numpy.r_[image.width-1:-1:-1], - image.height, 1).reshape(pixel_length) - v_coord = repmat(numpy.c_[image.height-1:-1:-1], - 1, image.width).reshape(pixel_length) - if color is not None: - color = color.reshape(pixel_length, 3) - normalized_depth = numpy.reshape(normalized_depth, pixel_length) - - # Search for pixels where the depth is greater than max_depth to - # delete them - max_depth_indexes = numpy.where(normalized_depth > max_depth) - normalized_depth = numpy.delete(normalized_depth, max_depth_indexes) - u_coord = numpy.delete(u_coord, max_depth_indexes) - v_coord = numpy.delete(v_coord, max_depth_indexes) - if color is not None: - color = numpy.delete(color, max_depth_indexes, axis=0) - - # pd2 = [u,v,1] - p2d = numpy.array([u_coord, v_coord, numpy.ones_like(u_coord)]) - - # P = [X,Y,Z] - p3d = numpy.dot(numpy.linalg.inv(k), p2d) - p3d *= normalized_depth * far - - # Formating the output to: - # [[X1,Y1,Z1,R1,G1,B1],[X2,Y2,Z2,R2,G2,B2], ... [Xn,Yn,Zn,Rn,Gn,Bn]] - if color is not None: - # numpy.concatenate((numpy.transpose(p3d), color), axis=1) - return sensor.PointCloud( - image.frame_number, - numpy.transpose(p3d), - color_array=color) - # [[X1,Y1,Z1],[X2,Y2,Z2], ... [Xn,Yn,Zn]] - return sensor.PointCloud(image.frame_number, numpy.transpose(p3d)) diff --git a/Deprecated/PythonClient/carla/planner/Town01.png b/Deprecated/PythonClient/carla/planner/Town01.png deleted file mode 100644 index b7cd5acf0..000000000 Binary files a/Deprecated/PythonClient/carla/planner/Town01.png and /dev/null differ diff --git a/Deprecated/PythonClient/carla/planner/Town01.txt b/Deprecated/PythonClient/carla/planner/Town01.txt deleted file mode 100644 index ffec1539e..000000000 --- a/Deprecated/PythonClient/carla/planner/Town01.txt +++ /dev/null @@ -1,49 +0,0 @@ -0.0,0.0,-0.3811000000 -0.000000,0.000000,0.0 -1.000000,1.000000,1.000000 --16.43022,-16.43022,0.000 -49, 41 -0,0 0,40 40 -0,40 0,0 40 -48,40 41,40 7 -41,40 48,40 7 -48,0 48,40 40 -48,40 48,0 40 -0,0 11,0 11 -11,0 0,0 11 -41,0 48,0 7 -48,0 41,0 7 -41,40 11,40 30 -11,40 41,40 30 -41,0 41,7 7 -41,7 41,0 7 -11,40 0,40 11 -0,40 11,40 11 -11,0 19,0 8 -19,0 11,0 8 -11,40 11,24 16 -11,24 11,40 16 -41,24 41,40 16 -41,40 41,24 16 -11,24 11,16 8 -11,16 11,24 8 -41,24 11,24 30 -11,24 41,24 30 -41,16 41,24 8 -41,24 41,16 8 -11,16 11,7 9 -11,7 11,16 9 -41,16 11,16 30 -11,16 41,16 30 -41,7 41,16 9 -41,16 41,7 9 -11,7 11,0 7 -11,0 11,7 7 -41,7 19,7 22 -19,7 41,7 22 -19,0 41,0 22 -41,0 19,0 22 -19,7 11,7 8 -11,7 19,7 8 -19,0 19,7 7 -19,7 19,0 7 diff --git a/Deprecated/PythonClient/carla/planner/Town01Central.png b/Deprecated/PythonClient/carla/planner/Town01Central.png deleted file mode 100644 index b2d769f94..000000000 Binary files a/Deprecated/PythonClient/carla/planner/Town01Central.png and /dev/null differ diff --git a/Deprecated/PythonClient/carla/planner/Town01Lanes.png b/Deprecated/PythonClient/carla/planner/Town01Lanes.png deleted file mode 100644 index 817035353..000000000 Binary files a/Deprecated/PythonClient/carla/planner/Town01Lanes.png and /dev/null differ diff --git a/Deprecated/PythonClient/carla/planner/Town02.png b/Deprecated/PythonClient/carla/planner/Town02.png deleted file mode 100644 index f173018ca..000000000 Binary files a/Deprecated/PythonClient/carla/planner/Town02.png and /dev/null differ diff --git a/Deprecated/PythonClient/carla/planner/Town02.txt b/Deprecated/PythonClient/carla/planner/Town02.txt deleted file mode 100644 index 44662a7f6..000000000 --- a/Deprecated/PythonClient/carla/planner/Town02.txt +++ /dev/null @@ -1,37 +0,0 @@ -5.4400,-107.48000,-0.22000000 -0.000000,0.000000,0.000000 -1.000000,1.000000,1.000000 --16.43022,-16.43022,0.000 -25, 25 -0,10 0,24 14 -0,24 0,10 14 -24,24 6,24 18 -6,24 24,24 18 -24,0 24,10 10 -24,10 24,0 10 -0,0 24,0 24 -24,0 0,0 24 -0,10 0,0 10 -0,0 0,10 10 -24,10 24,16 6 -24,16 24,10 6 -0,10 6,10 6 -6,10 0,10 6 -6,24 0,24 6 -0,24 6,24 6 -6,10 17,10 11 -17,10 6,10 11 -6,24 6,16 8 -6,16 6,24 8 -24,16 24,24 8 -24,24 24,16 8 -6,16 6,10 6 -6,10 6,16 6 -24,16 17,16 7 -17,16 24,16 7 -17,16 6,16 11 -6,16 17,16 11 -17,10 24,10 7 -24,10 17,10 7 -17,16 17,10 6 -17,10 17,16 6 diff --git a/Deprecated/PythonClient/carla/planner/Town02Big.png b/Deprecated/PythonClient/carla/planner/Town02Big.png deleted file mode 100644 index 6e6da4faa..000000000 Binary files a/Deprecated/PythonClient/carla/planner/Town02Big.png and /dev/null differ diff --git a/Deprecated/PythonClient/carla/planner/Town02Central.png b/Deprecated/PythonClient/carla/planner/Town02Central.png deleted file mode 100644 index 0c3a1ef10..000000000 Binary files a/Deprecated/PythonClient/carla/planner/Town02Central.png and /dev/null differ diff --git a/Deprecated/PythonClient/carla/planner/Town02Lanes.png b/Deprecated/PythonClient/carla/planner/Town02Lanes.png deleted file mode 100644 index 2f2b18da7..000000000 Binary files a/Deprecated/PythonClient/carla/planner/Town02Lanes.png and /dev/null differ diff --git a/Deprecated/PythonClient/carla/planner/__init__.py b/Deprecated/PythonClient/carla/planner/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/Deprecated/PythonClient/carla/planner/astar.py b/Deprecated/PythonClient/carla/planner/astar.py deleted file mode 100644 index 0d24a6090..000000000 --- a/Deprecated/PythonClient/carla/planner/astar.py +++ /dev/null @@ -1,156 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -import heapq - - -class Cell(object): - def __init__(self, x, y, reachable): - """Initialize new cell. - - @param reachable is cell reachable? not a wall? - @param x cell x coordinate - @param y cell y coordinate - @param g cost to move from the starting cell to this cell. - @param h estimation of the cost to move from this cell - to the ending cell. - @param f f = g + h - """ - self.reachable = reachable - self.x = x - self.y = y - self.parent = None - self.g = 0 - self.h = 0 - self.f = 0 - - def __lt__(self, other): - return self.g < other.g - - -class AStar(object): - def __init__(self): - # open list - self.opened = [] - heapq.heapify(self.opened) - # visited cells list - self.closed = set() - # grid cells - self.cells = [] - self.grid_height = None - self.grid_width = None - self.start = None - self.end = None - - def init_grid(self, width, height, walls, start, end): - """Prepare grid cells, walls. - - @param width grid's width. - @param height grid's height. - @param walls list of wall x,y tuples. - @param start grid starting point x,y tuple. - @param end grid ending point x,y tuple. - """ - self.grid_height = height - self.grid_width = width - for x in range(self.grid_width): - for y in range(self.grid_height): - if (x, y) in walls: - reachable = False - else: - reachable = True - self.cells.append(Cell(x, y, reachable)) - self.start = self.get_cell(*start) - self.end = self.get_cell(*end) - - def get_heuristic(self, cell): - """Compute the heuristic value H for a cell. - - Distance between this cell and the ending cell multiply by 10. - - @returns heuristic value H - """ - return 10 * (abs(cell.x - self.end.x) + abs(cell.y - self.end.y)) - - def get_cell(self, x, y): - """Returns a cell from the cells list. - - @param x cell x coordinate - @param y cell y coordinate - @returns cell - """ - return self.cells[x * self.grid_height + y] - - def get_adjacent_cells(self, cell): - """Returns adjacent cells to a cell. - - Clockwise starting from the one on the right. - - @param cell get adjacent cells for this cell - @returns adjacent cells list. - """ - cells = [] - if cell.x < self.grid_width - 1: - cells.append(self.get_cell(cell.x + 1, cell.y)) - if cell.y > 0: - cells.append(self.get_cell(cell.x, cell.y - 1)) - if cell.x > 0: - cells.append(self.get_cell(cell.x - 1, cell.y)) - if cell.y < self.grid_height - 1: - cells.append(self.get_cell(cell.x, cell.y + 1)) - return cells - - def get_path(self): - cell = self.end - path = [(cell.x, cell.y)] - while cell.parent is not self.start: - cell = cell.parent - path.append((cell.x, cell.y)) - - path.append((self.start.x, self.start.y)) - path.reverse() - return path - - def update_cell(self, adj, cell): - """Update adjacent cell. - - @param adj adjacent cell to current cell - @param cell current cell being processed - """ - adj.g = cell.g + 10 - adj.h = self.get_heuristic(adj) - adj.parent = cell - adj.f = adj.h + adj.g - - def solve(self): - """Solve maze, find path to ending cell. - - @returns path or None if not found. - """ - # add starting cell to open heap queue - heapq.heappush(self.opened, (self.start.f, self.start)) - while len(self.opened): - # pop cell from heap queue - _, cell = heapq.heappop(self.opened) - # add cell to closed list so we don't process it twice - self.closed.add(cell) - # if ending cell, return found path - if cell is self.end: - return self.get_path() - # get adjacent cells for cell - adj_cells = self.get_adjacent_cells(cell) - for adj_cell in adj_cells: - if adj_cell.reachable and adj_cell not in self.closed: - if (adj_cell.f, adj_cell) in self.opened: - # if adj cell in open list, check if current path is - # better than the one previously found - # for this adj cell. - if adj_cell.g > cell.g + 10: - self.update_cell(adj_cell, cell) - else: - self.update_cell(adj_cell, cell) - # add adj cell to open list - heapq.heappush(self.opened, (adj_cell.f, adj_cell)) diff --git a/Deprecated/PythonClient/carla/planner/city_track.py b/Deprecated/PythonClient/carla/planner/city_track.py deleted file mode 100644 index dbf872c5b..000000000 --- a/Deprecated/PythonClient/carla/planner/city_track.py +++ /dev/null @@ -1,131 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -from carla.planner.graph import sldist - -from carla.planner.astar import AStar -from carla.planner.map import CarlaMap - - -class CityTrack(object): - - def __init__(self, city_name): - self._map = CarlaMap(city_name) - - self._astar = AStar() - - # Refers to the start position of the previous route computation - self._previous_node = [] - - # The current computed route - self._route = None - - def project_node(self, position): - """ - Projecting the graph node into the city road - """ - - node = self._map.convert_to_node(position) - - # To change the orientation with respect to the map standards - - node = tuple([int(x) for x in node]) - - # Set to zero if it is less than zero. - - node = (max(0, node[0]), max(0, node[1])) - node = (min(self._map.get_graph_resolution()[0] - 1, node[0]), - min(self._map.get_graph_resolution()[1] - 1, node[1])) - - node = self._map.search_on_grid(node) - - return node - - def get_intersection_nodes(self): - return self._map.get_intersection_nodes() - - def get_pixel_density(self): - return self._map.get_map_resolution() - - def get_node_density(self): - return self._map.get_graph_resolution() - - def is_at_goal(self, source, target): - return source == target - - def is_at_new_node(self, current_node): - return current_node != self._previous_node - - def is_away_from_intersection(self, current_node): - return self._closest_intersection_position(current_node) > 1 - - def is_far_away_from_route_intersection(self, current_node): - # CHECK FOR THE EMPTY CASE - if self._route is None: - raise RuntimeError('Impossible to find route' - + ' Current planner is limited' - + ' Try to select start points away from intersections') - - return self._closest_intersection_route_position(current_node, - self._route) > 4 - - def compute_route(self, node_source, source_ori, node_target, target_ori): - - self._previous_node = node_source - - a_star = AStar() - a_star.init_grid(self._map.get_graph_resolution()[0], - self._map.get_graph_resolution()[1], - self._map.get_walls_directed(node_source, source_ori, - node_target, target_ori), node_source, - node_target) - - route = a_star.solve() - - # JuSt a Corner Case - # Clean this to avoid having to use this function - if route is None: - a_star = AStar() - a_star.init_grid(self._map.get_graph_resolution()[0], - self._map.get_graph_resolution()[1], self._map.get_walls(), - node_source, node_target) - - route = a_star.solve() - - self._route = route - - return route - - def get_distance_closest_node_route(self, pos, route): - distance = [] - - for node_iter in route: - - if node_iter in self._map.get_intersection_nodes(): - distance.append(sldist(node_iter, pos)) - - if not distance: - return sldist(route[-1], pos) - return sorted(distance)[0] - - - def _closest_intersection_position(self, current_node): - - distance_vector = [] - for node_iterator in self._map.get_intersection_nodes(): - distance_vector.append(sldist(node_iterator, current_node)) - - return sorted(distance_vector)[0] - - - def _closest_intersection_route_position(self, current_node, route): - - distance_vector = [] - for _ in route: - for node_iterator in self._map.get_intersection_nodes(): - distance_vector.append(sldist(node_iterator, current_node)) - - return sorted(distance_vector)[0] diff --git a/Deprecated/PythonClient/carla/planner/converter.py b/Deprecated/PythonClient/carla/planner/converter.py deleted file mode 100644 index f9ffff982..000000000 --- a/Deprecated/PythonClient/carla/planner/converter.py +++ /dev/null @@ -1,169 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -import math -import numpy as np - -from carla.planner.graph import string_to_floats - -# Constant definition enumeration - -PIXEL = 0 -WORLD = 1 -NODE = 2 - - -class Converter(object): - - def __init__(self, city_file, pixel_density, node_density): - - self._node_density = node_density - self._pixel_density = pixel_density - with open(city_file, 'r') as f: - # The offset of the world from the zero coordinates ( The - # coordinate we consider zero) - self._worldoffset = string_to_floats(f.readline()) - - angles = string_to_floats(f.readline()) - - # If there is an rotation between the world and map coordinates. - self._worldrotation = np.array([ - [math.cos(math.radians(angles[2])), -math.sin(math.radians(angles[2])), 0.0], - [math.sin(math.radians(angles[2])), math.cos(math.radians(angles[2])), 0.0], - [0.0, 0.0, 1.0]]) - - # Ignore for now, these are offsets for map coordinates and scale - # (not used). - _ = f.readline() - - # The offset of the map zero coordinate. - self._mapoffset = string_to_floats(f.readline()) - - def convert_to_node(self, input_data): - """ - Receives a data type (Can Be Pixel or World ) - :param input_data: position in some coordinate - :return: A vector representing a node - """ - - input_type = self._check_input_type(input_data) - if input_type == PIXEL: - return self._pixel_to_node(input_data) - elif input_type == WORLD: - return self._world_to_node(input_data) - else: - raise ValueError('Invalid node to be converted') - - def convert_to_pixel(self, input_data): - - """ - Receives a data type (Can Be Node or World ) - :param input_data: position in some coordinate - :return: A vector with pixel coordinates - """ - - input_type = self._check_input_type(input_data) - - if input_type == NODE: - return self._node_to_pixel(input_data) - elif input_type == WORLD: - return self._world_to_pixel(input_data) - else: - raise ValueError('Invalid node to be converted') - - def convert_to_world(self, input_data): - - """ - Receives a data type (Can Be Pixel or Node ) - :param input_data: position in some coordinate - :return: vector with world coordinates - """ - - input_type = self._check_input_type(input_data) - if input_type == NODE: - return self._node_to_world(input_data) - elif input_type == PIXEL: - return self._pixel_to_world(input_data) - else: - raise ValueError('Invalid node to be converted') - - def get_map_resolution(self): - return self._pixel_density - - def _node_to_pixel(self, node): - """ - Conversion from node format (graph) to pixel (image) - :param node: - :return: pixel - """ - pixel = [((node[0] + 2) * self._node_density) - , ((node[1] + 2) * self._node_density)] - return pixel - - def _pixel_to_node(self, pixel): - """ - Conversion from pixel format (image) to node (graph) - :param node: - :return: pixel - """ - node = [int(((pixel[0]) / self._node_density) - 2) - , int(((pixel[1]) / self._node_density) - 2)] - - return tuple(node) - - def _pixel_to_world(self, pixel): - """ - Conversion from pixel format (image) to world (3D) - :param pixel: - :return: world - """ - - relative_location = [pixel[0] * self._pixel_density, - pixel[1] * self._pixel_density] - - world = [ - relative_location[0] + self._mapoffset[0] - self._worldoffset[0], - relative_location[1] + self._mapoffset[1] - self._worldoffset[1], - self._mapoffset[2] - self._worldoffset[2] - ] - - return world - - def _world_to_pixel(self, world): - """ - Conversion from world format (3D) to pixel - :param world: - :return: pixel - """ - - rotation = np.array([world[0], world[1], world[2]]) - rotation = rotation.dot(self._worldrotation) - - relative_location = [rotation[0] + self._worldoffset[0] - self._mapoffset[0], - rotation[1] + self._worldoffset[1] - self._mapoffset[1], - rotation[2] + self._worldoffset[2] - self._mapoffset[2]] - - - - pixel = [math.floor(relative_location[0] / float(self._pixel_density)), - math.floor(relative_location[1] / float(self._pixel_density))] - - return pixel - - def _world_to_node(self, world): - return self._pixel_to_node(self._world_to_pixel(world)) - - def _node_to_world(self, node): - - return self._pixel_to_world(self._node_to_pixel(node)) - - def _check_input_type(self, input_data): - if len(input_data) > 2: - return WORLD - elif type(input_data[0]) is int: - return NODE - else: - return PIXEL diff --git a/Deprecated/PythonClient/carla/planner/graph.py b/Deprecated/PythonClient/carla/planner/graph.py deleted file mode 100644 index 23f32d381..000000000 --- a/Deprecated/PythonClient/carla/planner/graph.py +++ /dev/null @@ -1,141 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -import math -import numpy as np - - -def string_to_node(string): - vec = string.split(',') - return (int(vec[0]), int(vec[1])) - - -def string_to_floats(string): - vec = string.split(',') - return (float(vec[0]), float(vec[1]), float(vec[2])) - - -def sldist(c1, c2): - return math.sqrt((c2[0] - c1[0]) ** 2 + (c2[1] - c1[1]) ** 2) - - -def sldist3(c1, c2): - return math.sqrt((c2[0] - c1[0]) ** 2 + (c2[1] - c1[1]) - ** 2 + (c2[2] - c1[2]) ** 2) - - -class Graph(object): - """ - A simple directed, weighted graph - """ - - def __init__(self, graph_file=None, node_density=50): - - self._nodes = set() - self._angles = {} - self._edges = {} - self._distances = {} - self._node_density = node_density - - if graph_file is not None: - with open(graph_file, 'r') as f: - # Skipe the first four lines that - lines_after_4 = f.readlines()[4:] - - # the graph resolution. - linegraphres = lines_after_4[0] - self._resolution = string_to_node(linegraphres) - for line in lines_after_4[1:]: - - from_node, to_node, d = line.split() - from_node = string_to_node(from_node) - to_node = string_to_node(to_node) - - if from_node not in self._nodes: - self.add_node(from_node) - if to_node not in self._nodes: - self.add_node(to_node) - - self._edges.setdefault(from_node, []) - self._edges[from_node].append(to_node) - self._distances[(from_node, to_node)] = float(d) - - def add_node(self, value): - self._nodes.add(value) - - def make_orientations(self, node, heading): - - import collections - distance_dic = {} - for node_iter in self._nodes: - if node_iter != node: - distance_dic[sldist(node, node_iter)] = node_iter - - distance_dic = collections.OrderedDict( - sorted(distance_dic.items())) - - self._angles[node] = heading - for _, v in distance_dic.items(): - start_to_goal = np.array([node[0] - v[0], node[1] - v[1]]) - - print(start_to_goal) - - self._angles[v] = start_to_goal / np.linalg.norm(start_to_goal) - - def add_edge(self, from_node, to_node, distance): - self._add_edge(from_node, to_node, distance) - - def _add_edge(self, from_node, to_node, distance): - self._edges.setdefault(from_node, []) - self._edges[from_node].append(to_node) - self._distances[(from_node, to_node)] = distance - - def get_resolution(self): - return self._resolution - def get_edges(self): - return self._edges - - def intersection_nodes(self): - - intersect_nodes = [] - for node in self._nodes: - if len(self._edges[node]) > 2: - intersect_nodes.append(node) - - return intersect_nodes - - # This contains also the non-intersection turns... - - def turn_nodes(self): - - return self._nodes - - def plot_ori(self, c): - from matplotlib import collections as mc - - import matplotlib.pyplot as plt - line_len = 1 - - lines = [[(p[0], p[1]), (p[0] + line_len * self._angles[p][0], - p[1] + line_len * self._angles[p][1])] for p in self._nodes] - lc = mc.LineCollection(lines, linewidth=2, color='green') - _, ax = plt.subplots() - ax.add_collection(lc) - - ax.autoscale() - ax.margins(0.1) - - xs = [p[0] for p in self._nodes] - ys = [p[1] for p in self._nodes] - - plt.scatter(xs, ys, color=c) - - def plot(self, c): - import matplotlib.pyplot as plt - xs = [p[0] for p in self._nodes] - ys = [p[1] for p in self._nodes] - - plt.scatter(xs, ys, color=c) diff --git a/Deprecated/PythonClient/carla/planner/grid.py b/Deprecated/PythonClient/carla/planner/grid.py deleted file mode 100644 index fe14115a6..000000000 --- a/Deprecated/PythonClient/carla/planner/grid.py +++ /dev/null @@ -1,135 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -import copy -import numpy as np - - -def angle_between(v1, v2): - return np.arccos(np.dot(v1, v2) / np.linalg.norm(v1) / np.linalg.norm(v2)) - - -class Grid(object): - - def __init__(self, graph): - - self._graph = graph - self._structure = self._make_structure() - self._walls = self._make_walls() - - def search_on_grid(self, x, y): - visit = [[0, 1], [0, -1], [1, 0], [1, 1], - [1, -1], [-1, 0], [-1, 1], [-1, -1]] - c_x, c_y = x, y - scale = 1 - while self._structure[c_x, c_y] != 0: - for offset in visit: - c_x, c_y = x + offset[0] * scale, y + offset[1] * scale - - if c_x >= 0 and c_x < self._graph.get_resolution()[ - 0] and c_y >= 0 and c_y < self._graph.get_resolution()[1]: - if self._structure[c_x, c_y] == 0: - break - else: - c_x, c_y = x, y - scale += 1 - - return c_x, c_y - def get_walls(self): - return self._walls - - def get_wall_source(self, pos, pos_ori, target): - - free_nodes = self._get_adjacent_free_nodes(pos) - # print self._walls - final_walls = copy.copy(self._walls) - # print final_walls - heading_start = np.array([pos_ori[0], pos_ori[1]]) - for adj in free_nodes: - - start_to_goal = np.array([adj[0] - pos[0], adj[1] - pos[1]]) - angle = angle_between(heading_start, start_to_goal) - if (angle > 1.6 and adj != target): - final_walls.add((adj[0], adj[1])) - - return final_walls - - def get_wall_target(self, pos, pos_ori, source): - - free_nodes = self._get_adjacent_free_nodes(pos) - final_walls = copy.copy(self._walls) - heading_start = np.array([pos_ori[0], pos_ori[1]]) - for adj in free_nodes: - - start_to_goal = np.array([adj[0] - pos[0], adj[1] - pos[1]]) - angle = angle_between(heading_start, start_to_goal) - - if (angle < 1.0 and adj != source): - final_walls.add((adj[0], adj[1])) - - return final_walls - - def _draw_line(self, grid, xi, yi, xf, yf): - - if xf < xi: - aux = xi - xi = xf - xf = aux - - if yf < yi: - aux = yi - yi = yf - yf = aux - - for i in range(xi, xf + 1): - - for j in range(yi, yf + 1): - grid[i, j] = 0.0 - - return grid - - def _make_structure(self): - structure = np.ones( - (self._graph.get_resolution()[0], - self._graph.get_resolution()[1])) - - for key, connections in self._graph.get_edges().items(): - - # draw a line - for con in connections: - # print key[0],key[1],con[0],con[1] - structure = self._draw_line( - structure, key[0], key[1], con[0], con[1]) - # print grid - return structure - - def _make_walls(self): - walls = set() - - for i in range(self._structure.shape[0]): - - for j in range(self._structure.shape[1]): - if self._structure[i, j] == 1.0: - walls.add((i, j)) - - return walls - - def _get_adjacent_free_nodes(self, pos): - """ Eight nodes in total """ - visit = [[0, 1], [0, -1], [1, 0], [1, 1], - [1, -1], [-1, 0], [-1, 1], [-1, -1]] - - adjacent = set() - for offset in visit: - node = (pos[0] + offset[0], pos[1] + offset[1]) - - if (node[0] >= 0 and node[0] < self._graph.get_resolution()[0] - and node[1] >= 0 and node[1] < self._graph.get_resolution()[1]): - - if self._structure[node[0], node[1]] == 0.0: - adjacent.add(node) - - return adjacent diff --git a/Deprecated/PythonClient/carla/planner/map.py b/Deprecated/PythonClient/carla/planner/map.py deleted file mode 100644 index 59fb06f87..000000000 --- a/Deprecated/PythonClient/carla/planner/map.py +++ /dev/null @@ -1,154 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""Class used for operating the city map.""" - -import math -import os - -try: - import numpy as np -except ImportError: - raise RuntimeError('cannot import numpy, make sure numpy package is installed') - -try: - from PIL import Image -except ImportError: - raise RuntimeError('cannot import PIL, make sure pillow package is installed') - -from carla.planner.graph import Graph -from carla.planner.graph import sldist -from carla.planner.grid import Grid -from carla.planner.converter import Converter - - -def color_to_angle(color): - return (float(color) / 255.0) * 2 * math.pi - - -class CarlaMap(object): - - def __init__(self, city, pixel_density=0.1643, node_density=50): - dir_path = os.path.dirname(__file__) - city_file = os.path.join(dir_path, city + '.txt') - - city_map_file = os.path.join(dir_path, city + '.png') - city_map_file_lanes = os.path.join(dir_path, city + 'Lanes.png') - city_map_file_center = os.path.join(dir_path, city + 'Central.png') - - # The built graph. This is the exact same graph that unreal builds. This - # is a generic structure used for many cases - self._graph = Graph(city_file, node_density) - - self._pixel_density = pixel_density - self._grid = Grid(self._graph) - # The number of game units per pixel. For now this is fixed. - - self._converter = Converter(city_file, pixel_density, node_density) - - # Load the lanes image - self.map_image_lanes = Image.open(city_map_file_lanes) - self.map_image_lanes.load() - self.map_image_lanes = np.asarray(self.map_image_lanes, dtype="int32") - # Load the image - self.map_image = Image.open(city_map_file) - self.map_image.load() - self.map_image = np.asarray(self.map_image, dtype="int32") - - # Load the lanes image - self.map_image_center = Image.open(city_map_file_center) - self.map_image_center.load() - self.map_image_center = np.asarray(self.map_image_center, dtype="int32") - - def get_graph_resolution(self): - return self._graph.get_resolution() - - def get_map_resolution(self): - return self._converter.get_map_resolution() - - def get_map(self, height=None): - if height is not None: - img = Image.fromarray(self.map_image.astype(np.uint8)) - - aspect_ratio = height / float(self.map_image.shape[0]) - - img = img.resize((int(aspect_ratio * self.map_image.shape[1]), height), Image.ANTIALIAS) - img.load() - return np.asarray(img, dtype="int32") - return np.fliplr(self.map_image) - - def get_map_lanes(self, size=None): - if size is not None: - img = Image.fromarray(self.map_image_lanes.astype(np.uint8)) - img = img.resize((size[1], size[0]), Image.ANTIALIAS) - img.load() - return np.fliplr(np.asarray(img, dtype="int32")) - return np.fliplr(self.map_image_lanes) - - def get_lane_orientation(self, world): - """Get the lane orientation of a certain world position.""" - pixel = self.convert_to_pixel(world) - - ori = self.map_image_lanes[int(pixel[1]), int(pixel[0]), 2] - ori = color_to_angle(ori) - - return (-math.cos(ori), -math.sin(ori)) - - def convert_to_node(self, input_data): - """ - Receives a data type (Can Be Pixel or World ) - :param input_data: position in some coordinate - :return: A node object - """ - return self._converter.convert_to_node(input_data) - - def convert_to_pixel(self, input_data): - """ - Receives a data type (Can Be Node or World ) - :param input_data: position in some coordinate - :return: A node object - """ - return self._converter.convert_to_pixel(input_data) - - def convert_to_world(self, input_data): - """ - Receives a data type (Can Be Pixel or Node ) - :param input_data: position in some coordinate - :return: A node object - """ - return self._converter.convert_to_world(input_data) - - def get_walls_directed(self, node_source, source_ori, node_target, target_ori): - """ - This is the most hacky function. Instead of planning on two ways, - we basically use a one way road and interrupt the other road by adding - an artificial wall. - - """ - - final_walls = self._grid.get_wall_source(node_source, source_ori, node_target) - - final_walls = final_walls.union(self._grid.get_wall_target( - node_target, target_ori, node_source)) - return final_walls - - def get_walls(self): - - return self._grid.get_walls() - - def get_distance_closest_node(self, pos): - - distance = [] - for node_iter in self._graph.intersection_nodes(): - distance.append(sldist(node_iter, pos)) - - return sorted(distance)[0] - - def get_intersection_nodes(self): - return self._graph.intersection_nodes() - - def search_on_grid(self,node): - return self._grid.search_on_grid(node[0], node[1]) diff --git a/Deprecated/PythonClient/carla/planner/planner.py b/Deprecated/PythonClient/carla/planner/planner.py deleted file mode 100644 index 51eadc854..000000000 --- a/Deprecated/PythonClient/carla/planner/planner.py +++ /dev/null @@ -1,175 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -import collections -import math - -import numpy as np - -from . import city_track - - -def compare(x, y): - return collections.Counter(x) == collections.Counter(y) - - - -# Constants Used for the high level commands - - -REACH_GOAL = 0.0 -GO_STRAIGHT = 5.0 -TURN_RIGHT = 4.0 -TURN_LEFT = 3.0 -LANE_FOLLOW = 2.0 - - -# Auxiliary algebra function -def angle_between(v1, v2): - return np.arccos(np.dot(v1, v2) / np.linalg.norm(v1) / np.linalg.norm(v2)) - - -def sldist(c1, c2): return math.sqrt((c2[0] - c1[0]) ** 2 + (c2[1] - c1[1]) ** 2) - - -def signal(v1, v2): - return np.cross(v1, v2) / np.linalg.norm(v1) / np.linalg.norm(v2) - - -class Planner(object): - - def __init__(self, city_name): - - self._city_track = city_track.CityTrack(city_name) - - self._commands = [] - - def get_next_command(self, source, source_ori, target, target_ori): - """ - Computes the full plan and returns the next command, - Args - source: source position - source_ori: source orientation - target: target position - target_ori: target orientation - Returns - a command ( Straight,Lane Follow, Left or Right) - """ - - track_source = self._city_track.project_node(source) - track_target = self._city_track.project_node(target) - - # reach the goal - - if self._city_track.is_at_goal(track_source, track_target): - return REACH_GOAL - - if (self._city_track.is_at_new_node(track_source) - and self._city_track.is_away_from_intersection(track_source)): - - route = self._city_track.compute_route(track_source, source_ori, - track_target, target_ori) - if route is None: - raise RuntimeError('Impossible to find route') - - self._commands = self._route_to_commands(route) - - if self._city_track.is_far_away_from_route_intersection( - track_source): - return LANE_FOLLOW - else: - if self._commands: - return self._commands[0] - else: - return LANE_FOLLOW - else: - - if self._city_track.is_far_away_from_route_intersection( - track_source): - return LANE_FOLLOW - - # If there