Could I ask if there is a reason for the output to differ between versions of gluoncv? I’m currently investigating frameworks but am finding that between different versions of gluoncv I am getting different output on the same image sets. For example, on v0.1.0 the same image passed into the exact same demo_fcn.py generates a different output segmentation to mask when ran on v0.2.*
I was hoping to have consistent masks generated so I could create a test suite that will alert me to varying output (I use the mask to process the image); however, it seems that for the same downloaded model I get drastically inconsistent results between GluonCV versions.
Do the different versions download different models, or is it more to do with how GluonCV is operating as it is developed?