# 21th place solution

This competition is a tough one, with more than 4K resolution images training a decent model will take ages. One look at the competition and the immediate thought of solution is directly Mask RCNN based on the multi-class segmentation problem.
Our solution is a simple RESNET50 and RESNET101 Mask RCNN ensemble, training didn't stop improving for both of the models but we were forced to stop halfway after a few epochs wasting a lot of time as predicting and generating predictions also takes a lot of time. The ensemble we used is a simple average of mask and weighted average of scores based on proximity.
The ensemble didn't help as much as we expected it to and we only had time to test one type of parameters. Looks like we should have used our time to train more epochs. All in all a great experience especially with the lack of code from kernals to go forward. Looking forward to the Top Teams Sharing!