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This is the code for "How to Simulate a Self-Driving Car" by Siraj Raval on Youtube
This is the code for this video on Youtube by Siraj Raval. We're going to use Udacity's self driving car simulator as a testbed for training an autonomous car.
You can install all dependencies by running one of the following commands
You need a anaconda or miniconda to use the environment setting.
# Use TensorFlow without GPU
conda env create -f environments.yml
# Use TensorFlow with GPU
conda env create -f environment-gpu.yml
Or you can manually install the required libraries (see the contents of the environemnt*.yml files) using pip.
Start up the Udacity self-driving simulator, choose a scene and press the Autonomous Mode button. Then, run the model as follows:
python drive.py model.h5
You'll need the data folder which contains the training images.
python model.py
This will generate a file model-<epoch>.h5
whenever the performance in the epoch is better than the previous best. For example, the first epoch will generate a file called model-000.h5
.
The credits for this code go to naokishibuya. I've merely created a wrapper to get people started.
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