This week I worked on:
- created new clothing classification model to reduce overfitting. Added stronger preprocessing, dropout layer, batch normalization layer, and trained for less epochs. The new model achieved ~70% validation accuracy.
- created top-5 accuracy test on test data set. Overall 91% top-5 accuracy (yay! this meets our requirements of 90%)
- Started software integration of visualizer API. Integrated clothing detection and classification, working on integrating webscrapper right now.
- Helped Fred with hardware design. We required high precision in assembly so I suggested using laser cut components to aid in assembly. For next week:
- Finish visualizer software integration and create validation tests for software component.
- measure accuracy on images scraped from online
- measure runtime of system
- measure if storage costs are within our initial predictions
I am on schedule.