08. Training Your Network

Note that the workspace for this project is equipped with a GPU which can be enabled for training your network. So, rather than working in a shell on AWS you can enable GPU mode and work in a workspace shell.

04 - Training The Network

INSTRUCTOR NOTE:

NOTE: cv2.imread will get images in BGR format, while drive.py uses RGB. In the video above one way you could keep the same image formatting is to do "image = ndimage.imread(current_path)" with "from scipy import ndimage" instead.

Training Your Network

Now that you have training data, it’s time to build and train your network!

Use Keras to train a network to do the following:

  1. Take in an image from the center camera of the car. This is the input to your neural network.
  2. Output a new steering angle for the car.

You don’t have to worry about the throttle for this project, that will be set for you.

Save your trained model architecture as model.h5 using model.save('model.h5').

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