The main files of this repo are the training.py and the writeup.md. The result of driving the vehicle autonomously is captured in run.mp4. The writeup.md contains screenshots of the images captured during training, preprocessing and during the actual autonomous ride.
This lab requires:
The lab enviroment can be created with CarND Term1 Starter Kit. Click here for the details.
The following resources can be found in this github repository:
- drive.py
- video.py
- training.py
- writeup.md
The simulator can be downloaded from the download-data.sh file. A screenshot of the simulator for the first track is shown below:
Usage of drive.py requires you have saved the trained model as an h5 file, i.e. model.h5. Note that the model.h5 used in this repo
is available in the S3 bucket but for AWS cost reasons the file is not available for download.
Once the model has been created locally, it can be used with drive.py using this command:
python drive.py model.h5The above command will load the trained model and use the model to make predictions on individual images in real-time and send the predicted angle back to the server via a websocket connection.