Update controllers for new shapes and solve multiple experiments error

behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_70_km_h.py

@@ -134,7 +134,7 @@ def execute(self):
 
         self.update_pose(self.pose.getPose3d())
 
-        image_shape=(50, 150)
+        image_shape=(66, 200)
         img_base = cv2.resize(bird_eye_view_1, image_shape)
 
         AUGMENTATIONS_TEST = Compose([

behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_V_MAX_30.py

@@ -131,11 +131,10 @@ def execute(self):
 
         self.update_pose(self.pose.getPose3d())
 
-        image_shape=(50, 150)
+        image_shape=(66, 200)
         img_base = cv2.resize(bird_eye_view_1, image_shape)
 
         AUGMENTATIONS_TEST = Compose([
-            #ChannelDropout(p=1.0),
             Normalize()
         ])
         image = AUGMENTATIONS_TEST(image=img_base)

behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_broken_input.py

@@ -125,7 +125,7 @@ def execute(self):
         ]
 
         AUGMENTATIONS_TEST = Compose([
-            GridDropout(p=1.0, ratio=0.9)
+            GridDropout(p=1.0)
         ])
 
         bird_eye_view_1 = AUGMENTATIONS_TEST(image=bird_eye_view_1)
@@ -139,7 +139,7 @@ def execute(self):
 
         self.update_pose(self.pose.getPose3d())
 
-        image_shape=(50, 150)
+        image_shape=(66, 200)
         img_base = cv2.resize(bird_eye_view_1, image_shape)
 
         AUGMENTATIONS_TEST = Compose([

behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_broken_input_2.py

@@ -139,7 +139,7 @@ def execute(self):
 
         self.update_pose(self.pose.getPose3d())
 
-        image_shape=(50, 150)
+        image_shape=(66, 200)
         img_base = cv2.resize(bird_eye_view_1, image_shape)
 
         AUGMENTATIONS_TEST = Compose([

behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v.py

@@ -133,7 +133,7 @@ def execute(self):
 
         self.update_pose(self.pose.getPose3d())
 
-        image_shape=(50, 150)
+        image_shape=(66, 200)
         img_base = cv2.resize(bird_eye_view_1, image_shape)
 
         AUGMENTATIONS_TEST = Compose([
@@ -147,7 +147,7 @@ def execute(self):
             self.bird_eye_view_unique_images += 1
         self.previous_bird_eye_view_image = img
 
-        velocity_dim = np.full((150, 50), self.previous_speed/30)
+        velocity_dim = np.full((200, 66), self.previous_speed/30)
         new_img_vel = np.dstack((img, velocity_dim))
         img = new_img_vel
 

behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_70_km_h.py

@@ -135,7 +135,7 @@ def execute(self):
 
         self.update_pose(self.pose.getPose3d())
 
-        image_shape=(50, 150)
+        image_shape=(66, 200)
         img_base = cv2.resize(bird_eye_view_1, image_shape)
 
         AUGMENTATIONS_TEST = Compose([
@@ -149,7 +149,7 @@ def execute(self):
             self.bird_eye_view_unique_images += 1
         self.previous_bird_eye_view_image = img
 
-        velocity_dim = np.full((150, 50), self.previous_speed/30)
+        velocity_dim = np.full((200, 66), self.previous_speed/30)
         new_img_vel = np.dstack((img, velocity_dim))
         img = new_img_vel
 

behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_broken_input.py

@@ -126,7 +126,7 @@ def execute(self):
         ]
 
         AUGMENTATIONS_TEST = Compose([
-            GridDropout(p=1.0, ratio=0.9)
+            GridDropout(p=1.0)
         ])
 
         bird_eye_view_1 = AUGMENTATIONS_TEST(image=bird_eye_view_1)
@@ -140,7 +140,7 @@ def execute(self):
 
         self.update_pose(self.pose.getPose3d())
 
-        image_shape=(50, 150)
+        image_shape=(66, 200)
         img_base = cv2.resize(bird_eye_view_1, image_shape)
 
         AUGMENTATIONS_TEST = Compose([
@@ -154,7 +154,7 @@ def execute(self):
             self.bird_eye_view_unique_images += 1
         self.previous_bird_eye_view_image = img
 
-        velocity_dim = np.full((150, 50), self.previous_speed/30)
+        velocity_dim = np.full((200, 66), self.previous_speed/30)
         new_img_vel = np.dstack((img, velocity_dim))
         img = new_img_vel
 

behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_broken_input_2.py

@@ -140,7 +140,7 @@ def execute(self):
 
         self.update_pose(self.pose.getPose3d())
 
-        image_shape=(50, 150)
+        image_shape=(66, 200)
         img_base = cv2.resize(bird_eye_view_1, image_shape)
 
         AUGMENTATIONS_TEST = Compose([
@@ -154,7 +154,7 @@ def execute(self):
             self.bird_eye_view_unique_images += 1
         self.previous_bird_eye_view_image = img
 
-        velocity_dim = np.full((150, 50), self.previous_speed/30)
+        velocity_dim = np.full((200, 66), self.previous_speed/30)
         new_img_vel = np.dstack((img, velocity_dim))
         img = new_img_vel
 

behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_broken_input.py

@@ -147,7 +147,7 @@ def execute(self):
 
