Realistically, this was a very busy week for me which meant that I didn’t make much progress on the ML component of our project. Knowing that I wouldn’t have much time this past week, I overloaded a lot of work during the fall break so I am still ahead of schedule. These are some of the minor things I did:
- Significantly improved image preprocessing with more transformations which have kept our model from overfitting.
- Testing a transition away from the Haar-Cascade facial recognition model.
- I realized that while lightweight, this model in more very good or reliable.
- I have been working on creating our own model using Resnet as well as multiple components that I have built on top.
- Set up AWS instances to train our model in a much more efficient and faster way.
I am still ahead of schedule given that we have a usable emotion recognition model much before the deadline.
Goals for next week:
- Continue to update the hyperparameters of the model to obtain the best accuracy as possible.
- Download the model to my local machine which should allow me to integrate with OpenCV and test the recognition capabilities in real-time.
- Then, Download our model onto the Nvidia Jetson to ensure that it will run in real-time as quick as we want it.
- After this, I want to experiment with some other facial recognition models and boundary boxes that might make our system more versatile.