class ObstacleDetector(Node):
_node_config_section = "OBSTACLE_DETECTOR"
def __init__(self):
super().__init__(self._node_config_section)
# Node method implementations
def _start_up(self):
self._obstacle_distance_estimator = ObstacleDistanceEstimator()
self._obstacle_detector_sender = Sender(self._node_config_section)
self._sensor_input_camera = ReadCamera()
self._darknet_wrapper = DarknetWrapper()
def _progress(self):
frame_read = self._sensor_input_camera.get_frame()
detected_obstacles: List[
DetectedObject] = self._darknet_wrapper.detect_obstacles(
frame_read)
for detected_obstacle in detected_obstacles:
detected_obstacle.distance = self._obstacle_distance_estimator.estimate(
detected_obstacle.bounding_box.height)
obstacle_detector_result = ObstacleDetectorResult(detected_obstacles)
self._obstacle_detector_sender.send(obstacle_detector_result)
def _shut_down(self):
self._obstacle_detector_sender.close()
class PylonDetector(Node):
_node_config_section = "PYLON_DETECTOR"
def __init__(self):
super().__init__(self._node_config_section)
self._pylon_distance_estimator = PylonDistanceEstimator()
self._sensor_input_camera = ReadCamera()
self._darknet_wrapper = DarknetWrapper()
# Node method implementations
def _start_up(self):
self._pylon_detector_sender = Sender(self._node_config_section)
def _progress(self):
frame_read = self._sensor_input_camera.get_frame()
detected_pylons: List[
DetectedObject] = self._darknet_wrapper.detect_pylons(frame_read)
for detected_pylon in detected_pylons:
detected_pylon.bounding_box = PylonBoundingBoxAdjuster(
frame_read).adjust(detected_pylon.bounding_box)
detected_pylon.distance = self._pylon_distance_estimator.estimate(
detected_pylon.bounding_box.width)
self._pylon_detector_sender.send(PylonDetectorResult(detected_pylons))
def _shut_down(self):
self._pylon_detector_sender.close()
def _start_up(self):
self._obstacle_distance_estimator = ObstacleDistanceEstimator()
self._obstacle_detector_sender = Sender(self._node_config_section)
self._sensor_input_camera = ReadCamera()
self._darknet_wrapper = DarknetWrapper()
def __init__(self):
super().__init__(self._node_config_section)
self._sensor_input_camera = ReadCamera()
class NomadVisualizer(Node):
_node_config_section = "VISUALIZER"
_LOWER_RED_MIN = np.array([0, 100, 100], np.uint8)
_LOWER_RED_MAX = np.array([10, 255, 255], np.uint8)
_UPPER_RED_MIN = np.array([160, 100, 100], np.uint8)
_UPPER_RED_MAX = np.array([179, 255, 255], np.uint8)
def __init__(self):
super().__init__(self._node_config_section)
self._sensor_input_camera = ReadCamera()
def _start_up(self):
self.fake_objectresult_reader: FakeDataReader = FakeDataReader("objectresult")
self._steering_detector_receiver = Receiver("STEERING_COMMAND_GENERATOR")
self._fake_sonar = ReadSonar()
self._fake_imu = ReadIMU()
def _progress(self):
frame_read = self._sensor_input_camera.get_frame()
pickle_in = open(self.fake_objectresult_reader.getNextFilePath(), "rb")
object_detector_result: ObjectDetectorResult = pickle.load(pickle_in)
steering_command_generator_result: SteeringCommandGeneratorResult = self._steering_detector_receiver.receive()
sonar_data: SonarData = self._fake_sonar.get_Data()
imu_data: IMUData = self._fake_imu.get_Data()
draw_detected_objects(frame_read, object_detector_result.get_detected_objects)
# draw camera center range on image
camera_center_range = ObjectDetector.load_camera_center_range()
min_point = (int(camera_center_range.min_x), int(camera_center_range.min_y))
max_point = (int(camera_center_range.max_x), int(camera_center_range.max_y))
# cv2.rectangle(frame_read, min_point, max_point, (255, 0, 0), 1)
# draw ultrasonic information
cv2.putText(frame_read, "Ultrasonic Top: " + str(sonar_data.distance_top),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 20),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "Ultrasonic Bottom: " + str(sonar_data.distance_bottom),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 5),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