is computed commands - if self._commands: - return self._commands[0] - else: - return LANE_FOLLOW - - def get_shortest_path_distance( - self, - source, - source_ori, - target, - target_ori): - - distance = 0 - track_source = self._city_track.project_node(source) - track_target = self._city_track.project_node(target) - - current_pos = track_source - - route = self._city_track.compute_route(track_source, source_ori, - track_target, target_ori) - # No Route, distance is zero - if route is None: - return 0.0 - - for node_iter in route: - distance += sldist(node_iter, current_pos) - current_pos = node_iter - - # We multiply by these values to convert distance to world coordinates - return distance * self._city_track.get_pixel_density() \ - * self._city_track.get_node_density() - - def is_there_posible_route(self, source, source_ori, target, target_ori): - - track_source = self._city_track.project_node(source) - track_target = self._city_track.project_node(target) - - return not self._city_track.compute_route( - track_source, source_ori, track_target, target_ori) is None - - def test_position(self, source): - - node_source = self._city_track.project_node(source) - - return self._city_track.is_away_from_intersection(node_source) - - def _route_to_commands(self, route): - - """ - from the shortest path graph, transform it into a list of commands - - :param route: the sub graph containing the shortest path - :return: list of commands encoded from 0-5 - """ - - commands_list = [] - - for i in range(0, len(route)): - if route[i] not in self._city_track.get_intersection_nodes(): - continue - - current = route[i] - past = route[i - 1] - future = route[i + 1] - - past_to_current = np.array( - [current[0] - past[0], current[1] - past[1]]) - current_to_future = np.array( - [future[0] - current[0], future[1] - current[1]]) - angle = signal(current_to_future, past_to_current) - - if angle < -0.1: - command = TURN_RIGHT - elif angle > 0.1: - command = TURN_LEFT - else: - command = GO_STRAIGHT - - commands_list.append(command) - - return commands_list diff --git a/Deprecated/PythonClient/carla/sensor.py b/Deprecated/PythonClient/carla/sensor.py deleted file mode 100644 index bc5977303..000000000 --- a/Deprecated/PythonClient/carla/sensor.py +++ /dev/null @@ -1,334 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""CARLA sensors.""" - - -import os - -from collections import namedtuple - -try: - import numpy -except ImportError: - raise RuntimeError('cannot import numpy, make sure numpy package is installed.') - -from .transform import Transform, Translation, Rotation, Scale - - -# ============================================================================== -# -- Helpers ------------------------------------------------------------------- -# ============================================================================== - - -Color = namedtuple('Color', 'r g b') -Color.__new__.__defaults__ = (0, 0, 0) - - -Point = namedtuple('Point', 'x y z color') -Point.__new__.__defaults__ = (0.0, 0.0, 0.0, None) - - -def _append_extension(filename, ext): - return filename if filename.lower().endswith(ext.lower()) else filename + ext - - -# ============================================================================== -# -- Sensor -------------------------------------------------------------------- -# ============================================================================== - - -class Sensor(object): - """ - Base class for sensor descriptions. Used to add sensors to CarlaSettings. - """ - - def __init__(self, name, sensor_type): - self.SensorName = name - self.SensorType = sensor_type - self.PositionX = 0.2 - self.PositionY = 0.0 - self.PositionZ = 1.3 - self.RotationPitch = 0.0 - self.RotationRoll = 0.0 - self.RotationYaw = 0.0 - - def set(self, **kwargs): - for key, value in kwargs.items(): - if not hasattr(self, key): - raise ValueError('sensor.Sensor: no key named %r' % key) - setattr(self, key, value) - - def set_position(self, x, y, z): - self.PositionX = x - self.PositionY = y - self.PositionZ = z - - def set_rotation(self, pitch, yaw, roll): - self.RotationPitch = pitch - self.RotationYaw = yaw - self.RotationRoll = roll - - def get_transform(self): - ''' - Returns the camera to [whatever the camera is attached to] - transformation. - ''' - return Transform( - Translation(self.PositionX, self.PositionY, self.PositionZ), - Rotation(self.RotationPitch, self.RotationYaw, self.RotationRoll)) - - def get_unreal_transform(self): - ''' - Returns the camera to [whatever the camera is attached to] - transformation with the Unreal necessary corrections applied. - - @todo Do we need to expose this? - ''' - to_unreal_transform = Transform(Rotation(roll=-90, yaw=90), Scale(x=-1)) - return self.get_transform() * to_unreal_transform - - -class Camera(Sensor): - """ - Camera description. This class can be added to a CarlaSettings object to add - a camera to the player vehicle. - """ - - def __init__(self, name, **kwargs): - super(Camera, self).__init__(name, sensor_type="CAMERA") - self.PostProcessing = 'SceneFinal' - self.ImageSizeX = 720 - self.ImageSizeY = 512 - self.FOV = 90.0 - self.set(**kwargs) - - def set_image_size(self, pixels_x, pixels_y): - '''Sets the image size in pixels''' - self.ImageSizeX = pixels_x - self.ImageSizeY = pixels_y - - -class Lidar(Sensor): - """ - Lidar description. This class can be added to a CarlaSettings object to add - a Lidar to the player vehicle. - """ - - def __init__(self, name, **kwargs): - super(Lidar, self).__init__(name, sensor_type="LIDAR_RAY_CAST") - self.Channels = 32 - self.Range = 50.0 - self.PointsPerSecond = 56000 - self.RotationFrequency = 10.0 - self.UpperFovLimit = 10.0 - self.LowerFovLimit = -30.0 - self.ShowDebugPoints = False - self.set(**kwargs) - - -# ============================================================================== -# -- SensorData ---------------------------------------------------------------- -# ============================================================================== - - -class SensorData(object): - """Base class for sensor data returned from the server.""" - def __init__(self, frame_number): - self.frame_number = frame_number - - -class Image(SensorData): - """Data generated by a Camera.""" - - def __init__(self, frame_number, width, height, image_type, fov, raw_data): - super(Image, self).__init__(frame_number=frame_number) - assert len(raw_data) == 4 * width * height - self.width = width - self.height = height - self.type = image_type - self.fov = fov - self.raw_data = raw_data - self._converted_data = None - - @property - def data(self): - """ - Lazy initialization for data property, stores converted data in its - default format. - """ - if self._converted_data is None: - from . import image_converter - - if self.type == 'Depth': - self._converted_data = image_converter.depth_to_array(self) - elif self.type == 'SemanticSegmentation': - self._converted_data = image_converter.labels_to_array(self) - else: - self._converted_data = image_converter.to_rgb_array(self) - return self._converted_data - - def save_to_disk(self, filename): - """Save this image to disk (requires PIL installed).""" - filename = _append_extension(filename, '.png') - - try: - from PIL import Image as PImage - except ImportError: - raise RuntimeError( - 'cannot import PIL, make sure pillow package is installed') - - image = PImage.frombytes( - mode='RGBA', - size=(self.width, self.height), - data=self.raw_data, - decoder_name='raw') - color = image.split() - image = PImage.merge("RGB", color[2::-1]) - - folder = os.path.dirname(filename) - if not os.path.isdir(folder): - os.makedirs(folder) - image.save(filename) - - -class PointCloud(SensorData): - """A list of points.""" - - def __init__(self, frame_number, array, color_array=None): - super(PointCloud, self).__init__(frame_number=frame_number) - self._array = array - self._color_array = color_array - self._has_colors = color_array is not None - - @property - def array(self): - """The numpy array holding the point-cloud. - - 3D points format for n elements: - [ [X0,Y0,Z0], - ..., - [Xn,Yn,Zn] ] - """ - return self._array - - @property - def color_array(self): - """The numpy array holding the colors corresponding to each point. - It is None if there are no colors. - - Colors format for n elements: - [ [R0,G0,B0], - ..., - [Rn,Gn,Bn] ] - """ - return self._color_array - - def has_colors(self): - """Return whether the points have color.""" - return self._has_colors - - def apply_transform(self, transformation): - """Modify the PointCloud instance transforming its points""" - self._array = transformation.transform_points(self._array) - - def save_to_disk(self, filename): - """Save this point-cloud to disk as PLY format.""" - filename = _append_extension(filename, '.ply') - - def construct_ply_header(): - """Generates a PLY header given a total number of 3D points and - coloring property if specified - """ - points = len(self) # Total point number - header = ['ply', - 'format ascii 1.0', - 'element vertex {}', - 'property float32 x', - 'property float32 y', - 'property float32 z', - 'property uchar diffuse_red', - 'property uchar diffuse_green', - 'property uchar diffuse_blue', - 'end_header'] - if not self._has_colors: - return '\n'.join(header[0:6] + [header[-1]]).format(points) - return '\n'.join(header).format(points) - - if not self._has_colors: - ply = '\n'.join(['{:.2f} {:.2f} {:.2f}'.format( - *p) for p in self._array.tolist()]) - else: - points_3d = numpy.concatenate( - (self._array, self._color_array), axis=1) - ply = '\n'.join(['{:.2f} {:.2f} {:.2f} {:.0f} {:.0f} {:.0f}' - .format(*p) for p in points_3d.tolist()]) - - # Create folder to save if does not exist. - folder = os.path.dirname(filename) - if not os.path.isdir(folder): - os.makedirs(folder) - - # Open the file and save with the specific PLY format. - with open(filename, 'w+') as ply_file: - ply_file.write('\n'.join([construct_ply_header(), ply, ''])) - - def __len__(self): - return len(self.array) - - def __getitem__(self, key): - color = None if self._color_array is None else Color( - *self._color_array[key]) - return Point(*self._array[key], color=color) - - def __iter__(self): - class PointIterator(object): - """Iterator class for PointCloud""" - - def __init__(self, point_cloud): - self.point_cloud = point_cloud - self.index = -1 - - def __next__(self): - self.index += 1 - if self.index >= len(self.point_cloud): - raise StopIteration - return self.point_cloud[self.index] - - def next(self): - return self.__next__() - - return PointIterator(self) - - def __str__(self): - return str(self.array) - - -class LidarMeasurement(SensorData): - """Data generated by a Lidar.""" - - def __init__(self, frame_number, horizontal_angle, channels, point_count_by_channel, point_cloud): - super(LidarMeasurement, self).__init__(frame_number=frame_number) - assert numpy.sum(point_count_by_channel) == len(point_cloud.array) - self.horizontal_angle = horizontal_angle - self.channels = channels - self.point_count_by_channel = point_count_by_channel - self.point_cloud = point_cloud - - @property - def data(self): - """The numpy array holding the point-cloud. - - 3D points format for n elements: - [ [X0,Y0,Z0], - ..., - [Xn,Yn,Zn] ] - """ - return self.point_cloud.array - - def save_to_disk(self, filename): - """Save point-cloud to disk as PLY format.""" - self.point_cloud.save_to_disk(filename) diff --git a/Deprecated/PythonClient/carla/settings.py b/Deprecated/PythonClient/carla/settings.py deleted file mode 100644 index 44ba2b164..000000000 --- a/Deprecated/PythonClient/carla/settings.py +++ /dev/null @@ -1,123 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""CARLA Settings""" - -import io -import random -import sys - - -if sys.version_info >= (3, 0): - - from configparser import ConfigParser - -else: - - from ConfigParser import RawConfigParser as ConfigParser - - -from . import sensor as carla_sensor - - -MAX_NUMBER_OF_WEATHER_IDS = 14 - - -class CarlaSettings(object): - """ - The CarlaSettings object controls the settings of an episode. The __str__ - method retrieves an str with a CarlaSettings.ini file contents. - """ - - def __init__(self, **kwargs): - # [CARLA/Server] - self.SynchronousMode = True - self.SendNonPlayerAgentsInfo = False - self.DisableRendering = False - # [CARLA/QualitySettings] - self.QualityLevel = 'Epic' - # [CARLA/LevelSettings] - self.PlayerVehicle = None - self.NumberOfVehicles = 20 - self.NumberOfPedestrians = 30 - self.WeatherId = 1 - self.SeedVehicles = None - self.SeedPedestrians = None - self.DisableTwoWheeledVehicles = False - self.set(**kwargs) - self._sensors = [] - - def set(self, **kwargs): - for key, value in kwargs.items(): - if not hasattr(self, key): - raise ValueError('CarlaSettings: no key named %r' % key) - setattr(self, key, value) - - def randomize_seeds(self): - """ - Randomize the seeds of the new episode's pseudo-random number - generators. - """ - self.SeedVehicles = random.getrandbits(16) - self.SeedPedestrians = random.getrandbits(16) - - def randomize_weather(self): - """Randomized the WeatherId.""" - self.WeatherId = random.randint(0, MAX_NUMBER_OF_WEATHER_IDS) - - def add_sensor(self, sensor): - """Add a sensor to the player vehicle (see sensor.py).""" - if not isinstance(sensor, carla_sensor.Sensor): - raise ValueError('Sensor not supported') - self._sensors.append(sensor) - - def __str__(self): - """Converts this object to an INI formatted string.""" - ini = ConfigParser() - ini.optionxform = str - S_SERVER = 'CARLA/Server' - S_QUALITY = 'CARLA/QualitySettings' - S_LEVEL = 'CARLA/LevelSettings' - S_SENSOR = 'CARLA/Sensor' - - def get_attribs(obj): - return [a for a in dir(obj) if not a.startswith('_') and not callable(getattr(obj, a))] - - def add_section(section, obj, keys): - for key in keys: - if hasattr(obj, key) and getattr(obj, key) is not None: - if not ini.has_section(section): - ini.add_section(section) - ini.set(section, key, str(getattr(obj, key))) - - add_section(S_SERVER, self, [ - 'SynchronousMode', - 'SendNonPlayerAgentsInfo', - 'DisableRendering']) - add_section(S_QUALITY, self, [ - 'QualityLevel']) - add_section(S_LEVEL, self, [ - 'NumberOfVehicles', - 'NumberOfPedestrians', - 'WeatherId', - 'SeedVehicles', - 'SeedPedestrians', - 'DisableTwoWheeledVehicles']) - - ini.add_section(S_SENSOR) - ini.set(S_SENSOR, 'Sensors', ','.join(s.SensorName for s in self._sensors)) - - for sensor_def in self._sensors: - section = S_SENSOR + '/' + sensor_def.SensorName - add_section(section, sensor_def, get_attribs(sensor_def)) - - if sys.version_info >= (3, 0): - text = io.StringIO() - else: - text = io.BytesIO() - - ini.write(text) - return text.getvalue().replace(' = ', '=') diff --git a/Deprecated/PythonClient/carla/tcp.py b/Deprecated/PythonClient/carla/tcp.py deleted file mode 100644 index d6de55972..000000000 --- a/Deprecated/PythonClient/carla/tcp.py +++ /dev/null @@ -1,97 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""Basic TCP client.""" - -import logging -import socket -import struct -import time - -class TCPConnectionError(Exception): - pass - - -class TCPClient(object): - """ - Basic networking client for TCP connections. Errors occurred during - networking operations are raised as TCPConnectionError. - - Received messages are expected to be prepended by a int32 defining the - message size. Messages are sent following this convention. - """ - - def __init__(self, host, port, timeout): - self._host = host - self._port = port - self._timeout = timeout - self._socket = None - self._logprefix = '(%s:%s) ' % (self._host, self._port) - - def connect(self, connection_attempts=10): - """Try to establish a connection to the given host:port.""" - connection_attempts = max(1, connection_attempts) - error = None - for attempt in range(1, connection_attempts + 1): - try: - self._socket = socket.create_connection(address=(self._host, self._port), timeout=self._timeout) - self._socket.settimeout(self._timeout) - logging.debug('%sconnected', self._logprefix) - return - except socket.error as exception: - error = exception - logging.debug('%sconnection attempt %d: %s', self._logprefix, attempt, error) - time.sleep(1) - self._reraise_exception_as_tcp_error('failed to connect', error) - - def disconnect(self): - """Disconnect any active connection.""" - if self._socket is not None: - logging.debug('%sdisconnecting', self._logprefix) - self._socket.close() - self._socket = None - - def connected(self): - """Return whether there is an active connection.""" - return self._socket is not None - - def write(self, message): - """Send message to the server.""" - if self._socket is None: - raise TCPConnectionError(self._logprefix + 'not connected') - header = struct.pack(' 0: - try: - data = self._socket.recv(length) - except socket.error as exception: - self._reraise_exception_as_tcp_error('failed to read data', exception) - if not data: - raise TCPConnectionError(self._logprefix + 'connection closed') - buf += data - length -= len(data) - return buf - - def _reraise_exception_as_tcp_error(self, message, exception): - raise TCPConnectionError('%s%s: %s' % (self._logprefix, message, exception)) diff --git a/Deprecated/PythonClient/carla/transform.py b/Deprecated/PythonClient/carla/transform.py deleted file mode 100644 index 0ae6cbdd8..000000000 --- a/Deprecated/PythonClient/carla/transform.py +++ /dev/null @@ -1,137 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -import math - -from collections import namedtuple - -try: - import numpy -except ImportError: - raise RuntimeError( - 'cannot import numpy, make sure numpy package is installed.') - -try: - from . import carla_server_pb2 as carla_protocol -except ImportError: - raise RuntimeError('cannot import "carla_server_pb2.py", run ' - 'the protobuf compiler to generate this file') - - -Translation = namedtuple('Translation', 'x y z') -Translation.