TensorFlow impementation of: Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images, with code optimized for clarity and simplicity.
Only 160 lines of code, and only uses Python modules that come installed with TensorFlow. Proper writeup explaining the paper plus improved model code to soon follow.
Left column are xt, x{t+1}, and right column are the E2C reconstructions.
Larger step sizes (magnitude of u) yield better latent space reconstruction...
but degrade image reconstruction fidelity (more on this later...). Here's a different set of obstacles:
First, generate the synthetic training data plane2.npz
by running the following script.
$ python plane_data2.py
Then, train the model
$ python e2c.py
You can then generate visualizations by executing:
$ python viz_results.py
Thanks to Manuel Watter for answering my questions about the paper.
Apache 2.0