# draw imu information
cv2.putText(frame_read, "Accel x: " + str(imu_data.acc_x),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 120),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "Accel y: " + str(imu_data.acc_y),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 105),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "Accel z: " + str(imu_data.acc_z),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 90),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "Gyro x: " + str(imu_data.gyro_x),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 75),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "Gyro y: " + str(imu_data.gyro_y),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 60),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "Gyro z: " + str(imu_data.gyro_z),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 45),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "state: " + str(steering_command_generator_result.state),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 210),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "velocity m/s: " + str(steering_command_generator_result.velocity_meters_per_second),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 195),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "steering angel: " + str(steering_command_generator_result.steering_angel),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 180),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "driving direction: " + str(steering_command_generator_result.driving_direction),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 165),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "curve radius centimeters: " + str(steering_command_generator_result.curve_radius_centimeters),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 150),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, [255, 0, 0], 2)
cv2.imshow('NOMAD_Visualizer', frame_read)
cv2.waitKey(3)
def _shut_down(self):
self._steering_detector_receiver.close()
def __init__(self):
super().__init__(self._node_config_section)
self._pylon_distance_estimator = PylonDistanceEstimator()
self._sensor_input_camera = ReadCamera()
self._darknet_wrapper = DarknetWrapper()
class ObjectDetectorVisualizer(Node):
_node_config_section = "VISUALIZER"
_LOWER_RED_MIN = np.array([0, 100, 100], np.uint8)
_LOWER_RED_MAX = np.array([10, 255, 255], np.uint8)
_UPPER_RED_MIN = np.array([160, 100, 100], np.uint8)
_UPPER_RED_MAX = np.array([179, 255, 255], np.uint8)
def __init__(self):
super().__init__(self._node_config_section)
self._sensor_input_camera = ReadCamera()
def _start_up(self):
self._object_detector_receiver = Receiver("OBJECT_DETECTOR")
self._fake_sonar = ReadSonar()
self._fake_imu = ReadIMU()
def _progress(self):
frame_read = self._sensor_input_camera.get_frame()
object_detector_result = self._object_detector_receiver.receive()
sonar_data: SonarData = self._fake_sonar.get_Data()
imu_data: IMUData = self._fake_imu.get_Data()
draw_detected_objects(frame_read,
object_detector_result.get_detected_objects)
# draw camera center range on image
camera_center_range = ObjectDetector.load_camera_center_range()
min_point = (int(camera_center_range.min_x),
int(camera_center_range.min_y))
max_point = (int(camera_center_range.max_x),
int(camera_center_range.max_y))
# cv2.rectangle(frame_read, min_point, max_point, (255, 0, 0), 1)
# draw ultrasonic information
cv2.putText(frame_read,
"Ultrasonic Top: " + str(sonar_data.distance_top),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, [255, 0, 0], 2)
cv2.putText(frame_read,
"Ultrasonic Bottom: " + str(sonar_data.distance_bottom),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 15),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, [255, 0, 0], 2)
# draw imu information
cv2.putText(frame_read, "Accel x: " + str(imu_data.acc_x),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 120),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "Accel y: " + str(imu_data.acc_y),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 105),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "Accel z: " + str(imu_data.acc_z),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 90),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "Gyro x: " + str(imu_data.gyro_x),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 75),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "Gyro y: " + str(imu_data.gyro_y),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 60),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, [255, 0, 0], 2)
cv2.putText(frame_read, "Gyro z: " + str(imu_data.gyro_z),
(int(camera_center_range.max_x) - 200,
int(camera_center_range.max_y) - 45),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, [255, 0, 0], 2)
cv2.imshow('Pylon_Detector_Visualizer', frame_read)
cv2.waitKey(3)
def _shut_down(self):
self._object_detector_receiver.close()