The goal of this project is to use deep neural networks and convolutional neural networks to clone driving behavior. The model was trained, validated and tested using Keras, and will output a steering angle to an autonomous vehicle.
The network architecture used is very similar to the LeNet architecture, and uses several convolutional layers with max pooling followed by fully connected layers that perform the classification.
Check out my writeup to learn more about my process and how it works.
This lab requires:
The simulator can be downloaded from the classroom. In the classroom, we have also provided sample data that you can optionally use to help train your model.
Usage of drive.py
requires you have saved the trained model as an h5 file, i.e. model.h5
. (See the Keras documentation).
Once the model has been saved, it can be used with drive.py using this command:
python drive.py model.h5
The 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.
python drive.py model.h5 run1
The fourth argument, run1
, is the directory in which to save the images seen by the agent. If the directory already exists, it'll be overwritten.
ls run1
[2017-01-09 16:10:23 EST] 12KiB 2017_01_09_21_10_23_424.jpg
[2017-01-09 16:10:23 EST] 12KiB 2017_01_09_21_10_23_451.jpg
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[2017-01-09 16:10:23 EST] 12KiB 2017_01_09_21_10_23_528.jpg
[2017-01-09 16:10:23 EST] 12KiB 2017_01_09_21_10_23_573.jpg
[2017-01-09 16:10:23 EST] 12KiB 2017_01_09_21_10_23_618.jpg
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[2017-01-09 16:10:23 EST] 12KiB 2017_01_09_21_10_23_817.jpg
...
The image file name is a timestamp of when the image was seen. This information is used by video.py
to create a chronological video of the agent driving.
python video.py run1
Creates a video based on images found in the run1
directory. The name of the video will be the name of the directory followed by '.mp4'
, so, in this case the video will be run1.mp4
.
Optionally, one can specify the FPS (frames per second) of the video:
python video.py run1 --fps 48
Will run the video at 48 FPS. The default FPS is 60.
There is known local system's setting issue with replacing "," with "." when using drive.py. When this happens it can make predicted steering values clipped to max/min values. If this occurs, a known fix for this is to add "export LANG=en_US.utf8" to the bashrc file.