Skip to content
master
Go to file
Code

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

readme.md

End to End Learning for Self-Driving Cars

  • Still work in progress, but basic model trained on GTA V dataset can be found:

    To Do:

    • Get proper driving data.
    • Inlcude the autonomy score.
    • Include model internal state viz.

About the Model

  • Originally the model consists of:

The network consists of 9 layers, including a normalization layer, 5 convolutional layers and 3 fully connected layers. The input image is split into YUV planes and passed to the network.

img

  • model.py contains the ConvNet, running the file will output a model to be used by train.py

Dependecy:

  • Keras '1.2.0'
  • Theano '0.9.0dev4.dev-RELEASE'

Dataset:

  • The GTA V Dataset was used, previously it use to be hosted here.

  • The dataset is messy often, but good enough for training/testing a model.

  • If you have the dataset, load_deepdrive_data.py can be used to reduce the data into 128 and do any normalization desired for the model.

  • trained model / weights, can be downloaded here

Training results for steering with Autopilot ConvNet:

  • GPU (Trained 1080).

  • Green is the original steering, and red is the Model's predictions.

img

the data contains weird incidents where the car is not going anywhere and suddent appearnce of other cars

About

Keras Implementation of End to End Learning for Self-Driving Cars by (Baris Kayalibay, Grady Jensen, Patrick van der Smagt)

Resources

Releases

No releases published

Packages

No packages published

Languages

You can’t perform that action at this time.