__new__.__defaults__ = (0.0, 0.0, 0.0) - -Rotation = namedtuple('Rotation', 'pitch yaw roll') -Rotation.__new__.__defaults__ = (0.0, 0.0, 0.0) - -Scale = namedtuple('Scale', 'x y z') -Scale.__new__.__defaults__ = (1.0, 1.0, 1.0) - - -class Transform(object): - """A 3D transformation. - - The transformation is applied in the order: scale, rotation, translation. - """ - - def __init__(self, *args, **kwargs): - if 'matrix' in kwargs: - self.matrix = kwargs['matrix'] - return - if isinstance(args[0], carla_protocol.Transform): - args = [ - Translation( - args[0].location.x, - args[0].location.y, - args[0].location.z), - Rotation( - args[0].rotation.pitch, - args[0].rotation.yaw, - args[0].rotation.roll) - ] - self.matrix = numpy.matrix(numpy.identity(4)) - self.set(*args, **kwargs) - - def set(self, *args): - """Builds the transform matrix given a Translate, Rotation - and Scale. - """ - translation = Translation() - rotation = Rotation() - scale = Scale() - - if len(args) > 3: - raise ValueError("'Transform' accepts 3 values as maximum.") - - def get_single_obj_type(obj_type): - """Returns the unique object contained in the - arguments lists that is instance of 'obj_type'. - """ - obj = [x for x in args if isinstance(x, obj_type)] - if len(obj) > 1: - raise ValueError("Transform only accepts one instances of " + - str(obj_type) + " as a parameter") - elif not obj: - # Create an instance of the type that is 'obj_type' - return obj_type() - return obj[0] - - translation = get_single_obj_type(Translation) - rotation = get_single_obj_type(Rotation) - scale = get_single_obj_type(Scale) - - for param in args: - if not isinstance(param, Translation) and \ - not isinstance(param, Rotation) and \ - not isinstance(param, Scale): - raise TypeError( - "'" + str(type(param)) + "' type not match with \ - 'Translation', 'Rotation' or 'Scale'") - - # Transformation matrix - cy = math.cos(numpy.radians(rotation.yaw)) - sy = math.sin(numpy.radians(rotation.yaw)) - cr = math.cos(numpy.radians(rotation.roll)) - sr = math.sin(numpy.radians(rotation.roll)) - cp = math.cos(numpy.radians(rotation.pitch)) - sp = math.sin(numpy.radians(rotation.pitch)) - self.matrix[0, 3] = translation.x - self.matrix[1, 3] = translation.y - self.matrix[2, 3] = translation.z - self.matrix[0, 0] = scale.x * (cp * cy) - self.matrix[0, 1] = scale.y * (cy * sp * sr - sy * cr) - self.matrix[0, 2] = -scale.z * (cy * sp * cr + sy * sr) - self.matrix[1, 0] = scale.x * (sy * cp) - self.matrix[1, 1] = scale.y * (sy * sp * sr + cy * cr) - self.matrix[1, 2] = scale.z * (cy * sr - sy * sp * cr) - self.matrix[2, 0] = scale.x * (sp) - self.matrix[2, 1] = -scale.y * (cp * sr) - self.matrix[2, 2] = scale.z * (cp * cr) - - def inverse(self): - """Return the inverse transform.""" - return Transform(matrix=numpy.linalg.inv(self.matrix)) - - def transform_points(self, points): - """ - Given a 4x4 transformation matrix, transform an array of 3D points. - Expected point foramt: [[X0,Y0,Z0],..[Xn,Yn,Zn]] - """ - # Needed foramt: [[X0,..Xn],[Z0,..Zn],[Z0,..Zn]]. So let's transpose - # the point matrix. - points = points.transpose() - # Add 1s row: [[X0..,Xn],[Y0..,Yn],[Z0..,Zn],[1,..1]] - points = numpy.append(points, numpy.ones((1, points.shape[1])), axis=0) - # Point transformation - points = self.matrix * points - # Return all but last row - return points[0:3].transpose() - - def __mul__(self, other): - return Transform(matrix=numpy.dot(self.matrix, other.matrix)) - - def __str__(self): - return str(self.matrix) diff --git a/Deprecated/PythonClient/carla/util.py b/Deprecated/PythonClient/carla/util.py deleted file mode 100644 index 80995fb76..000000000 --- a/Deprecated/PythonClient/carla/util.py +++ /dev/null @@ -1,68 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -import datetime -import sys - -from contextlib import contextmanager - - -@contextmanager -def make_connection(client_type, *args, **kwargs): - """Context manager to create and connect a networking client object.""" - client = None - try: - client = client_type(*args, **kwargs) - client.connect() - yield client - finally: - if client is not None: - client.disconnect() - - -class StopWatch(object): - def __init__(self): - self.start = datetime.datetime.now() - self.end = None - - def restart(self): - self.start = datetime.datetime.now() - self.end = None - - def stop(self): - self.end = datetime.datetime.now() - - def seconds(self): - return (self.end - self.start).total_seconds() - - def milliseconds(self): - return 1000.0 * self.seconds() - - -def to_hex_str(header): - return ':'.join('{:02x}'.format(ord(c)) for c in header) - - -if sys.version_info >= (3, 3): - - import shutil - - def print_over_same_line(text): - terminal_width = shutil.get_terminal_size((80, 20)).columns - empty_space = max(0, terminal_width - len(text)) - sys.stdout.write('\r' + text + empty_space * ' ') - sys.stdout.flush() - -else: - - # Workaround for older Python versions. - def print_over_same_line(text): - line_length = max(print_over_same_line.last_line_length, len(text)) - empty_space = max(0, line_length - len(text)) - sys.stdout.write('\r' + text + empty_space * ' ') - sys.stdout.flush() - print_over_same_line.last_line_length = line_length - print_over_same_line.last_line_length = 0 diff --git a/Deprecated/PythonClient/client_example.py b/Deprecated/PythonClient/client_example.py deleted file mode 100755 index 5095e23f5..000000000 --- a/Deprecated/PythonClient/client_example.py +++ /dev/null @@ -1,250 +0,0 @@ -#!/usr/bin/env python3 - -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""Basic CARLA client example.""" - -from __future__ import print_function - -import argparse -import logging -import random -import time - -from carla.client import make_carla_client -from carla.sensor import Camera, Lidar -from carla.settings import CarlaSettings -from carla.tcp import TCPConnectionError -from carla.util import print_over_same_line - - -def run_carla_client(args): - # Here we will run 3 episodes with 300 frames each. - number_of_episodes = 3 - frames_per_episode = 300 - - # We assume the CARLA server is already waiting for a client to connect at - # host:port. To create a connection we can use the `make_carla_client` - # context manager, it creates a CARLA client object and starts the - # connection. It will throw an exception if something goes wrong. The - # context manager makes sure the connection is always cleaned up on exit. - with make_carla_client(args.host, args.port) as client: - print('CarlaClient connected') - - for episode in range(0, number_of_episodes): - # Start a new episode. - - if args.settings_filepath is None: - - # Create a CarlaSettings object. This object is a wrapper around - # the CarlaSettings.ini file. Here we set the configuration we - # want for the new episode. - settings = CarlaSettings() - settings.set( - SynchronousMode=True, - SendNonPlayerAgentsInfo=True, - NumberOfVehicles=20, - NumberOfPedestrians=40, - WeatherId=random.choice([1, 3, 7, 8, 14]), - QualityLevel=args.quality_level) - settings.randomize_seeds() - - # Now we want to add a couple of cameras to the player vehicle. - # We will collect the images produced by these cameras every - # frame. - - # The default camera captures RGB images of the scene. - camera0 = Camera('CameraRGB') - # Set image resolution in pixels. - camera0.set_image_size(800, 600) - # Set its position relative to the car in meters. - camera0.set_position(0.30, 0, 1.30) - settings.add_sensor(camera0) - - # Let's add another camera producing ground-truth depth. - camera1 = Camera('CameraDepth', PostProcessing='Depth') - camera1.set_image_size(800, 600) - camera1.set_position(0.30, 0, 1.30) - settings.add_sensor(camera1) - - if args.lidar: - lidar = Lidar('Lidar32') - lidar.set_position(0, 0, 2.50) - lidar.set_rotation(0, 0, 0) - lidar.set( - Channels=32, - Range=50, - PointsPerSecond=100000, - RotationFrequency=10, - UpperFovLimit=10, - LowerFovLimit=-30) - settings.add_sensor(lidar) - - else: - - # Alternatively, we can load these settings from a file. - with open(args.settings_filepath, 'r') as fp: - settings = fp.read() - - # Now we load these settings into the server. The server replies - # with a scene description containing the available start spots for - # the player. Here we can provide a CarlaSettings object or a - # CarlaSettings.ini file as string. - scene = client.load_settings(settings) - - # Choose one player start at random. - number_of_player_starts = len(scene.player_start_spots) - player_start = random.randint(0, max(0, number_of_player_starts - 1)) - - # Notify the server that we want to start the episode at the - # player_start index. This function blocks until the server is ready - # to start the episode. - print('Starting new episode at %r...' % scene.map_name) - client.start_episode(player_start) - - # Iterate every frame in the episode. - for frame in range(0, frames_per_episode): - - # Read the data produced by the server this frame. - measurements, sensor_data = client.read_data() - - # Print some of the measurements. - print_measurements(measurements) - - # Save the images to disk if requested. - if args.save_images_to_disk: - for name, measurement in sensor_data.items(): - filename = args.out_filename_format.format(episode, name, frame) - measurement.save_to_disk(filename) - - # We can access the encoded data of a given image as numpy - # array using its "data" property. For instance, to get the - # depth value (normalized) at pixel X, Y - # - # depth_array = sensor_data['CameraDepth'].data - # value_at_pixel = depth_array[Y, X] - # - - # Now we have to send the instructions to control the vehicle. - # If we are in synchronous mode the server will pause the - # simulation until we send this control. - - if not args.autopilot: - - client.send_control( - steer=random.uniform(-1.0, 1.0), - throttle=0.5, - brake=0.0, - hand_brake=False, - reverse=False) - - else: - - # Together with the measurements, the server has sent the - # control that the in-game autopilot would do this frame. We - # can enable autopilot by sending back this control to the - # server. We can modify it if wanted, here for instance we - # will add some noise to the steer. - - control = measurements.player_measurements.autopilot_control - control.steer += random.uniform(-0.1, 0.1) - client.send_control(control) - - -def print_measurements(measurements): - number_of_agents = len(measurements.non_player_agents) - player_measurements = measurements.player_measurements - message = 'Vehicle at ({pos_x:.1f}, {pos_y:.1f}), ' - message += '{speed:.0f} km/h, ' - message += 'Collision: {{vehicles={col_cars:.0f}, pedestrians={col_ped:.0f}, other={col_other:.0f}}}, ' - message += '{other_lane:.0f}% other lane, {offroad:.0f}% off-road, ' - message += '({agents_num:d} non-player agents in the scene)' - message = message.format( - pos_x=player_measurements.transform.location.x, - pos_y=player_measurements.transform.location.y, - speed=player_measurements.forward_speed * 3.6, # m/s -> km/h - col_cars=player_measurements.collision_vehicles, - col_ped=player_measurements.collision_pedestrians, - col_other=player_measurements.collision_other, - other_lane=100 * player_measurements.intersection_otherlane, - offroad=100 * player_measurements.intersection_offroad, - agents_num=number_of_agents) - print_over_same_line(message) - - -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( - '-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') - - 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) - - args.out_filename_format = '_out/episode_{:0>4d}/{:s}/{:0>6d}' - - while True: - try: - - run_carla_client(args) - - print('Done.') - return - - except TCPConnectionError as error: - logging.error(error) - time.sleep(1) - - -if __name__ == '__main__': - - try: - main() - except KeyboardInterrupt: - print('\nCancelled by user. Bye!') diff --git a/Deprecated/PythonClient/driving_benchmark_example.py b/Deprecated/PythonClient/driving_benchmark_example.py deleted file mode 100755 index 84b5b6618..000000000 --- a/Deprecated/PythonClient/driving_benchmark_example.py +++ /dev/null @@ -1,92 +0,0 @@ -#!/usr/bin/env python3 - -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -import argparse -import logging - -from carla.driving_benchmark import run_driving_benchmark -from carla.driving_benchmark.experiment_suites import CoRL2017 -from carla.driving_benchmark.experiment_suites import BasicExperimentSuite -from carla.agent import ForwardAgent - -if __name__ == '__main__': - - argparser = argparse.ArgumentParser(description=__doc__) - argparser.add_argument( - '-v', '--verbose', - action='store_true', - dest='verbose', - help='print some extra status information') - argparser.add_argument( - '-db', '--debug', - 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( - '-c', '--city-name', - metavar='C', - default='Town01', - help='The town that is going to be used on benchmark' - + '(needs to match active town in server, options: Town01 or Town02)') - argparser.add_argument( - '-n', '--log_name', - metavar='T', - default='test', - help='The name of the log file to be created by the benchmark' - ) - argparser.add_argument( - '--corl-2017', - action='store_true', - help='If you want to benchmark the corl-2017 instead of the Basic one' - ) - argparser.add_argument( - '--continue-experiment', - action='store_true', - help='If you want to continue the experiment with the same name' - ) - - args = argparser.parse_args() - if args.debug: - log_level = logging.DEBUG - elif args.verbose: - log_level = logging.INFO - else: - log_level = logging.WARNING - - logging.basicConfig(format='%(levelname)s: %(message)s', level=log_level) - logging.info('listening to server %s:%s', args.host, args.port) - - # We instantiate a forward agent, a simple policy that just set - # acceleration as 0.9 and steering as zero - agent = ForwardAgent() - - # We instantiate an experiment suite. Basically a set of experiments - # that are going to be evaluated on this benchmark. - if args.corl_2017: - experiment_suite = CoRL2017(args.city_name) - else: - print (' WARNING: running the basic driving benchmark, to run for CoRL 2017' - ' experiment suites, you should run' - ' python driving_benchmark_example.py --corl-2017') - experiment_suite = BasicExperimentSuite(args.city_name) - - # Now actually run the driving_benchmark - run_driving_benchmark(agent, experiment_suite, args.city_name, - args.log_name, args.continue_experiment, - args.host, args.port) diff --git a/Deprecated/PythonClient/manual_control.py b/Deprecated/PythonClient/manual_control.py deleted file mode 100755 index a727bbb37..000000000 --- a/Deprecated/PythonClient/manual_control.py +++ /dev/null @@ -1,441 +0,0 @@ -#!