This repository aims to provide an object detection system in carla simulation environment. YOLOv3 algorithm is chosen as a detector system to detect and classify pedestriants, vehicles and objects on the road. This algorithm is based on YOLOv3: An Incremental Improvement which originaly implemented in YOLOv3
- python 3.7
- Opencv 3.4.2
- numpy
To start with the implementation
-
Download CARLA simulator (version 0.9.11).
-
Clone the following repository
git clone https://github.com/shayantaherian/Object_Detection_Carla.git
-
Copy
Object_Detection.py
inCARLA_0.9.11/PythonAPI/examples
folder.# -
Run
CarlaU£4.exe
to connect with the server. -
Finally run
Object_Detection.py
.
Note that to use yolov3 for this task, it is required to download yolo weights from yolov3.weights. Examples of this detection system in carla environment can be seen as follows: