Hi all! Just finished lesson 1 and decided to have a little fun gathering my own dataset for this week’s project: identifying whether a person is wearing their mask properly or improperly. Images were manually gathered using Google Images. A total of 45 images of proper mask wear and 45 images of improper mask wear were gathered. Here is a random batch:
I managed to reach an error rate of 17% (3 out of 18 images incorrectly classified). Not too sure how to improve this given the small dataset size. I tried applying some data augmentation using mixup, but it did not help much. Here are the top losses (some very obvious errors):
I’ll be moving on to lesson 2 so hopefully new tips and tricks will help. Code is available on GitHub.