Merge pull request #245 from JdeRobot/issue-244

Removed camera deviation calculation

behavior_metrics/brains/f1/brain_f1_explicit.py

@@ -15,7 +15,6 @@ def __init__(self, sensors, actuators, handler, config=None):
 
         self.x_middle_left_above = 0
         self.deviation_left = 0
-        self.camera_deviation_error = []
         # self.iteration = 0
         # self.json_data = []
         self.lock = threading.Lock()
@@ -142,8 +141,6 @@ def execute(self):
             x_middle_left_down, not_found_down = self.check_center(position_x_down)
             x_middle_left_middle, not_found_middle = self.check_center(position_x_middle)
 
-            self.camera_deviation_error.append(abs(326 - x_middle_left_down) if not_found_down is False else 500)
-
             # We look if white pixels of the row above are located
             if (len(position_x_above[0]) > 1):
                 self.x_middle_left_above = (position_x_above[0][0] + position_x_above[0][

behavior_metrics/brains/f1/brain_f1_keras.py

@@ -44,7 +44,6 @@ def __init__(self, sensors, actuators, model=None, handler=None, config=None):
         self.cont = 0
         self.inference_times = []
         self.config = config
-        self.camera_deviation_error = []
 
         if self.config['GPU'] is False:
             os.environ["CUDA_VISIBLE_DEVICES"]="-1"
@@ -89,38 +88,6 @@ def get_point(self, index, img):
             mid = np.abs(left - right) / 2 + left
         return int(mid)
 
-    def get_camera_deviation_error(self, image_cropped):
-        image_hsv = cv2.cvtColor(image_cropped, cv2.COLOR_RGB2HSV)
-        lower_red = np.array([0, 50, 50])
-        upper_red = np.array([180, 255, 255])
-        image_mask = cv2.inRange(image_hsv, lower_red, upper_red)
-
-        rows, cols = image_mask.shape
-        rows = rows - 1  # para evitar desbordamiento
-
-        alt = 0
-        ff = cv2.reduce(image_mask, 1, cv2.REDUCE_SUM, dtype=cv2.CV_32S)
-        if np.count_nonzero(ff[:, 0]) > 0:
-            alt = np.min(np.nonzero(ff[:, 0]))
-
-        points = []
-        for i in range(3):
-            if i == 0:
-                index = alt
-            else:
-                index = rows // (2 * i)
-            points.append((self.get_point(index, image_mask), index))
-
-        points.append((self.get_point(rows, image_mask), rows))
-
-        position_x_down = np.where(image_mask[points[3][1], :])
-
-        # We see that white pixels have been located and we look if the center is located
-        # In this way we can know if the car has left the circuit
-        x_middle_left_down, not_found_down = self.check_center(position_x_down)
-
-        return abs(326 - x_middle_left_down) if not_found_down is False else 500
-
     def execute(self):
         """Main loop of the brain. This will be called iteratively each TIME_CYCLE (see pilot.py)"""
 
@@ -142,8 +109,6 @@ def execute(self):
             else:
                 img = image
 
-            camera_deviation_error = self.get_devcamera_deviation_error(image)
-            self.camera_deviation_error.append(camera_deviation_error)
 
             if self.config['ImageNormalized']:
                 AUGMENTATIONS_TEST = Compose([

behavior_metrics/ui/gui/views/stats_window.py

@@ -15,8 +15,6 @@ def __init__(self, parent=None, controller=None):
         self.layout.addWidget(self.percentage_completed_label)
         self.completed_distance_label = QLabel("Completed distance -> " + str(self.controller.lap_statistics['completed_distance']) + "m")
         self.layout.addWidget(self.completed_distance_label)
-        self.camera_deviation_error_label = QLabel("Mean camera deviation -> " + str(sum(self.controller.metrics['camera_deviation_error'])/len(self.controller.metrics['camera_deviation_error'])))
-        self.layout.addWidget(self.camera_deviation_error_label)
 
         # If lap is completed, extend information
         if 'lap_seconds' in self.controller.lap_statistics:

behavior_metrics/utils/controller.py

@@ -206,7 +206,6 @@ def record_stats(self, perfect_lap_filename, stats_record_dir_path, world_counte
         self.stats_record_dir_path = stats_record_dir_path
         timestr = time.strftime("%Y%m%d-%H%M%S")
         self.stats_filename = timestr + '.bag'
-        self.pilot.brains.active_brain.camera_deviation_error = []
         topics = ['/F1ROS/odom', '/clock']
         command = "rosbag record -O " + self.stats_filename + " " + " ".join(topics) + " __name:=behav_stats_bag"
         command = shlex.split(command)
@@ -225,9 +224,6 @@ def stop_record_stats(self):
         # Wait for rosbag file to be closed. Otherwise it causes error
         while os.path.isfile(self.stats_filename + '.active'):
             pass
-
-        self.metrics['camera_deviation_error'] = self.pilot.brains.active_brain.camera_deviation_error
-        self.pilot.brains.active_brain.camera_deviation_error = []
 
         checkpoints = []
         metrics_str = json.dumps(self.metrics)