I am using pre-trained ResNet34v1. Also I am normalizing the input data bounded to between 0 and 1, although it is not normalized using |data-mean|/SD format but for now I am just diving images by 255 and lable data by size of the image.
Okay I have pretty much attached my entire code in Jupyter-notebook with some sample examples linked here…
JupyterNotebook Google Drive Link
Set up virtualenv and you should be good to go once you install requirements.txt.
I do know anchor boxes are bit off and might not be scaled properly. I am working on fixing that.
So main question is why the loss is decreasing should I use IOU as error function?
Also do you think would it viable to use ResNet101 instead of 34 for image of size 1675x1250.
And one question is would be good to use rectangular images? That was the next area that I wanted to explore.