PythonPilot
This is an Open Source Python Framework for prototyping ADAS and Autonomous Vehicles. It supports only Lateral Control now.
freeway_test.mp4
Table of Contents
- Tested Development Environment
- Getting Started
- Running the demo
- Architecture
- Use Cases
- Acknowledgments
- License
Tested Development Environment
- Processer: Intel Core i9-9900K CPU @ 3.60GHz × 16
- Memory: 16GB
- Graphics: NVIDIA GeForce RTX 2080/PCIe/SSE2
- OS Types: Ubuntu 16.04 LTS 64-bit
- Disk: 240GB
Getting Started
Clone Repository
$ cd ~/
$ git clone https://github.com/YanbaruRobotics/PythonPilot
Prerequisites
-
Python 3.5.x
-
matplotlib 3.0.2
-
numpy 1.16.1
-
OpenCV 3.4.5
-
scipy 1.2.1
-
tensorflow 1.13.0
$ cd ~/PythonPilot/
$ sudo pip3 install -r requirements.txt
Download and uncompress the model
$ cd ~/PythonPilot/
$ wget https://www.dropbox.com/s/i7b6eyzucoxs0fq/models.zip # 800 MB
$ unzip models.zip
$ rm -r models.zip
Download and uncompress sample log data
$ cd ~/PythonPilot/
$ wget https://www.dropbox.com/s/mo6zo1oo2s46l02/log.zip # 600 MB
$ unzip log.zip
$ rm -r log.zip
Running the demo
Lunch a vehicle server
$ cd ~/PythonPilot/scripts/
$ bash run_vehicle_main.sh
Lunch a pilot client
Open a new terminal.
$ cd ~/PythonPilot/scripts/
$ bash run_pilot_main.sh
Stop Program
Type 'Ctrl' + 'c' in both terminals.
Architecture
Use Cases
You can see other example videos at here.
Acknowledgments
- The Lane Segmnetation is built upon LaneNet and BDD100K data.
- The Object Detection is built upon realtime_object_detection.
License
This project is licensed under the Apache License 2.0 - see the LICENSE file for details
THIS IS ALPHA QUALITY SOFTWARE FOR RESEARCH AND EDUCATION PURPOSES ONLY. YOU ARE RESPONSIBLE FOR USING WITH LOCAL LAWS AND REGULATIONS. NO WARRANTY EXPRESSED OR IMPLIED.