How to use the carla.sensor.Camera function in carla

def build_experiments(self):
        """
        Creates the whole set of experiment objects,
        The experiments created depend on the selected Town.


        """

        # We set the camera
        # This single RGB camera is used on every experiment

        camera = Camera('rgb')
        camera.set(FOV=100)
        camera.set_image_size(800, 600)
        camera.set_position(2.0, 0.0, 1.4)
        camera.set_rotation(-15.0, 0, 0)


        poses_tasks = self._poses()
        vehicles_tasks = [0, 15, 70]
        pedestrians_tasks = [0, 50, 150]

        task_names = ['empty', 'normal', 'cluttered']

        experiments_vector = []

        for weather in self.weathers:

def build_experiments(self):
        """
        Creates the whole set of experiment objects,
        The experiments created depend on the selected Town.
        """

        # We set the camera
        # This single RGB camera is used on every experiment

        camera = Camera('rgb')
        camera.set(FOV=100)
        camera.set_image_size(800, 600)
        camera.set_position(2.0, 0.0, 1.4)
        camera.set_rotation(-15.0, 0, 0)

        poses_tasks = self._poses()
        vehicles_tasks = [0]
        pedestrians_tasks = [250]

        experiments_vector = []

        for weather in self.weathers:

            for iteration in range(len(poses_tasks)):
                poses = poses_tasks[iteration]
                vehicles = vehicles_tasks[iteration]

'weathers_train': [1],
                   'weathers_validation': []

                   },
        'Town02': {'poses': _poses_town02(),
                   'vehicles': [15],
                   'pedestrians': [50],
                   'weathers_train': [],
                   'weathers_validation': [14]

                   }
    }

    # We set the camera
    # This single RGB camera is used on every experiment
    camera = Camera('rgb')
    camera.set(FOV=100)
    camera.set_image_size(800, 600)
    camera.set_position(2.0, 0.0, 1.4)
    camera.set_rotation(-15.0, 0, 0)
    sensor_set = [camera]

    return _build_experiments(exp_set_dict, sensor_set), exp_set_dict

# 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 centimeters.
        camera0.set_position(30, 0, 130)
        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(30, 0, 130)
        settings.add_sensor(camera1)

        camera2 = Camera('CameraSemanticSegmentation', PostProcessing='SemanticSegmentation')
        camera2.set_image_size(800, 600)
        camera2.set_position(30, 0, 130)
        settings.add_sensor(camera2)

        # 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 = 0  # 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

camera.set_position(2.0, 0, 1.4)
            camera.set_rotation(-15.0, 30, 0)
            settings.add_sensor(camera)

        # add a front facing depth camera
        if CameraTypes.DEPTH in cameras:
            camera = Camera(CameraTypes.DEPTH.value)
            camera.set_image_size(camera_width, camera_height)
            camera.set_position(0.2, 0, 1.3)
            camera.set_rotation(8, 30, 0)
            camera.PostProcessing = 'Depth'
            settings.add_sensor(camera)

        # add a front facing semantic segmentation camera
        if CameraTypes.SEGMENTATION in cameras:
            camera = Camera(CameraTypes.SEGMENTATION.value)
            camera.set_image_size(camera_width, camera_height)
            camera.set_position(0.2, 0, 1.3)
            camera.set_rotation(8, 30, 0)
            camera.PostProcessing = 'SemanticSegmentation'
            settings.add_sensor(camera)

        return settings

def default_settings():
    settings = CarlaSettings()
    settings.set(
        SynchronousMode=True,
        SendNonPlayerAgentsInfo=True,
        NumberOfVehicles=0,
        NumberOfPedestrians=0,
        WeatherId=1,  # random.choice([1, 3, 7, 8, 14]),
        PlayerVehicle='/Game/Blueprints/Vehicles/Mustang/Mustang.Mustang_C',
        QualityLevel='Epic')
    settings.randomize_seeds()

    camera_RGB = Camera('CameraRGB')
    camera_RGB.set_image_size(256, 256)
    camera_RGB.set_position(1, 0, 2.50)
    settings.add_sensor(camera_RGB)

    camera_seg = Camera('CameraSegmentation', PostProcessing='SemanticSegmentation')
    camera_seg.set_image_size(256, 256)
    camera_seg.set_position(1, 0, 2.50)
    settings.add_sensor(camera_seg)

    return settings

# 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(

print('CarlaClient connected')
        settings = CarlaSettings()
        settings.set(
            SynchronousMode=True,
            SendNonPlayerAgentsInfo=True,
            NumberOfVehicles=20,
            NumberOfPedestrians=0,
            WeatherId= 1)  # random.choice([1, 3, 7, 8, 14]))
        settings.randomize_seeds()

        camera0 = Camera('CameraRGB')
        camera0.set_image_size(800, 600)
        camera0.set_position(30, 0, 130)
        settings.add_sensor(camera0)

        camera1 = Camera('CameraDepth', PostProcessing='Depth')
        camera1.set_image_size(800, 600)
        camera1.set_position(30, 0, 130)
        settings.add_sensor(camera1)

        camera2 = Camera('CameraSemanticSegmentation', PostProcessing='SemanticSegmentation')
        camera2.set_image_size(800, 600)
        camera2.set_position(30, 0, 130)
        settings.add_sensor(camera2)

        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))

        print('Starting...')
        client.start_episode(player_start)

camera.set_position(2.0, 0, 1.4)
            camera.set_rotation(-15.0, 0, 0)
            settings.add_sensor(camera)

        # add a left facing camera
        if CameraTypes.LEFT in cameras:
            camera = Camera(CameraTypes.LEFT.value)
            camera.set(FOV=100)
            camera.set_image_size(camera_width, camera_height)
            camera.set_position(2.0, 0, 1.4)
            camera.set_rotation(-15.0, -30, 0)
            settings.add_sensor(camera)

        # add a right facing camera
        if CameraTypes.RIGHT in cameras:
            camera = Camera(CameraTypes.RIGHT.value)
            camera.set(FOV=100)
            camera.set_image_size(camera_width, camera_height)
            camera.set_position(2.0, 0, 1.4)
            camera.set_rotation(-15.0, 30, 0)
            settings.add_sensor(camera)

        # add a front facing depth camera
        if CameraTypes.DEPTH in cameras:
            camera = Camera(CameraTypes.DEPTH.value)
            camera.set_image_size(camera_width, camera_height)
            camera.set_position(0.2, 0, 1.3)
            camera.set_rotation(8, 30, 0)
            camera.PostProcessing = 'Depth'
            settings.add_sensor(camera)

        # add a front facing semantic segmentation camera

NumberOfVehicles=0,
            NumberOfPedestrians=0,
            WeatherId=1)  # random.choice([1, 3, 7, 8, 14]))
        settings.randomize_seeds()

        camera0 = Camera('CameraRGB')
        camera0.set_image_size(800, 600)
        camera0.set_position(30, 0, 130)
        settings.add_sensor(camera0)

        camera1 = Camera('CameraDepth', PostProcessing='Depth')
        camera1.set_image_size(800, 600)
        camera1.set_position(30, 0, 130)
        settings.add_sensor(camera1)

        camera2 = Camera('CameraSemanticSegmentation', PostProcessing='SemanticSegmentation')
        camera2.set_image_size(800, 600)
        camera2.set_position(30, 0, 130)
        settings.add_sensor(camera2)

        scene = client.load_settings(settings)

        number_of_player_starts = len(scene.player_start_spots)
        player_start = 1  # random.randint(0, max(0, number_of_player_starts - 1))

        print('Starting...')
        client.start_episode(player_start)

        if show_camera:
            plt.ion()
            plt.show()