def process_images(self, simulator_image):
""" Invoked when an image is received from the simulator.
Args:
simulator_image: a carla.Image.
"""
game_time = int(simulator_image.timestamp * 1000)
timestamp = erdos.Timestamp(coordinates=[game_time])
watermark_msg = erdos.WatermarkMessage(timestamp)
with erdos.profile(self.config.name + '.process_images',
self,
event_data={'timestamp': str(timestamp)}):
# Ensure that the code executes serially
with self._lock:
msg = None
if self._camera_setup.camera_type == 'sensor.camera.rgb':
msg = FrameMessage(
timestamp,
CameraFrame.from_simulator_frame(
simulator_image, self._camera_setup))
elif self._camera_setup.camera_type == 'sensor.camera.depth':
# Include the transform relative to the vehicle.
# simulator_image.transform returns the world transform,
# but we do not use it directly.
msg = DepthFrameMessage(
timestamp,
DepthFrame.from_simulator_frame(
simulator_image,
self._camera_setup,
save_original_frame=self._flags.
visualize_depth_camera))
elif (self._camera_setup.camera_type ==
'sensor.camera.semantic_segmentation'):
msg = SegmentedFrameMessage(
timestamp,
SegmentedFrame.from_simulator_image(
simulator_image, self._camera_setup))
if self._release_data:
self._camera_stream.send(msg)
self._camera_stream.send(watermark_msg)
else:
# Pickle the data, and release it upon release msg receipt.
pickled_msg = pickle.dumps(
msg, protocol=pickle.HIGHEST_PROTOCOL)
with self._pickle_lock:
self._pickled_messages[msg.timestamp] = pickled_msg
self._notify_reading_stream.send(watermark_msg)
def on_camera_frame(self, data):
self._counter += 1
if self._counter % self._modulo_to_send != 0:
return
cv2_image = self._bridge.imgmsg_to_cv2(data, "bgr8")
resized_image = cv2.resize(
cv2.flip(cv2_image, -1),
(self._flags.camera_image_width, self._flags.camera_image_height))
numpy_array = np.asarray(resized_image)
timestamp = erdos.Timestamp(coordinates=[self._msg_cnt])
camera_frame = CameraFrame(numpy_array, 'BGR', self._camera_setup)
self._camera_stream.send(FrameMessage(timestamp, camera_frame))
watermark_msg = erdos.WatermarkMessage(timestamp)
self._camera_stream.send(watermark_msg)
self._logger.debug('@{}: sent message'.format(timestamp))
self._msg_cnt += 1
def process_images(self, carla_image):
""" Invoked when an image is received from the simulator.
Args:
carla_image: a carla.Image.
"""
# Ensure that the code executes serially
with self._lock:
game_time = int(carla_image.timestamp * 1000)
timestamp = erdos.Timestamp(coordinates=[game_time])
watermark_msg = erdos.WatermarkMessage(timestamp)
msg = None
if self._camera_setup.camera_type == 'sensor.camera.rgb':
msg = FrameMessage(
timestamp,
CameraFrame.from_carla_frame(carla_image,
self._camera_setup))
elif self._camera_setup.camera_type == 'sensor.camera.depth':
# Include the transform relative to the vehicle.
# Carla carla_image.transform returns the world transform, but
# we do not use it directly.
msg = DepthFrameMessage(
timestamp,
DepthFrame.from_carla_frame(carla_image,
self._camera_setup))
elif self._camera_setup.camera_type == \
'sensor.camera.semantic_segmentation':
msg = SegmentedFrameMessage(
timestamp,
SegmentedFrame.from_carla_image(carla_image,
self._camera_setup))
# Send the message containing the frame.
self._camera_stream.send(msg)
# Note: The operator is set not to automatically propagate
# watermark messages received on input streams. Thus, we can
# issue watermarks only after the Carla callback is invoked.
self._camera_stream.send(watermark_msg)
def on_camera_msg(carla_image):
game_time = int(carla_image.timestamp * 1000)
print("Received camera msg {}".format(game_time))
global last_frame
last_frame = FrameMessage(carla_image, game_time, encoding='carla')