/usr/bin/env python3 - -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -# Keyboard controlling for CARLA. Please refer to client_example.py for a simpler -# and more documented example. - -""" -Welcome to CARLA manual control. - -Use ARROWS or WASD keys for control. - - W : throttle - S : brake - AD : steer - Q : toggle reverse - Space : hand-brake - P : toggle autopilot - - R : restart level - -STARTING in a moment... -""" - -from __future__ import print_function - -import argparse -import logging -import random -import time - -try: - import pygame - from pygame.locals import K_DOWN - from pygame.locals import K_LEFT - from pygame.locals import K_RIGHT - from pygame.locals import K_SPACE - from pygame.locals import K_UP - from pygame.locals import K_a - from pygame.locals import K_d - from pygame.locals import K_p - from pygame.locals import K_q - from pygame.locals import K_r - from pygame.locals import K_s - from pygame.locals import K_w -except ImportError: - raise RuntimeError('cannot import pygame, make sure pygame package is installed') - -try: - import numpy as np -except ImportError: - raise RuntimeError('cannot import numpy, make sure numpy package is installed') - -from carla import image_converter -from carla import sensor -from carla.client import make_carla_client, VehicleControl -from carla.planner.map import CarlaMap -from carla.settings import CarlaSettings -from carla.tcp import TCPConnectionError -from carla.util import print_over_same_line - - -WINDOW_WIDTH = 800 -WINDOW_HEIGHT = 600 -MINI_WINDOW_WIDTH = 320 -MINI_WINDOW_HEIGHT = 180 - - -def make_carla_settings(args): - """Make a CarlaSettings object with the settings we need.""" - settings = CarlaSettings() - settings.set( - SynchronousMode=False, - SendNonPlayerAgentsInfo=True, - NumberOfVehicles=15, - NumberOfPedestrians=30, - WeatherId=random.choice([1, 3, 7, 8, 14]), - QualityLevel=args.quality_level) - settings.randomize_seeds() - camera0 = sensor.Camera('CameraRGB') - camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT) - camera0.set_position(2.0, 0.0, 1.4) - camera0.set_rotation(0.0, 0.0, 0.0) - settings.add_sensor(camera0) - camera1 = sensor.Camera('CameraDepth', PostProcessing='Depth') - camera1.set_image_size(MINI_WINDOW_WIDTH, MINI_WINDOW_HEIGHT) - camera1.set_position(2.0, 0.0, 1.4) - camera1.set_rotation(0.0, 0.0, 0.0) - settings.add_sensor(camera1) - camera2 = sensor.Camera('CameraSemSeg', PostProcessing='SemanticSegmentation') - camera2.set_image_size(MINI_WINDOW_WIDTH, MINI_WINDOW_HEIGHT) - camera2.set_position(2.0, 0.0, 1.4) - camera2.set_rotation(0.0, 0.0, 0.0) - settings.add_sensor(camera2) - if args.lidar: - lidar = sensor.Lidar('Lidar32') - lidar.set_position(0, 0, 2.5) - lidar.set_rotation(0, 0, 0) - lidar.set( - Channels=32, - Range=50, - PointsPerSecond=100000, - RotationFrequency=10, - UpperFovLimit=10, - LowerFovLimit=-30) - settings.add_sensor(lidar) - return settings - - -class Timer(object): - def __init__(self): - self.step = 0 - self._lap_step = 0 - self._lap_time = time.time() - - def tick(self): - self.step += 1 - - def lap(self): - self._lap_step = self.step - self._lap_time = time.time() - - def ticks_per_second(self): - return float(self.step - self._lap_step) / self.elapsed_seconds_since_lap() - - def elapsed_seconds_since_lap(self): - return time.time() - self._lap_time - - -class CarlaGame(object): - def __init__(self, carla_client, args): - self.client = carla_client - self._carla_settings = make_carla_settings(args) - self._timer = None - self._display = None - self._main_image = None - self._mini_view_image1 = None - self._mini_view_image2 = None - self._enable_autopilot = args.autopilot - self._lidar_measurement = None - self._map_view = None - self._is_on_reverse = False - self._display_map = args.map - self._city_name = None - self._map = None - self._map_shape = None - self._map_view = None - self._position = None - self._agent_positions = None - - def execute(self): - """Launch the PyGame.""" - pygame.init() - self._initialize_game() - try: - while True: - for event in pygame.event.get(): - if event.type == pygame.QUIT: - return - self._on_loop() - self._on_render() - finally: - pygame.quit() - - def _initialize_game(self): - self._on_new_episode() - - if self._city_name is not None: - self._map = CarlaMap(self._city_name) - self._map_shape = self._map.map_image.shape - self._map_view = self._map.get_map(WINDOW_HEIGHT) - - extra_width = int((WINDOW_HEIGHT/float(self._map_shape[0]))*self._map_shape[1]) - self._display = pygame.display.set_mode( - (WINDOW_WIDTH + extra_width, WINDOW_HEIGHT), - pygame.HWSURFACE | pygame.DOUBLEBUF) - else: - self._display = pygame.display.set_mode( - (WINDOW_WIDTH, WINDOW_HEIGHT), - pygame.HWSURFACE | pygame.DOUBLEBUF) - - logging.debug('pygame started') - - def _on_new_episode(self): - self._carla_settings.randomize_seeds() - self._carla_settings.randomize_weather() - scene = self.client.load_settings(self._carla_settings) - if self._display_map: - self._city_name = scene.map_name - number_of_player_starts = len(scene.player_start_spots) - player_start = np.random.randint(number_of_player_starts) - print('Starting new episode...') - self.client.start_episode(player_start) - self._timer = Timer() - self._is_on_reverse = False - - def _on_loop(self): - self._timer.tick() - - measurements, sensor_data = self.client.read_data() - - self._main_image = sensor_data.get('CameraRGB', None) - self._mini_view_image1 = sensor_data.get('CameraDepth', None) - self._mini_view_image2 = sensor_data.get('CameraSemSeg', None) - self._lidar_measurement = sensor_data.get('Lidar32', None) - - # Print measurements every second. - if self._timer.elapsed_seconds_since_lap() > 1.0: - if self._city_name is not None: - # Function to get car position on map. - map_position = self._map.convert_to_pixel([ - measurements.player_measurements.transform.location.x, - measurements.player_measurements.transform.location.y, - measurements.player_measurements.transform.location.z]) - # Function to get orientation of the road car is in. - lane_orientation = self._map.get_lane_orientation([ - measurements.player_measurements.transform.location.x, - measurements.player_measurements.transform.location.y, - measurements.player_measurements.transform.location.z]) - - self._print_player_measurements_map( - measurements.player_measurements, - map_position, - lane_orientation) - else: - self._print_player_measurements(measurements.player_measurements) - - # Plot position on the map as well. - - self._timer.lap() - - control = self._get_keyboard_control(pygame.key.get_pressed()) - # Set the player position - if self._city_name is not None: - self._position = self._map.convert_to_pixel([ - measurements.player_measurements.transform.location.x, - measurements.player_measurements.transform.location.y, - measurements.player_measurements.transform.location.z]) - self._agent_positions = measurements.non_player_agents - - if control is None: - self._on_new_episode() - elif self._enable_autopilot: - self.client.send_control(measurements.player_measurements.autopilot_control) - else: - self.client.send_control(control) - - def _get_keyboard_control(self, keys): - """ - Return a VehicleControl message based on the pressed keys. Return None - if a new episode was requested. - """ - if keys[K_r]: - return None - control = VehicleControl() - if keys[K_LEFT] or keys[K_a]: - control.steer = -1.0 - if keys[K_RIGHT] or keys[K_d]: - control.steer = 1.0 - if keys[K_UP] or keys[K_w]: - control.throttle = 1.0 - if keys[K_DOWN] or keys[K_s]: - control.brake = 1.0 - if keys[K_SPACE]: - control.hand_brake = True - if keys[K_q]: - self._is_on_reverse = not self._is_on_reverse - if keys[K_p]: - self._enable_autopilot = not self._enable_autopilot - control.reverse = self._is_on_reverse - return control - - def _print_player_measurements_map( - self, - player_measurements, - map_position, - lane_orientation): - message = 'Step {step} ({fps:.1f} FPS): ' - message += 'Map Position ({map_x:.1f},{map_y:.1f}) ' - message += 'Lane Orientation ({ori_x:.1f},{ori_y:.1f}) ' - message += '{speed:.2f} km/h, ' - message += '{other_lane:.0f}% other lane, {offroad:.0f}% off-road' - message = message.format( - map_x=map_position[0], - map_y=map_position[1], - ori_x=lane_orientation[0], - ori_y=lane_orientation[1], - step=self._timer.step, - fps=self._timer.ticks_per_second(), - speed=player_measurements.forward_speed * 3.6, - other_lane=100 * player_measurements.intersection_otherlane, - offroad=100 * player_measurements.intersection_offroad) - print_over_same_line(message) - - def _print_player_measurements(self, player_measurements): - message = 'Step {step} ({fps:.1f} FPS): ' - message += '{speed:.2f} km/h, ' - message += '{other_lane:.0f}% other lane, {offroad:.0f}% off-road' - message = message.format( - step=self._timer.step, - fps=self._timer.ticks_per_second(), - speed=player_measurements.forward_speed * 3.6, - other_lane=100 * player_measurements.intersection_otherlane, - offroad=100 * player_measurements.intersection_offroad) - print_over_same_line(message) - - def _on_render(self): - gap_x = (WINDOW_WIDTH - 2 * MINI_WINDOW_WIDTH) / 3 - mini_image_y = WINDOW_HEIGHT - MINI_WINDOW_HEIGHT - gap_x - - if self._main_image is not None: - array = image_converter.to_rgb_array(self._main_image) - surface = pygame.surfarray.make_surface(array.swapaxes(0, 1)) - self._display.blit(surface, (0, 0)) - - if self._mini_view_image1 is not None: - array = image_converter.depth_to_logarithmic_grayscale(self._mini_view_image1) - surface = pygame.surfarray.make_surface(array.swapaxes(0, 1)) - self._display.blit(surface, (gap_x, mini_image_y)) - - if self._mini_view_image2 is not None: - array = image_converter.labels_to_cityscapes_palette( - self._mini_view_image2) - surface = pygame.surfarray.make_surface(array.swapaxes(0, 1)) - - self._display.blit( - surface, (2 * gap_x + MINI_WINDOW_WIDTH, mini_image_y)) - - if self._lidar_measurement is not None: - lidar_data = np.array(self._lidar_measurement.data[:, :2]) - lidar_data *= 2.0 - lidar_data += 100.0 - lidar_data = np.fabs(lidar_data) - lidar_data = lidar_data.astype(np.int32) - lidar_data = np.reshape(lidar_data, (-1, 2)) - #draw lidar - lidar_img_size = (200, 200, 3) - lidar_img = np.zeros(lidar_img_size) - lidar_img[tuple(lidar_data.T)] = (255, 255, 255) - surface = pygame.surfarray.make_surface(lidar_img) - self._display.blit(surface, (10, 10)) - - if self._map_view is not None: - array = self._map_view - array = array[:, :, :3] - - new_window_width = \ - (float(WINDOW_HEIGHT) / float(self._map_shape[0])) * \ - float(self._map_shape[1]) - surface = pygame.surfarray.make_surface(array.swapaxes(0, 1)) - - w_pos = int(self._position[0]*(float(WINDOW_HEIGHT)/float(self._map_shape[0]))) - h_pos = int(self._position[1] *(new_window_width/float(self._map_shape[1]))) - - pygame.draw.circle(surface, [255, 0, 0, 255], (w_pos, h_pos), 6, 0) - for agent in self._agent_positions: - if agent.HasField('vehicle'): - agent_position = self._map.convert_to_pixel([ - agent.vehicle.transform.location.x, - agent.vehicle.transform.location.y, - agent.vehicle.transform.location.z]) - - w_pos = int(agent_position[0]*(float(WINDOW_HEIGHT)/float(self._map_shape[0]))) - h_pos = int(agent_position[1] *(new_window_width/float(self._map_shape[1]))) - - pygame.draw.circle(surface, [255, 0, 255, 255], (w_pos, h_pos), 4, 0) - - self._display.blit(surface, (WINDOW_WIDTH, 0)) - - pygame.display.flip() - - -def main(): - argparser = argparse.ArgumentParser( - description='CARLA Manual Control Client') - 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( - '-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( - '-m', '--map', - action='store_true', - help='plot the map of the current city') - 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) - - print(__doc__) - - while True: - try: - - with make_carla_client(args.host, args.port) as client: - game = CarlaGame(client, args) - game.execute() - break - - except TCPConnectionError as error: - logging.error(error) - time.sleep(1) - - -if __name__ == '__main__': - - try: - main() - except KeyboardInterrupt: - print('\nCancelled by user. Bye!') diff --git a/Deprecated/PythonClient/point_cloud_example.py b/Deprecated/PythonClient/point_cloud_example.py deleted file mode 100755 index 65bef0d65..000000000 --- a/Deprecated/PythonClient/point_cloud_example.py +++ /dev/null @@ -1,191 +0,0 @@ -#!/usr/bin/env python3 - -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB), and the INTEL Visual Computing Lab. -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""Basic CARLA client to generate point cloud in PLY format that you - can visualize with MeshLab (meshlab.net) for instance. Please - refer to client_example.py for a simpler and more documented example.""" - -from __future__ import print_function - -import argparse -import logging -import os -import random -import time - -from carla.client import make_carla_client -from carla.sensor import Camera -from carla.settings import CarlaSettings -from carla.tcp import TCPConnectionError -from carla.util import print_over_same_line, StopWatch -from carla.image_converter import depth_to_local_point_cloud, to_rgb_array -from carla.transform import Transform - - -def run_carla_client(host, port, far): - # Here we will run a single episode with 300 frames. - number_of_frames = 3000 - frame_step = 100 # Save one image every 100 frames - output_folder = '_out' - image_size = [800, 600] - camera_local_pos = [0.3, 0.0, 1.3] # [X, Y, Z] - camera_local_rotation = [0, 0, 0] # [pitch(Y), yaw(Z), roll(X)] - fov = 70 - - # Connect with the server - with make_carla_client(host, port) as client: - print('CarlaClient connected') - - # Here we load the settings. - settings = CarlaSettings() - settings.set( - SynchronousMode=True, - SendNonPlayerAgentsInfo=False, - NumberOfVehicles=20, - NumberOfPedestrians=40, - WeatherId=random.choice([1, 3, 7, 8, 14])) - settings.randomize_seeds() - - camera1 = Camera('CameraDepth', PostProcessing='Depth', FOV=fov) - camera1.set_image_size(*image_size) - camera1.set_position(*camera_local_pos) - camera1.set_rotation(*camera_local_rotation) - settings.add_sensor(camera1) - - camera2 = Camera('CameraRGB', PostProcessing='SceneFinal', FOV=fov) - camera2.set_image_size(*image_size) - camera2.set_position(*camera_local_pos) - camera2.set_rotation(*camera_local_rotation) - settings.add_sensor(camera2) - - client.load_settings(settings) - - # Start at location index id '0' - client.start_episode(0) - - # Compute the camera transform matrix - camera_to_car_transform = camera2.get_unreal_transform() - - # Iterate every frame in the episode except for the first one. - for frame in range(1, number_of_frames): - # Read the data produced by the server this frame. - measurements, sensor_data = client.read_data() - - # Save one image every 'frame_step' frames - if not frame % frame_step: - # Start transformations time mesure. - timer = StopWatch() - - # RGB image [[[r,g,b],..