What we did this week:
Dylan completed the image dewarping and mapping the transformed face from the image processing to the projected image. Dylan also began transferring our processing to AWS.
Avi has almost completed the training loop to train the adversarial network. He has gotten to the point where gradients can be passed backwards through the networks to train and reduce loss consistently in a small test case.
Claudia began overlaying shapes onto the chosen facial landmark coordinates that are obtained from dlib. Some of them did not have much effect, as they did not change the classification probabilities significantly.
What we are planning to do:
Dylan is planning to finish transferring our scripts to AWS. Dylan also plans on verifying that the projection works as expected if the projector comes in.
Avi will finish implementing the training loop so that the Adversarial network will be able to show significant learning by the end of the week. He will also implement other adversarial network architectures to train.
Claudia will try out more combinations of modifications and facial landmarks to find the ones that work best across all test individuals.