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Teach a convolutional neural network (NVIDIA architecture) how to drive using the Udacity self-driving car simulator

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Behavioral-Cloning

Teach a convolutional neural network (NVIDIA architecture) how to drive using the Udacity self-driving car simulator

  • Create an Anaconda environment using conda env create -f environment.yml --name car_environment within the repo

  • Activate the Anaconda environment using source activate car_environment

  • model.py --> script used to create and train the model

  • drive.py --> script to drive the car by Udacity

  • model.h5 --> a trained Keras model

  • video.py --> script used to create a video from the autonomous driving pictures

Save a video of the autonomous agent --> python drive.py model.h5 run1 (run1 being the directory where the images get saved)

Make an mp4 video of the autonomous driving --> python video.py run1 (--fps 48 for 48 FPS)

Starter code provided by Udacity

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Teach a convolutional neural network (NVIDIA architecture) how to drive using the Udacity self-driving car simulator

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