[r,g,b]],..[[r,g,b],..[r,g,b]]] - image_RGB = to_rgb_array(sensor_data['CameraRGB']) - - # 2d to (camera) local 3d - # We use the image_RGB to colorize each 3D point, this is optional. - # "max_depth" is used to keep only the points that are near to the - # camera, meaning 1.0 the farest points (sky) - point_cloud = depth_to_local_point_cloud( - sensor_data['CameraDepth'], - image_RGB, - max_depth=far - ) - - # (Camera) local 3d to world 3d. - # Get the transform from the player protobuf transformation. - world_transform = Transform( - measurements.player_measurements.transform - ) - - # Compute the final transformation matrix. - car_to_world_transform = world_transform * camera_to_car_transform - - # Car to World transformation given the 3D points and the - # transformation matrix. - point_cloud.apply_transform(car_to_world_transform) - - # End transformations time mesure. - timer.stop() - - # Save PLY to disk - # This generates the PLY string with the 3D points and the RGB colors - # for each row of the file. - point_cloud.save_to_disk(os.path.join( - output_folder, '{:0>5}.ply'.format(frame)) - ) - - print_message(timer.milliseconds(), len(point_cloud), frame) - - client.send_control( - measurements.player_measurements.autopilot_control - ) - - -def print_message(elapsed_time, point_n, frame): - message = ' '.join([ - 'Transformations took {:>3.0f} ms.', - 'Saved {:>6} points to "{:0>5}.ply".' - ]).format(elapsed_time, point_n, frame) - print_over_same_line(message) - - -def check_far(value): - fvalue = float(value) - if fvalue < 0.0 or fvalue > 1.0: - raise argparse.ArgumentTypeError( - "{} must be a float between 0.0 and 1.0") - return fvalue - - -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( - '-f', '--far', - default=0.2, - type=check_far, - help='The maximum save distance of camera-point ' - '[0.0 (near), 1.0 (far)] (default: 0.2)') - - 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) - - while True: - try: - run_carla_client(host=args.host, port=args.port, far=args.far) - print('\nDone!') - return - - except TCPConnectionError as error: - logging.error(error) - time.sleep(1) - - -if __name__ == '__main__': - - try: - main() - except KeyboardInterrupt: - print('\nClient stoped by user.') diff --git a/Deprecated/PythonClient/requirements.txt b/Deprecated/PythonClient/requirements.txt deleted file mode 100644 index f170835dd..000000000 --- a/Deprecated/PythonClient/requirements.txt +++ /dev/null @@ -1,6 +0,0 @@ -Pillow -numpy -protobuf -pygame -matplotlib -future diff --git a/Deprecated/PythonClient/setup.py b/Deprecated/PythonClient/setup.py deleted file mode 100644 index 7071693c7..000000000 --- a/Deprecated/PythonClient/setup.py +++ /dev/null @@ -1,16 +0,0 @@ -from setuptools import setup - -# @todo Dependencies are missing. - -setup( - name='carla_client', - version='0.8.4', - packages=['carla', 'carla.driving_benchmark', 'carla.agent', - 'carla.driving_benchmark.experiment_suites', 'carla.planner'], - license='MIT License', - description='Python API for communicating with the CARLA server.', - url='https://github.com/carla-simulator/carla', - author='The CARLA team', - author_email='carla.simulator@gmail.com', - include_package_data=True -) diff --git a/Deprecated/PythonClient/test/__init__.py b/Deprecated/PythonClient/test/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/Deprecated/PythonClient/test/acceptance_tests/__init__.py b/Deprecated/PythonClient/test/acceptance_tests/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/Deprecated/PythonClient/test/benchmark_server.py b/Deprecated/PythonClient/test/benchmark_server.py deleted file mode 100755 index 171497f38..000000000 --- a/Deprecated/PythonClient/test/benchmark_server.py +++ /dev/null @@ -1,242 +0,0 @@ -#!/usr/bin/env python3 - -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""A client for benchmarking the CARLA server.""" - -import argparse -import logging -import os -import random -import sys -import time - -sys.path.append(os.path.join(os.path.dirname(__file__), '..')) - -import carla - -from carla import sensor -from carla.client import make_carla_client -from carla.sensor import Camera -from carla.settings import CarlaSettings -from carla.util import StopWatch - -TEXT = \ -"""=========================== -Annotated {count:d} frames. ---------------------------- -average = {avg:.2f} FPS -maximum = {max:.2f} FPS -minimum = {min:.2f} FPS -=========================== -""" - -def make_base_settings(): - return CarlaSettings( - WeatherId=1, - SendNonPlayerAgentsInfo=False, - SynchronousMode=False, - NumberOfVehicles=20, - NumberOfPedestrians=30, - SeedVehicles=123456789, - SeedPedestrians=123456789, - QualityLevel='Epic') - - -def generate_settings_scenario_001(): - logging.info('Scenario 001: no sensors') - return make_base_settings() - - -def generate_settings_scenario_002(): - logging.info('Scenario 002: no sensors, no agents at all') - settings = make_base_settings() - settings.set(NumberOfVehicles=0, NumberOfPedestrians=0) - return settings - - -def generate_settings_scenario_003(): - logging.info('Scenario 003: no sensors, no pedestrians') - settings = make_base_settings() - settings.set(NumberOfPedestrians=0) - return settings - - -def generate_settings_scenario_004(): - logging.info('Scenario 004: no sensors, no vehicles') - settings = make_base_settings() - settings.set(NumberOfVehicles=0) - return settings - - -def generate_settings_scenario_005(): - logging.info('Scenario 005: no sensors, hard rain') - settings = make_base_settings() - settings.set(WeatherId=13) - return settings - - -def generate_settings_scenario_006(): - logging.info('Scenario 006: no sensors, sending agents info') - settings = make_base_settings() - settings.set(SendNonPlayerAgentsInfo=True) - return settings - - -def generate_settings_scenario_007(): - logging.info('Scenario 007: single camera RGB') - settings = make_base_settings() - settings.add_sensor(Camera('DefaultRGBCamera')) - return settings - - -def generate_settings_scenario_008(): - logging.info('Scenario 008: single camera Depth') - settings = make_base_settings() - settings.add_sensor(Camera('DefaultDepthCamera', PostProcessing='Depth')) - return settings - - -def generate_settings_scenario_009(): - logging.info('Scenario 009: single camera SemanticSegmentation') - settings = make_base_settings() - settings.add_sensor(Camera('DefaultSemSegCamera', PostProcessing='SemanticSegmentation')) - return settings - - -def generate_settings_scenario_010(): - logging.info('Scenario 010: 3 cameras') - settings = make_base_settings() - settings.add_sensor(Camera('DefaultRGBCamera')) - settings.add_sensor(Camera('DefaultDepthCamera', PostProcessing='Depth')) - settings.add_sensor(Camera('DefaultSemSegCamera', PostProcessing='SemanticSegmentation')) - return settings - - -class FPSWatch(object): - def __init__(self): - self.stop_watch = StopWatch() - self.sum = 0.0 - self.count = 0 - self.max = 0.0 - self.min = float("inf") - - def annotate(self): - self.stop_watch.stop() - fps = 1.0 / self.stop_watch.seconds() - self.sum += fps - self.count += 1 - self.max = max(self.max, fps) - self.min = min(self.min, fps) - self.stop_watch.restart() - - def __str__(self): - return TEXT.format( - count=self.count, - avg=self.sum/self.count, - max=self.max, - min=self.min) - - -def run_carla_client(args, settings_generators): - with make_carla_client(args.host, args.port, timeout=25) as client: - for settings_generator in settings_generators: - scene = client.load_settings(settings_generator()) - client.start_episode(0) - watch = FPSWatch() - for frame in range(0, 3000): - measurements, sensor_data = client.read_data() - client.send_control(measurements.player_measurements.autopilot_control) - watch.annotate() - print(str(watch)) - print('done.') - - -def main(): - argparser = argparse.ArgumentParser(description=__doc__) - argparser.add_argument( - '-v', '--verbose', - action='store_true', - dest='debug', - help='print debug information') - argparser.add_argument( - '--log', - metavar='LOG_FILE', - default=None, - help='print output to file') - 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( - '-s', '--scenario', - metavar='N', - default=-1, - type=int, - help='benchmark scenario to use') - argparser.add_argument( - '-l', '--list', - action='store_true', - help='list available benchmark scenarios') - - args = argparser.parse_args() - - logging_config = { - 'format': '%(levelname)s: %(message)s', - 'level': logging.DEBUG if args.debug else logging.INFO - } - if args.log: - logging_config['filename'] = args.log - logging_config['filemode'] = 'w+' - logging.basicConfig(**logging_config) - - self_module = sys.modules[__name__] - generators = sorted(x for x in dir(self_module) if x.startswith('generate_settings_scenario_')) - - if args.list: - for generator_name in generators: - getattr(self_module, generator_name)() - return - - if args.scenario == -1: - generators_to_use = generators - elif args.scenario < 1 or args.scenario > len(generators): - logging.error('invalid scenario %d', args.scenario) - sys.exit(1) - else: - generators_to_use = [generators[args.scenario - 1]] - - settings_generators = [getattr(self_module, x) for x in generators_to_use] - - logging.info('listening to server %s:%s', args.host, args.port) - - while True: - try: - - run_carla_client(args, settings_generators) - return - - except AssertionError as assertion: - raise assertion - except Exception as exception: - logging.error('exception: %s', exception) - time.sleep(1) - - -if __name__ == '__main__': - - try: - main() - except KeyboardInterrupt: - print('\nCancelled by user. Bye!') diff --git a/Deprecated/PythonClient/test/console.py b/Deprecated/PythonClient/test/console.py deleted file mode 100644 index da1b73e60..000000000 --- a/Deprecated/PythonClient/test/console.py +++ /dev/null @@ -1,180 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""CARLA client console""" - - -import cmd -import logging -import subprocess -import tempfile -import threading -import time - - -from carla.client import CarlaClient -from carla.sensor import Camera, Image -from carla.settings import CarlaSettings - - -class _Control(object): - def __init__(self): - self.c_throttle = 0.0 - self.c_steer = 0.0 - self.c_brake = 0.0 - self.c_hand_brake = False - self.c_reverse = False - - def action_list(self): - return [x[2:] for x in dir(self) if x.startswith('c_')] - - def kwargs(self): - return dict((x[2:], getattr(self, x)) for x in dir(self) if x.startswith('c_')) - - def set(self, line): - control, value = line.split(' ') - control = 'c_' + control - if not hasattr(self, control): - raise ValueError('invalid control: %r' % control[2:]) - setattr(self, control, self._parse(type(getattr(self, control)), value)) - - @staticmethod - def _parse(atype, value): - if atype == bool: - false_keys = ['f', 'false', '0', 'n', 'no', 'disable', 'off'] - return value not in false_keys - return atype(value) - - -def get_default_carla_settings(args): - settings = CarlaSettings( - SynchronousMode=args.synchronous, - SendNonPlayerAgentsInfo=False, - NumberOfVehicles=20, - NumberOfPedestrians=40, - WeatherId=1) - settings.add_sensor(Camera('Camera1')) - return str(settings) - - -def edit_text(text): - editor = 'vim' - with tempfile.NamedTemporaryFile('w+', suffix='.ini') as fp: - fp.write(text) - fp.flush() - try: - if 0 != subprocess.run([editor, fp.name]).returncode: - print('Cancelled.') - return None - except FileNotFoundError: - logging.error('error opening text editor, is %r installed?', editor) - return None - fp.seek(0) - return fp.read() - - -class CarlaClientConsole(cmd.Cmd): - def __init__(self, args): - cmd.Cmd.__init__(self) - self.args = args - self.prompt = '\x1b[1;34m%s\x1b[0m ' % '(carla)' - self.client = CarlaClient(args.host, args.port) - self.settings = get_default_carla_settings(args) - self.print_measurements = False - self.control = _Control() - self.thread = threading.Thread(target=self._agent_thread_worker) - self.done = False - self.thread.start() - - def cleanup(self): - self.do_disconnect() - self.done = True - if self.thread.is_alive(): - self.thread.join() - - def default(self, line): - logging.error('unknown command \'%s\'!', line) - - def emptyline(self): - pass - - def precmd(self, line): - return line.strip().lower() - - def can_exit(self): - return True - - def do_exit(self, line=None): - """Exit the console.""" - return True - - def do_eof(self, line=None): - """Exit the console.""" - print('exit') - return self.do_exit(line) - - def help_help(self): - print('usage: help [topic]') - - def do_disconnect(self, line=None): - """Disconnect from the server.""" - self.client.disconnect() - - def do_new_episode(self, line=None): - """Request a new episode. Connect to the server if not connected.""" - try: - self.control = _Control() - if not self.client.connected(): - self.client.connect() - self.client.load_settings(self.settings) - self.client.start_episode(0) - logging.info('new episode started') - except Exception as exception: - logging.error(exception) - - def do_control(self, line=None): - """Set control message:\nusage: control [reset| ]\n(e.g., control throttle 0.5)""" - try: - if line == 'reset': - self.control = _Control() - else: - self.control.set(line) - logging.debug('control: %s', self.control.kwargs()) - except Exception as exception: - logging.error(exception) - - def complete_control(self, text, *args, **kwargs): - options = self.control.action_list() - options.append('reset') - return [x + ' ' for x in options if x.startswith(text)] - - def do_settings(self, line=None): - """Open a text editor to edit CARLA settings.""" - result = edit_text(self.settings) - if result is not None: - self.settings = result - - def do_print_measurements(self, line): - """Print received measurements to console.\nusage: print_measurements [t/f]""" - self.print_measurements = True if not line else _Control._parse(bool, line) - - def _agent_thread_worker(self): - filename = '_images/console/camera_{:0>3d}/image_{:0>8d}.png' - while not self.done: - try: - measurements, sensor_data = self.client.read_data() - if self.print_measurements: - print(measurements) - - if self.args.images_to_disk: - images = [x for x in sensor_data.values() if isinstance(x, Image)] - for n, image in enumerate(images): - path = filename.format(n, measurements.game_timestamp) - image.save_to_disk(path) - self.client.send_control(**self.control.kwargs()) - except Exception as exception: - # logging.exception(exception) - time.sleep(1) diff --git a/Deprecated/PythonClient/test/suite/Basic.py b/Deprecated/PythonClient/test/suite/Basic.py deleted file mode 100644 index 071ef69c4..000000000 --- a/Deprecated/PythonClient/test/suite/Basic.py +++ /dev/null @@ -1,130 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -import logging -import random - -import suite - -import carla - -from carla.client import CarlaClient -from carla.sensor import Camera, Image -from carla.sensor import Lidar, LidarMeasurement -from carla.settings import CarlaSettings -from carla.util import make_connection - - -class _BasicTestBase(suite.CarlaServerTest): - def run_carla_client(self, carla_settings, number_of_episodes, number_of_frames, use_autopilot_control=None): - with make_connection(CarlaClient, self.args.host, self.args.port, timeout=15) as client: - logging.info('CarlaClient connected, running %d episodes', number_of_episodes) - for _ in range(0, number_of_episodes): - carla_settings.randomize_seeds() - carla_settings.randomize_weather() - logging.debug('sending CarlaSettings:\n%s', carla_settings) - logging.info('new episode requested') - scene = client.load_settings(carla_settings) - number_of_player_starts = len(scene.player_start_spots) - player_start = random.randint(0, max(0, number_of_player_starts - 1)) - logging.info( - 'start episode at %d/%d player start (%d frames)', - player_start, - number_of_player_starts, - number_of_frames) - client.start_episode(player_start) - if use_autopilot_control is None: - use_autopilot_control = (random.random() < 0.5) - reverse = (random.random() < 0.2) - for _ in range(0, number_of_frames): - logging.debug('reading measurements...') - measurements, sensor_data = client.read_data() - images = [x for x in sensor_data.values() if isinstance(x, Image)] - number_of_agents = len(measurements.non_player_agents) - logging.debug('received data of %d agents', number_of_agents) - logging.debug('received %d images', len(images)) - if len(sensor_data) != len(carla_settings._sensors): - raise RuntimeError('received %d, expected %d' % (len(sensor_data), len(carla_settings._sensors))) - logging.debug('sending control...') - control = measurements.player_measurements.autopilot_control - if not use_autopilot_control: - control.steer = random.uniform(-1.0, 1.0) - control.throttle = 0.3 - control.hand_brake = False - control.reverse = reverse - client.send_control( - steer=control.steer, - throttle=control.throttle, - brake=control.brake, - hand_brake=control.hand_brake, - reverse=control.reverse) - - -class UseCase(_BasicTestBase): - def run(self): - settings = CarlaSettings() - settings.add_sensor(Camera('DefaultCamera')) - self.run_carla_client(settings, 5, 200) - - -class NoCamera(_BasicTestBase): - def run(self): - settings = CarlaSettings() - self.run_carla_client(settings, 3, 200) - - -class TwoCameras(_BasicTestBase): - def run(self): - settings = CarlaSettings() - settings.add_sensor(Camera('DefaultCamera')) - camera2 = Camera('Camera2') - camera2.set(PostProcessing='Depth', FOV=120) - camera2.set_image_size(1924, 1028) - settings.add_sensor(camera2) - self.run_carla_client(settings, 3, 100) - - -class SynchronousMode(_BasicTestBase): - def run(self): - settings = CarlaSettings(SynchronousMode=True) - settings.add_sensor(Camera('DefaultCamera')) - self.run_carla_client(settings, 3, 200) - - -class GetAgentsInfo(_BasicTestBase): - def run(self): - settings = CarlaSettings() - settings.set( - SynchronousMode=True, - SendNonPlayerAgentsInfo=True, - NumberOfVehicles=60, - NumberOfPedestrians=90) - settings.add_sensor(Camera('DefaultCamera')) - self.run_carla_client(settings, 3, 100) - - -class LongEpisode(_BasicTestBase): - def run(self): - settings = CarlaSettings() - settings.add_sensor(Camera('DefaultCamera')) - self.run_carla_client(settings, 1, 2000, use_autopilot_control=True) - - -class LidarTest(_BasicTestBase): - def run(self): - settings = CarlaSettings() - settings.add_sensor(Lidar('DefaultLidar')) - self.run_carla_client(settings, 3, 100) - - -class SpeedLowQuality(_BasicTestBase): - def run(self): - settings = CarlaSettings(QualityLevel='Low') - settings.add_sensor(Lidar('DefaultLidar')) - settings.add_sensor(Camera('DefaultCamera')) - settings.add_sensor(Camera('DefaultDepth', PostProcessing='Depth')) - settings.add_sensor(Camera('DefaultSemSeg', PostProcessing='SemanticSegmentation')) - self.run_carla_client(settings, 3, 200) diff --git a/Deprecated/PythonClient/test/suite/__init__.py b/Deprecated/PythonClient/test/suite/__init__.py deleted file mode 100644 index 2531e433f..000000000 --- a/Deprecated/PythonClient/test/suite/__init__.py +++ /dev/null @@ -1,10 +0,0 @@ -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - - -class CarlaServerTest(object): - def __init__(self, args): - self.args = args diff --git a/Deprecated/PythonClient/test/test_client.py b/Deprecated/PythonClient/test/test_client.py deleted file mode 100755 index e5fcd2a01..000000000 --- a/Deprecated/PythonClient/test/test_client.py +++ /dev/null @@ -1,186 +0,0 @@ -#!/usr/bin/env python3 - -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""A CARLA client for testing.""" - -import argparse -import logging -import os -import random -import sys -import time - -sys.path.append(os.path.join(os.path.dirname(__file__), '..')) - -import carla - -from carla import sensor -from carla.client import CarlaClient -from carla.settings import CarlaSettings -from carla.tcp import TCPClient -from carla.util import make_connection - -import console - - -def run_carla_client(args): - with make_connection(CarlaClient, args.host, args.port, timeout=15) as client: - logging.info('CarlaClient connected') - filename = '_out/test_episode_{:0>4d}/{:s}/{:0>6d}' - frames_per_episode = 300 - episode = 0 - while True: - episode += 1 - settings = CarlaSettings() - settings.set(SendNonPlayerAgentsInfo=True, SynchronousMode=args.synchronous) - settings.randomize_seeds() - camera = sensor.Camera('DefaultCamera') - camera.set_image_size(300, 200) # Do not change this, hard-coded in test. - settings.add_sensor(camera) - lidar = sensor.Lidar('DefaultLidar') - settings.add_sensor(lidar) - - logging.debug('sending CarlaSettings:\n%s', settings) - logging.info('new episode requested') - - scene = client.load_settings(settings) - - number_of_player_starts = len(scene.player_start_spots) - player_start = random.randint(0, max(0, number_of_player_starts - 1)) - logging.info( - 'start episode at %d/%d player start (%d frames)', - player_start, - number_of_player_starts, - frames_per_episode) - - client.start_episode(player_start) - - use_autopilot_control = (random.random() < 0.5) - reverse = (random.random() < 0.2) - - for frame in range(0, frames_per_episode): - logging.debug('reading measurements...') - measurements, sensor_data = client.read_data() - images = [x for x in sensor_data.values() if isinstance(x, sensor.Image)] - - logging.debug('received data of %d agents', len(measurements.non_player_agents)) - if len(images) > 0: - assert (images[0].width, images[0].height) == (camera.ImageSizeX, camera.ImageSizeY) - - if args.images_to_disk: - for name, data in sensor_data.items(): - data.save_to_disk(filename.format(episode, name, frame)) - - logging.debug('sending control...') - control = measurements.player_measurements.autopilot_control - if not use_autopilot_control: - control.steer = random.uniform(-1.0, 1.0) - control.throttle = 0.3 - control.hand_brake = False - control.reverse = reverse - client.send_control( - steer=control.steer, - throttle=control.throttle, - brake=control.brake, - hand_brake=control.hand_brake, - reverse=control.reverse) - - -def main(): - argparser = argparse.ArgumentParser(description=__doc__) - argparser.add_argument( - '-v', '--verbose', - action='store_true', - dest='debug', - help='print debug information') - argparser.add_argument( - '--log', - metavar='LOG_FILE', - default=None, - help='print output to file') - argparser.add_argument( - '--host', - metavar='H', - default='127.0.0.1', - help='IP of the host server (default: 127.0.0.1)') - argparser.add_argument( - '-p', '--port', - metavar='P', - default=2000, - type=int, - help='TCP port to listen to (default: 2000)') - argparser.add_argument( - '-s', '--synchronous', - action='store_true', - help='enable synchronous mode') - argparser.add_argument( - '-i', '--images-to-disk', - action='store_true', - help='save images to disk') - argparser.add_argument( - '--echo', - action='store_true', - help='start a client that just echoes what the server sends') - argparser.add_argument( - '-c', '--console', - action='store_true', - help='start the client console') - - args = argparser.parse_args() - - name = 'echo_client: ' if args.echo else 'carla_client: ' - logging_config = { - 'format': name + '%(levelname)s: %(message)s', - 'level': logging.DEBUG if args.debug else logging.INFO - } - if args.log: - logging_config['filename'] = args.log - logging_config['filemode'] = 'w+' - logging.basicConfig(**logging_config) - - logging.info('listening to server %s:%s', args.host, args.port) - - if args.console: - cmd = console.CarlaClientConsole(args) - try: - cmd.cmdloop() - finally: - cmd.cleanup() - return - - while True: - try: - - if args.echo: - - with make_connection(TCPClient, args.host, args.port, timeout=15) as client: - while True: - logging.info('reading...') - data = client.read() - if not data: - raise RuntimeError('failed to read data from server') - logging.info('writing...') - client.write(data) - - else: - - run_carla_client(args) - - except AssertionError as assertion: - raise assertion - except Exception as exception: - logging.error('exception: %s', exception) - time.sleep(1) - - -if __name__ == '__main__': - - try: - main() - except KeyboardInterrupt: - print('\nCancelled by user. Bye!') diff --git a/Deprecated/PythonClient/test/test_repeatability.py b/Deprecated/PythonClient/test/test_repeatability.py deleted file mode 100755 index a37d83a3c..000000000 --- a/Deprecated/PythonClient/test/test_repeatability.py +++ /dev/null @@ -1,168 +0,0 @@ -#!/usr/bin/env python3 - -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB), and the INTEL Visual Computing Lab. -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""Client that runs two servers simultaneously to test repeatability.""" - -import argparse -import logging -import os -import random -import sys -import time - -sys.path.append(os.path.join(os.path.dirname(__file__), '..')) - -from carla.client import make_carla_client -from carla.sensor import Camera, Image -from carla.settings import CarlaSettings -from carla.tcp import TCPConnectionError - - -def run_carla_clients(args): - filename = '_images_repeatability/server{:d}/{:0>6d}.png' - with make_carla_client(args.host1, args.port1) as client1: - logging.info('1st client connected') - with make_carla_client(args.host2, args.port2) as client2: - logging.info('2nd client connected') - - settings = CarlaSettings() - settings.set( - SynchronousMode=True, - SendNonPlayerAgentsInfo=True, - NumberOfVehicles=50, - NumberOfPedestrians=50, - WeatherId=random.choice([1, 3, 7, 8, 14])) - settings.randomize_seeds() - - if args.images_to_disk: - camera = Camera('DefaultCamera') - camera.set_image_size(800, 600) - settings.add_sensor(camera) - - scene1 = client1.load_settings(settings) - scene2 = client2.load_settings(settings) - - number_of_player_starts = len(scene1.player_start_spots) - assert number_of_player_starts == len(scene2.player_start_spots) - player_start = random.randint(0, max(0, number_of_player_starts - 1)) - logging.info( - 'start episode at %d/%d player start (run forever, press ctrl+c to cancel)', - player_start, - number_of_player_starts) - - client1.start_episode(player_start) - client2.start_episode(player_start) - - frame = 0 - while True: - frame += 1 - - meas1, sensor_data1 = client1.read_data() - meas2, sensor_data2 = client2.read_data() - - player1 = meas1.player_measurements - player2 = meas2.player_measurements - - images1 = [x for x in sensor_data1.values() if isinstance(x, Image)] - images2 = [x for x in sensor_data2.values() if isinstance(x, Image)] - - control1 = player1.autopilot_control - control2 = player2.autopilot_control - - try: - assert len(images1) == len(images2) - assert len(meas1.non_player_agents) == len(meas2.non_player_agents) - assert player1.transform.location.x == player2.transform.location.x - assert player1.transform.location.y == player2.transform.location.y - assert player1.transform.location.z == player2.transform.location.z - assert control1.steer == control2.steer - assert control1.throttle == control2.throttle - assert control1.brake == control2.brake - assert control1.hand_brake == control2.hand_brake - assert control1.reverse == control2.reverse - except AssertionError: - logging.exception('assertion failed') - - if args.images_to_disk: - assert len(images1) == 1 - images1[0].save_to_disk(filename.format(1, frame)) - images2[0].save_to_disk(filename.format(2, frame)) - - client1.send_control(control1) - client2.send_control(control2) - - -def main(): - argparser = argparse.ArgumentParser(description=__doc__) - argparser.add_argument( - '-v', '--verbose', - action='store_true', - dest='debug', - help='print debug information') - argparser.add_argument( - '--log', - metavar='LOG_FILE', - default=None, - help='print output to file') - argparser.add_argument( - '--host1', - metavar='H', - default='127.0.0.1', - help='IP of the first host server (default: 127.0.0.1)') - argparser.add_argument( - '-p1', '--port1', - metavar='P', - default=2000, - type=int, - help='TCP port to listen to the first server (default: 2000)') - argparser.add_argument( - '--host2', - metavar='H', - default='127.0.0.1', - help='IP of the second host server (default: 127.0.0.1)') - argparser.add_argument( - '-p2', '--port2', - metavar='P', - default=3000, - type=int, - help='TCP port to listen to the second server (default: 3000)') - argparser.add_argument( - '-i', '--images-to-disk', - action='store_true', - help='save images to disk') - - args = argparser.parse_args() - - logging_config = { - 'format': '%(levelname)s: %(message)s', - 'level': logging.DEBUG if args.debug else logging.INFO - } - if args.log: - logging_config['filename'] = args.log - logging_config['filemode'] = 'w+' - logging.basicConfig(**logging_config) - - logging.info('listening to 1st server at %s:%s', args.host1, args.port1) - logging.info('listening to 2nd server at %s:%s', args.host2, args.port2) - - while True: - try: - - run_carla_clients(args) - - except TCPConnectionError as error: - logging.error(error) - time.sleep(1) - - -if __name__ == '__main__': - - try: - main() - except KeyboardInterrupt: - print('\nCancelled by user. Bye!') diff --git a/Deprecated/PythonClient/test/test_suite.py b/Deprecated/PythonClient/test/test_suite.py deleted file mode 100755 index 0e544f16b..000000000 --- a/Deprecated/PythonClient/test/test_suite.py +++ /dev/null @@ -1,191 +0,0 @@ -#!