End to End Learning for Self-Driving Cars
Still work in progress, but basic model trained on GTA V dataset can be found:
- 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.
model.pycontains the ConvNet, running the file will output a model to be used by
- Keras '1.2.0'
- Theano '0.9.0dev4.dev-RELEASE'
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.pycan 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.
the data contains weird incidents where the car is not going anywhere and suddent appearnce of other cars