Updated brain

JdeRobot · Apr 29, 2024 · 5afe1ff · 5afe1ff
1 parent 4fe663b
commit 5afe1ff
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Showing 2 changed files with 5 additions and 44 deletions.
diff --git a/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_V.py b/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_V.py
@@ -127,32 +127,10 @@ def execute(self):
         try:
             image = Image.fromarray(image)
 
-            #print(image.size)
-            #image = image.resize((300, 225))
-            #image = image.resize((225, 300))
-            #print(image.size)
-            #image.save('imagen_guardada.png')
-            # (2048, 1536)
-            # (2048, 120)
-
-
-            # ATLAS original
-            #camera_bp.set_attribute('image_size_x', str(2048))
-            #camera_bp.set_attribute('image_size_y', str(1536))
-            # We adjust the size to retrieve images at a faster pace
-            #camera_bp.set_attribute('image_size_x', str(300))
-            #camera_bp.set_attribute('image_size_y', str(224.85))
-
             altura_recorte = 120
             ancho, altura = image.size
             y_superior = max(0, altura - altura_recorte)
             image = image.crop((0, y_superior, ancho, altura))
-
-            #print('image.size', image.size)
-
-
-
-
             image = self.transformations(image)
 
 
@@ -161,33 +139,21 @@ def execute(self):
             vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2)
 
             #print('vehicle_speed', vehicle_speed)
-
             vehicle_speed_norm = torch.clamp(torch.tensor(vehicle_speed, dtype=torch.float32) / 40.0, 0, 1.0)
 
 
             valor_cuartadimension = torch.full((1, image.shape[1], image.shape[2]), float(vehicle_speed_norm))
             image = torch.cat((image, valor_cuartadimension), dim=0).to(self.device)
             image = image.unsqueeze(0) 
 
-            #print('image.shape', image.shape)
-            #print('self.gpu_inference', self.gpu_inference)
-            #print(image)
-
             start_time = time.time()
             with torch.no_grad():
                 prediction = self.net(image).cpu().numpy() if self.gpu_inference else self.net(image).numpy()
             self.inference_times.append(time.time() - start_time)
 
-            print('prediction', prediction)
-            if (prediction[0][1] < 0.4):
-                print('LOG!!!!!!!!!!!!!!!!!!!!!!!!!!!')
+            #print('prediction', prediction)
             #print(prediction)
             prediction = prediction.flatten()
-            # prediction = prediction.detach().cpu().numpy().flatten()
-            #print('prediction', prediction)
-
-            #print('vehicle_speed', vehicle_speed)
-            #print('vehicle_speed_norm', vehicle_speed_norm)
 
             combined, steer = prediction
             combined = float(combined)
@@ -197,13 +163,8 @@ def execute(self):
             else:
                 break_command = (0.5 - combined) / 0.5
             steer = (float(steer) * 2.0) - 1.0
+            #print(throttle, steer, break_command)
 
-            #throttle = prediction[0][0]
-            #steer = prediction[0][1] * (1 - (-1)) + (-1)
-            #break_command = prediction[0][2]
-
-            print(throttle, steer, break_command)
-            #print('----')
 
             if vehicle_speed > 30:
                 self.motors.sendThrottle(0)
@@ -215,7 +176,7 @@ def execute(self):
                     self.motors.sendSteer(0.0)
                     self.motors.sendBrake(0)
                 else:
-                    self.motors.sendThrottle(0.5)
+                    self.motors.sendThrottle(throttle)
                     self.motors.sendSteer(steer)
                     self.motors.sendBrake(break_command)
 

diff --git a/behavior_metrics/configs/CARLA/default_carla_torch.yml b/behavior_metrics/configs/CARLA/default_carla_torch.yml
@@ -34,10 +34,10 @@ Behaviors:
                     MaxV: 3
                     MaxW: 0.3
         BrainPath: 'brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_V.py'
-        PilotTimeCycle: 50
+        PilotTimeCycle: 100
         AsyncMode: True
         Parameters:
-            Model: '15_04_best_model_checkpoint_189.pth'
+            Model: '29_04_best_model_checkpoint_299.pth'
             ImageCropped: True
             ImageSize: [ 100,50 ]
             ImageNormalized: True