Is the glass half-full or half-empty?
Well, it depends on the weather! If it's raining in Pittsburgh, it's half-empty. If there's nice weather, it's half full. Basically, depending on the weather the reader will either have a pessimist or optimist look on the world.
The machine learning algorithm is looking for three states: Full, Half, and Empty. Depending on the state, it will ask the Openweather API the state of the weather. If the weather is bad, the machine learning system will say that the Glass is half empty, else it will say that it is half full.
I suggest the viewer to train the model using a dark liquid because it would be easier for the computer to differentiate between the bottle and the background.
Originally, I wanted to do face tracking but then I realized that having to retrain ML5 over and over again would prove too repetitive, instead I decided to make something that would tell me how full a bottle of water is.
When I was working on the accuracy of my project, I modified Professor Levin's variant of the ml5 p5.js classifier so it would tell me what items it would see. For example, if I were to train the model using three different labels, it would give me all the labels in order of accuracy. The most accurate label would appear first, followed by the least accurate and so on.
At one point, I was trying to have a trained model load upon runtime because I didn't want to constantly retrain the classifier. Unfortunately, I couldn't get it to work in time.