This repository represents a tool which shows and allows you to start-up your car easier. In this project the following functionalities are implemented in Python:
- a simple multithread/multiprocess architecture
- utility tools/packages for a better development experience
The above image illustrates the general overview of a possible architecture. It is a layered architecture where each node (colored rectangle) represents a process. The gray rectangles denotes the modules/packages, which are not implemented. The inter-process communication is done with pipes. The main ideas, that we followed in the development of this architecture, were modularity and the ease of modification anywhere and anytime. A range of tools have been created for development and debugging.
Hardware Layer:
- Camera Handler
- Serial Handler
Data Acquisition Layer:
- Lane Detector
- Object Detector
- Sensor Processor
- GPS Tracker
Brain Layer:
- Data Fusion
- Decision Making
- Camera Spoofer
- Remote Control
- Camera Streamer
To see the full documentation for each component, please follow the links above [to be completed].
The applications was tested with Python3.7, but there are compatible with other version of Python3. For using the implemented applications you have to install the Python API of Opencv (cv2) on the remote device and your Raspberry. If you are using Debian based operating system, you can do it easily by running the following code in terminal:
sudo apt-get install python3-opencv
The requirements files contains the other dependencies, they are different for the Raspberry Pi and your remote device. The script, which runs on Raspberry Pi, depends on pySerial, picamera, cv2 code libraries. The remote debug and development tools relies on pynput and cv2 libraries. You can install these libraries by applying the following codes:
Raspberry Pi
pip3 install -r requirements_rpi.txt
PC
pip3 install -r requirements_remote.txt
Note: The remote tools were tested on Linux and Windows. On Linux they are worked correctly without any error. On Windows the camera receiver works nicely, but the remote controller transmitter may produce a delay. On Mac Os the remote tools weren't tested.
The first step before being able to test the platform and add more functionalities to it is to configure the scripts that one can find in this repository. To do so, you will have to set of your IP addresses, for your Raspberry and for your PC, and, if necessary, the ports used for communication. This configuration should occur every time the IP of one of your devices has changed.
The following files should be considered:
src/utils/camerastreamer/camerastreamer.py
src/utils/camerastreamer/camerareceiver.py
src/utils/remotecontrol/remotecontroltransmitter.py
src/utils/remotecontrol/remotecontrolreceiver.py
Note: You have to change the IP parameters only in RemoteControlTransmitter and CameraStreamer classes, where they are class member parameters, named serverIp.
In order to control your car, you will have to start your application onto RaspberryPi and enable from main.py the Remote Control feature, by setting the enableRc flag to true value. Also, you will have to launch the Remote Control Transmitter on your PC and make sure that the IP of your devices are configured correctly.
After that, run the following:
Raspberry Pi
python3 main.py
PC
python3 -m bin.remotecontroltransmitter
If you want to stream the camera and view on the remote device, you will have to start the same application onto RaspberryPi and enable from main.py the Camera Steamer feature, by changing the enableStream flag to true value. On the remote device you will have to run the Camera Receiver script. The IP address of the remote device must be introduced in the CameraStreamer class. After the configuration, you can run the following code:
Raspberry Pi
python3 main.py
PC
python3 -m bin.camerareceiver