 
         AUGMENTATIONS_TEST = Compose([
-            GridDropout(p=1.0, ratio=0.9)
+            GridDropout(p=1.0)
         ])
 
         bird_eye_view_1 = AUGMENTATIONS_TEST(image=bird_eye_view_1)

behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_broken_input_2.py

@@ -9,7 +9,7 @@
 import carla
 from os import path
 from albumentations import (
-    Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare, GridDropout, ChannelDropout, GaussNoise
+    Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare, GridDropout, ChannelDropout
 )
 from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH
 from utils.logger import logger
@@ -147,8 +147,7 @@ def execute(self):
 
 
         AUGMENTATIONS_TEST = Compose([
-            #GridDropout(p=1.0, ratio=0.5),
-            GaussNoise(p=1.0, var_limit=(500.0, 1500.0))
+            GridDropout(p=1.0, ratio=0.9)
         ])
 
         bird_eye_view_1 = AUGMENTATIONS_TEST(image=bird_eye_view_1)

behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_70_km_h.py

@@ -172,9 +172,11 @@ def execute(self):
             self.image_8 = img
         elif type(self.image_9) is int:
             self.image_9 = img
+        elif type(self.image_10) is int:
+            self.image_10 = img
         else:
             self.bird_eye_view_images += 1
-            if (self.image_9==img).all() == False:
+            if (self.image_10==img).all() == False:
                 self.bird_eye_view_unique_images += 1
             self.image_1 = self.image_2
             self.image_2 = self.image_3
@@ -184,9 +186,10 @@ def execute(self):
             self.image_6 = self.image_7
             self.image_7 = self.image_8
             self.image_8 = self.image_9
-            self.image_9 = img
+            self.image_9 = self.image_10
+            self.image_10 = img
 
-            img = [self.image_1, self.image_4, self.image_9]
+            img = [self.image_1, self.image_5, self.image_10]
             img = np.expand_dims(img, axis=0)
 
             start_time = time.time()

behavior_metrics/driver_carla.py

@@ -127,7 +127,7 @@ def is_config_correct(app_configuration):
 
     return is_correct
 
-def generate_agregated_experiments_metrics(experiments_starting_time, experiments_elapsed_times):
+def generate_agregated_experiments_metrics(experiments_starting_time, experiments_elapsed_times, app_configuration):
     result = metrics_carla.get_aggregated_experiments_list(experiments_starting_time)
 
     experiments_starting_time_dt = datetime.fromtimestamp(experiments_starting_time)
@@ -252,28 +252,33 @@ def generate_agregated_experiments_metrics(experiments_starting_time, experiment
             'metric': 'suddenness_distance_speed_per_km',
             'title': 'Suddenness distance speed per km per experiment'
         },
-        {
-            'metric': 'dangerous_distance_pct_km',
-            'title': 'Percentage of dangerous distance per km'
-        },
-        {
-            'metric': 'close_distance_pct_km',
-            'title': 'Percentage of close distance per km'
-        },
-        {
-            'metric': 'medium_distance_pct_km',
-            'title': 'Percentage of medium distance per km'
-        },
-        {
-            'metric': 'great_distance_pct_km',
-            'title': 'Percentage of great distance per km'
-        },
+
         {
             'metric': 'completed_laps',
             'title': 'Completed laps per experiment'
         },
     ]
 
+    if app_configuration.task == 'follow_lane_traffic':
+        experiments_metrics_and_titles.append(
+            {
+                'metric': 'dangerous_distance_pct_km',
+                'title': 'Percentage of dangerous distance per km'
+            },
+            {
+                'metric': 'close_distance_pct_km',
+                'title': 'Percentage of close distance per km'
+            },
+            {
+                'metric': 'medium_distance_pct_km',
+                'title': 'Percentage of medium distance per km'
+            },
+            {
+                'metric': 'great_distance_pct_km',
+                'title': 'Percentage of great distance per km'
+            },
+        )
+
     metrics_carla.get_all_experiments_aggregated_metrics(result, experiments_starting_time_str, experiments_metrics_and_titles)
     metrics_carla.get_per_model_aggregated_metrics(result, experiments_starting_time_str, experiments_metrics_and_titles)
     metrics_carla.get_all_experiments_aggregated_metrics_boxplot(result, experiments_starting_time_str, experiments_metrics_and_titles)
@@ -413,7 +418,7 @@ def main():
                 logger.info('Invalid task type. Try "follow_route", "follow_lane" or "follow_lane_traffic". Killing program...')
                 sys.exit(-1)
             experiments_elapsed_times['total_experiments_elapsed_time'] = time.time() - experiments_starting_time
-            generate_agregated_experiments_metrics(experiments_starting_time, experiments_elapsed_times)
+            generate_agregated_experiments_metrics(experiments_starting_time, experiments_elapsed_times, app_configuration)
     if app_configuration.experiment_random_spawn_point == True or app_configuration.task == 'follow_route':
         if os.path.isfile('tmp_circuit.launch'):
             os.remove('tmp_circuit.launch')