Update segmentation.md

doc/research/paf24/segmentation.md

@@ -3,10 +3,10 @@
 **Summary:** This page contains the research into the segmentation component of Autoware.
 
 - [Segmentation](#Segmentation)
-  - [Already implemended solutions](#1.-Already-implemented-solutions)
-  - [Implemented but dropped](#2Implemented-but-dropped)
-  - [Carla Sensors](#3-Carla-Sensors)
-  - [Follow up Question](#4-Follow-up-Question)
+  - [Already implemented solutions](#already-implemented-solutions)
+  - [Implemented but dropped](#implemented-but-dropped)
+  - [Carla Sensors](#carla-sensors)
+  - [Follow-up Question](#follow-up-question)
 
 ## Already implemented solutions
 
@@ -19,23 +19,34 @@ https://github.com/una-auxme/paf/blob/8e8f9a1a03ae09d5ac763c1a11b398fc1ce144b0/c
 https://github.com/una-auxme/paf/blob/8c968fb5c6c44c15b2733c5a181c496eb9b244be/doc/perception/efficientps.md#efficientps
 
 ## Carla Sensors:
-https://carla.readthedocs.io/en/0.8.4/cameras_and_sensors/
-```
-camera = carla.sensor.Camera('MyCamera', PostProcessing='SemanticSegmentation')
-camera.set(FOV=90.0)
-camera.set_image_size(800, 600)
-camera.set_position(x=0.30, y=0, z=1.30)
-camera.set_rotation(pitch=0, yaw=0, roll=0)
+![Alt text](https://carla.readthedocs.io/en/0.9.14/img/ref_sensors_semantic.jpg)
+![Alt text](https://carla.readthedocs.io/en/0.9.14/img/tuto_sem.jpg)
 
-carla_settings.add_sensor(camera)
-```
-![Alt text](https://github.com/una-auxme/paf/blob/368-visionnode-and-segmentation/doc/assets/perception/Carla_Segmentation_Sensor.png)
+for more context:
+the pedestrian walks will be labled as roadlines
+
+example:
+``` 
+# --------------
+# Add a new semantic segmentation camera to my ego
+# --------------
+sem_cam = None
+sem_bp = world.get_blueprint_library().find('sensor.camera.semantic_segmentation')
+sem_bp.set_attribute("image_size_x",str(1920))
+sem_bp.set_attribute("image_size_y",str(1080))
+sem_bp.set_attribute("fov",str(105))
+sem_location = carla.Location(2,0,1)
+sem_rotation = carla.Rotation(0,180,0)
+sem_transform = carla.Transform(sem_location,sem_rotation)
+sem_cam = world.spawn_actor(sem_bp,sem_transform,attach_to=ego_vehicle, attachment_type=carla.AttachmentType.Rigid)
+# This time, a color converter is applied to the image, to get the semantic segmentation view
+sem_cam.listen(lambda image: image.save_to_disk('tutorial/new_sem_output/%.6d.jpg' % image.frame,carla.ColorConverter.CityScapesPalette))
 
-there is another solution implemented by the carla simulator:
+```
+For more information:
 https://carla.readthedocs.io/en/0.9.14/ref_sensors/#semantic-segmentation-camera:~:text=the%20object%20it.-,Semantic%20segmentation%20camera,-Blueprint%3A%20sensor
 
-for more context:
-the pedestrian walks will be labeld as roadlines
+https://carla.readthedocs.io/en/0.9.14/tuto_G_retrieve_data/#semantic-segmentation-camera:~:text=on%20the%20right.-,Semantic%20segmentation%20camera,-The%20semantic%20segmentation
 
 ## Follow up Question:
 Why the last group used bounding boxes and not the segmentation model is it to slow or maybe not reliable?