Progress
This week, I trained a few new models on the new dataset for the point. With evaluating validation accuracy on seperate videos, I found that the SVM method gave around 92% accuracy. So, I also tried a simple categorical neural net that gave around 93% validation accuracy. Additionally, I tried a multitask model that predicted the x and y categories individually. This gave the best results, with 97% validation accuracy for the x axis and 94% on the y axis.
Installing tensorflow on the Xavier board took some time, but I have recorded the installation steps for future reference.
I am also collecting the larger point dataset, with a room larger than just 3×3 bins.
Deliverables next week
Next week, I will apply some SVM tuning suggestions Marios gave us. I am also going to train the models on the larger point dataset. I will also work on a trigger for the dataset.
Schedule
On schedule.