I want to build an app that will recognize what emojis have been used on the wallpaper.

So for instance this app will receive on input:

And on output should array of names of recognizing emojis return:

[
  "Smiling Face with Sunglasses", 
  "Grinning Face with Smiling Eyes", 
  "Kissing Face with Closed Eyes"
]

I have prepared training data that consists of individual emojis. For instance, I have rotated each emoji by 30 degrees, cut it by half, etc.

After training the model, the average precision is 0.8, which is quite nice, but it only works for one emoji per wallpaper. If I upload many types of emojis on one wallpaper, it does not recognize any objects.

My question is: why does it recognize one type of emoji per wallpaper, but if I put many types of emojis on one wallpaper, it does not work?

I am using Google ML Vision, and I have chosen Multi-Label Classification for the data set.