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Autonomous driving: Tensorflow implementation of the paper "End-to-end Driving via Conditional Imitation Learning"

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"We take different weight hyperparameters for the outputs (steer, gas, brake, speed), since the hyperparameters suggested in the paper did not work for us." Do you mean the suggested hyperparameters...

does the code support fine tuning or is it train a model from scratch?

After training the model with the 24GB training dataset, I loaded it into a client on CARLA, just to realize that it outputs extremely large values (i.e. in the thousands)...

Currently training only works using the `tf.Estimator` framework. Some users might prefer using the standard `sess.run` way of calling the training operation for a more low level way of doing...

enhancement

So far, we only provide instructions to run this on Python2. It would be nice to make the codebase compatible with both Python2 and Python3.

enhancement

The Steer is between -1 and 1,but the last layer Activation function is RELU

Bumps [pillow](https://github.com/python-pillow/Pillow) from 5.2.0 to 9.3.0. Release notes Sourced from pillow's releases. 9.3.0 https://pillow.readthedocs.io/en/stable/releasenotes/9.3.0.html Changes Initialize libtiff buffer when saving #6699 [@​radarhere] Limit SAMPLESPERPIXEL to avoid runtime DOS #6700 [@​wiredfool]...

dependencies