/usr/bin/env python3 - -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""Test suite for testing CARLAUE4.""" - -import argparse -import glob -import imp -import inspect -import logging -import os -import random -import sys -import time - -sys.path.append(os.path.join(os.path.dirname(__file__), '..')) -sys.path.append(os.path.join(os.path.dirname(__file__), '.')) - -import carla - -from carla.tcp import TCPConnectionError -from carla.util import StopWatch - -from suite import CarlaServerTest - -# Modified by command-line args. -LOGGING_TO_FILE = False - -# Output. -GREEN = '\x1b[0;32m%s\x1b[0m' -YELLOW = '\x1b[0;33m%s\x1b[0m' -RED = '\x1b[0;31m%s\x1b[0m' - -SEP0 = GREEN % '[==========]' -SEP1 = GREEN % '[----------]' -RUN = GREEN % '[ RUN ]' -OK = GREEN % '[ OK ]' -PASSED = GREEN % '[ PASSED ]' -FAILED = RED % '[EXCEPTION ]' -FAILED = RED % '[ FAILED ]' - - -def log_test(prep, message, *args): - message = prep + ' ' + message % args - print(message) - if LOGGING_TO_FILE: - logging.info(message) - - -class TestProxy(object): - def __init__(self, name, declaration, module_name): - self.name = module_name + '.' + name - self.declaration = declaration - self.instance = None - - def instantiate(self, *args, **kwargs): - self.instance = self.declaration(*args, **kwargs) - - def run(self, *args, **kwargs): - if not hasattr(self.instance, 'run'): - logging.error('%s: "run" method should be implemented in derived class', self.name) - return False - result = self.instance.run(*args, **kwargs) - return True if result is None else result - - -def iterate_tests(): - interface = CarlaServerTest - strip_ext = lambda f: os.path.splitext(os.path.basename(f))[0] - is_valid = lambda obj: inspect.isclass(obj) and issubclass(obj, interface) - - folder = os.path.join(os.path.dirname(__file__), 'suite') - modules = glob.glob(os.path.join(folder, "*.py")) - - for module_name in set(strip_ext(m) for m in modules if not m.startswith('_')): - logging.debug('parsing module %r', module_name) - try: - module_info = imp.find_module(module_name, [folder]) - # This do a reload if already imported. - module = imp.load_module(module_name, *module_info) - for name, declaration in inspect.getmembers(module, is_valid): - if not name.startswith('_'): - yield TestProxy(name, declaration, module_name) - except Exception as exception: - logging.error('failed to load module %r: %s', module_name, exception) - finally: - module_info[0].close() - - -def run_test(test, args): - log_test(SEP1, 'Instantiating %s', test.name) - try: - test.instantiate(args) - except Exception as exception: - logging.error('exception instantiating %r: %s', test.name, exception) - return False - log_test(RUN, test.name) - while True: - try: - timer = StopWatch() - result = test.run() - timer.stop() - break - except TCPConnectionError as error: - logging.error(error) - time.sleep(1) - except Exception as exception: - timer.stop() - logging.exception('exception: %s', exception) - result = False - break - log_test(OK if result else FAILED, '%s (%d ms)', test.name, timer.milliseconds()) - return result - - -def do_the_tests(args): - tests = [t for t in iterate_tests()] - random.shuffle(tests) - succeeded = [] - failed = [] - log_test(SEP0, 'Running %d tests.', len(tests)) - for test in tests: - if run_test(test, args): - succeeded.append(test) - else: - failed.append(test) - log_test(SEP0, '%d tests ran.', len(tests)) - if succeeded: - log_test(PASSED, '%d tests.', len(succeeded)) - if failed: - log_test(FAILED, '%d tests.', len(failed)) - for test in failed: - log_test(FAILED, test.name) - return True - - -def main(): - argparser = argparse.ArgumentParser(description=__doc__) - argparser.add_argument( - '-v', '--verbose', - action='store_true', - dest='debug', - help='print debug information') - argparser.add_argument( - '--log', - metavar='LOG_FILE', - default=None, - help='print output to file') - argparser.add_argument( - '--host', - metavar='H', - default='127.0.0.1', - help='IP of the host server (default: 127.0.0.1)') - argparser.add_argument( - '-p', '--port', - metavar='P', - default=2000, - type=int, - help='TCP port to listen to (default: 2000)') - - args = argparser.parse_args() - - global LOGGING_TO_FILE - LOGGING_TO_FILE = args.log is not None - - logging_config = { - 'format': '%(levelname)s: %(message)s', - 'level': logging.DEBUG if args.debug else logging.INFO - } - if args.log: - logging_config['filename'] = args.log - logging_config['filemode'] = 'w+' - logging.basicConfig(**logging_config) - - logging.info('listening to server %s:%s', args.host, args.port) - - print('Running the CARLAUE4 test suite (looks like GTest but it\'s not).') - do_the_tests(args) - - -if __name__ == '__main__': - - try: - main() - except KeyboardInterrupt: - print('\nCancelled by user. Bye!') diff --git a/Deprecated/PythonClient/test/unit_tests/test_data/testfile_collisions/measurements.csv b/Deprecated/PythonClient/test/unit_tests/test_data/testfile_collisions/measurements.csv deleted file mode 100644 index de2071eb9..000000000 --- a/Deprecated/PythonClient/test/unit_tests/test_data/testfile_collisions/measurements.csv +++ /dev/null @@ -1,3211 +0,0 @@ -intersection_offroad,collision_other,collision_pedestrians,weather,brake,exp_id,collision_vehicles,pos_x,pos_y,intersection_otherlane,end_point,rep,throttle,start_point,steer -0.0,0.0,0.0,3,0.0,3,0.0,122.2798080444336,326.1367492675781,0.0,29,0,0.8999999761581421,105,0.0 -0.0,0.0,0.0,3,0.0,3,6267.859375,121.46373748779297,326.0997619628906,0.0,29,0,0.8999999761581421,105,0.0 -0.0,0.0,0.0,3,0.0,3,6267.859375,120.96914672851562,326.058837890625,0.0,29,0,0.8999999761581421,105,0.0 -0.0,0.0,0.0,3,0.0,3,6267.859375,120.45499420166016,326.02978515625,0.0,29,0,0.8999999761581421,105,0.0 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b/Deprecated/PythonClient/test/unit_tests/test_data/testfile_collisions/summary.csv deleted file mode 100644 index bf1cd06ed..000000000 --- a/Deprecated/PythonClient/test/unit_tests/test_data/testfile_collisions/summary.csv +++ /dev/null @@ -1,3 +0,0 @@ -weather,time_out,result,final_time,end_point,final_distance,exp_id,rep,start_point,initial_distance -3,335314,0,335314,29,171.3219381575824,3,0,105,280.44944447968976 -3,243.6346,0,243.6346,130,215.56398248559435,3,0,27,174.94691018267446 \ No newline at end of file diff --git a/Deprecated/PythonClient/test/unit_tests/test_experiment_suite.py b/Deprecated/PythonClient/test/unit_tests/test_experiment_suite.py deleted file mode 100644 index c0560d9cf..000000000 --- a/Deprecated/PythonClient/test/unit_tests/test_experiment_suite.py +++ /dev/null @@ -1,26 +0,0 @@ -import unittest -from carla.driving_benchmark.experiment_suites.experiment_suite import ExperimentSuite - -from carla.driving_benchmark.experiment_suites.basic_experiment_suite import BasicExperimentSuite - -from carla.driving_benchmark.experiment_suites.corl_2017 import CoRL2017 - -class testExperimentSuite(unittest.TestCase): - - - def test_init(self): - - base_class = ExperimentSuite('Town01') - subclasses_instanciate = [obj('Town01') for obj in ExperimentSuite.__subclasses__()] - - - def test_properties(self): - - all_classes = [obj('Town01') for obj in ExperimentSuite.__subclasses__()] - print (all_classes) - for exp_suite in all_classes: - print(exp_suite.__class__) - print(exp_suite.dynamic_tasks) - print(exp_suite.weathers) - - diff --git a/Deprecated/PythonClient/test/unit_tests/test_metrics.py b/Deprecated/PythonClient/test/unit_tests/test_metrics.py deleted file mode 100644 index bad694547..000000000 --- a/Deprecated/PythonClient/test/unit_tests/test_metrics.py +++ /dev/null @@ -1,190 +0,0 @@ -import os -import numpy as np -import unittest -from carla.driving_benchmark.metrics import Metrics -from carla.driving_benchmark.recording import Recording - - - -def sum_matrix(matrix): - # Line trick to reduce sum a matrix in one line - return sum(sum(matrix, [])) - - -class testMetrics(unittest.TestCase): - - def __init__(self, *args, **kwargs): - super(testMetrics, self).__init__(*args, **kwargs) - - self._metrics_parameters = { - - 'intersection_offroad': {'frames_skip': 10, # Check intersection always with 10 frames tolerance - 'frames_recount': 20, - 'threshold': 0.3 - }, - 'intersection_otherlane': {'frames_skip': 10, # Check intersection always with 10 frames tolerance - 'frames_recount': 20, - 'threshold': 0.4 - }, - 'collision_other': {'frames_skip': 10, - 'frames_recount': 20, - 'threshold': 400 - }, - 'collision_vehicles': {'frames_skip': 10, - 'frames_recount': 30, - 'threshold': 400 - }, - 'collision_pedestrians': {'frames_skip': 5, - 'frames_recount': 100, - 'threshold': 300 - }, - 'dynamic_episodes': [3] - - } - - - - 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_init(self): - - # Metric should instantiate with parameters - Metrics(self._metrics_parameters,[3]) - - - - def test_divide_by_episodes(self): - - - metrics_obj = Metrics(self._metrics_parameters,[3]) - - poses_to_test = [[24, 32], [34, 36], [54, 67]] - path = self._generate_test_case(poses_to_test) - - # We start by reading the summary header file and the measurements header file. - with open(os.path.join(path, 'summary.csv'), "r") as f: - header = f.readline() - header = header.split(',') - header[-1] = header[-1][:-2] - - - - with open(os.path.join(path,'measurements.csv'), "r") as f: - - header_metrics = f.readline() - header_metrics = header_metrics.split(',') - header_metrics[-1] = header_metrics[-1][:-2] - - - result_matrix = np.loadtxt(os.path.join(path, 'summary.csv'), delimiter=",", skiprows=1) - - # Corner Case: The presented test just had one episode - if result_matrix.ndim == 1: - result_matrix = np.expand_dims(result_matrix, axis=0) - - - tasks = np.unique(result_matrix[:, header.index('exp_id')]) - - - all_weathers = np.unique(result_matrix[:, header.index('weather')]) - - measurements_matrix = np.loadtxt(os.path.join(path, 'measurements.csv'), delimiter=",", skiprows=1) - - - episodes = metrics_obj._divide_by_episodes(measurements_matrix,header_metrics) - - - self.assertEqual(len(episodes),3) - - - - def test_compute(self): - - # This is is the last one, generate many cases, corner cases, to be tested. - - metrics_obj = Metrics(self._metrics_parameters,[3]) - - - # Lets start testing a general file, not from a real run - # The case is basically an empty case - poses_to_test = [[24, 32], [34, 36], [54, 67]] - path = self._generate_test_case(poses_to_test) - - - - summary_dict = metrics_obj.compute(path) - - - number_of_colisions_vehicles = sum_matrix(summary_dict['collision_vehicles'][1.0]) - number_of_colisions_general = sum_matrix(summary_dict['collision_other'][1.0]) - number_of_colisions_pedestrians = sum_matrix(summary_dict['collision_pedestrians'][1.0]) - number_of_intersection_offroad = sum_matrix(summary_dict['intersection_offroad'][1.0]) - number_of_intersection_otherlane = sum_matrix(summary_dict['intersection_otherlane'][1.0]) - - - - self.assertEqual(number_of_colisions_vehicles, 0) - self.assertEqual(number_of_colisions_general, 0) - self.assertEqual(number_of_colisions_pedestrians, 0) - self.assertEqual(number_of_intersection_offroad, 0) - self.assertEqual(number_of_intersection_otherlane, 0) - - - # Now lets make a collision test on a premade file - - path = 'test/unit_tests/test_data/testfile_collisions' - - summary_dict = metrics_obj.compute(path) - - number_of_colisions_vehicles = sum_matrix(summary_dict['collision_vehicles'][3.0]) - number_of_colisions_general = sum_matrix(summary_dict['collision_other'][3.0]) - number_of_colisions_pedestrians = sum_matrix(summary_dict['collision_pedestrians'][3.0]) - number_of_intersection_offroad = sum_matrix(summary_dict['intersection_offroad'][3.0]) - number_of_intersection_otherlane = sum_matrix(summary_dict['intersection_otherlane'][3.0]) - - - - self.assertEqual(number_of_colisions_vehicles, 2) - self.assertEqual(number_of_colisions_general, 9) - self.assertEqual(number_of_colisions_pedestrians, 0) - self.assertEqual(number_of_intersection_offroad, 1) - self.assertEqual(number_of_intersection_otherlane, 3) - - - - - - - diff --git a/Deprecated/PythonClient/test/unit_tests/test_recording.py b/Deprecated/PythonClient/test/unit_tests/test_recording.py deleted file mode 100644 index 716c5ff57..000000000 --- a/Deprecated/PythonClient/test/unit_tests/test_recording.py +++ /dev/null @@ -1,254 +0,0 @@ -import os -import unittest -from carla.driving_benchmark.recording import Recording - - -class testRecording(unittest.TestCase): - - def test_init(self): - """ - The recording should have a reasonable full name - """ - - recording = Recording(name_to_save='Test1', - continue_experiment=False, save_images=True) - - _ = open(os.path.join(recording._path, 'summary.csv'), 'r') - _ = open(os.path.join(recording._path, 'measurements.csv'), 'r') - - # There should be three files in any newly created case - self.assertEqual(len(os.listdir(recording._path)), 3) - - 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 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) - - # Check if the the test_good_order summaries have all the same files. - - def test_write_measurements_results(self): - """ - Test writing a few measurements into the log - """ - - 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 _ in range(20)] - control_vec = [Control() for _ 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 test_continue_experiment(self): - """ - Test if you are able to continue an experiment after restarting the process - """ - 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 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 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) - - -if __name__ == '__main__': - unittest.main() diff --git a/Deprecated/PythonClient/view_start_positions.py b/Deprecated/PythonClient/view_start_positions.py deleted file mode 100755 index 629a79985..000000000 --- a/Deprecated/PythonClient/view_start_positions.py +++ /dev/null @@ -1,135 +0,0 @@ -#!/usr/bin/env python3 - -# Copyright (c) 2017 Computer Vision Center (CVC) at the Universitat Autonoma de -# Barcelona (UAB). -# -# This work is licensed under the terms of the MIT license. -# For a copy, see . - -"""Connects with a CARLA simulator and displays the available start positions -for the current map.""" - -from __future__ import print_function - -import argparse -import logging -import sys -import time - -import matplotlib.image as mpimg -import matplotlib.pyplot as plt - -from matplotlib.patches import Circle - -from carla.client import make_carla_client -from carla.planner.map import CarlaMap -from carla.settings import CarlaSettings -from carla.tcp import TCPConnectionError - - -def view_start_positions(args): - # We assume the CARLA server is already waiting for a client to connect at - # host:port. The same way as in the client example. - with make_carla_client(args.host, args.port) as client: - print('CarlaClient connected') - - # We load the default settings to the client. - scene = client.load_settings(CarlaSettings()) - print("Received the start positions") - - try: - image = mpimg.imread('carla/planner/%s.png' % scene.map_name) - carla_map = CarlaMap(scene.map_name) - except IOError as exception: - logging.error(exception) - logging.error('Cannot find map "%s"', scene.map_name) - sys.exit(1) - - fig, ax = plt.subplots(1) - - ax.imshow(image) - - if args.positions == 'all': - positions_to_plot = range(len(scene.player_start_spots)) - else: - positions_to_plot = map(int, args.positions.split(',')) - - for position in positions_to_plot: - # Check if position is valid - if position >= len(scene.player_start_spots): - raise RuntimeError('Selected position is invalid') - - # Convert world to pixel coordinates - pixel = carla_map.convert_to_pixel([scene.player_start_spots[position].location.x, - scene.player_start_spots[position].location.y, - scene.player_start_spots[position].location.z]) - - circle = Circle((pixel[0], pixel[1]), 12, color='r', label='A point') - ax.add_patch(circle) - - if not args.no_labels: - plt.text(pixel[0], pixel[1], str(position), size='x-small') - - plt.axis('off') - plt.show() - - fig.savefig('town_positions.pdf', orientation='landscape', bbox_inches='tight') - - -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( - '-pos', '--positions', - metavar='P', - default='all', - help='Indices of the positions that you want to plot on the map. ' - 'The indices must be separated by commas (default = all positions)') - argparser.add_argument( - '--no-labels', - action='store_true', - help='do not display position indices') - - 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) - - while True: - try: - - view_start_positions(args) - print('Done.') - return - - except TCPConnectionError as error: - logging.error(error) - time.sleep(1) - except RuntimeError as error: - logging.error(error) - break - - -if __name__ == '__main__': - - try: - main() - except KeyboardInterrupt: - print('\nCancelled by user. Bye!')