Modify input image size for training/inference

[cvKDean]

Good day,

I would like to train on my own map images. However I noticed that the input image size is 300 * 300, following the crowdAI (AIcrowd) Mapping Challenge dataset. Is it possible to train on images with a different size/resolution (e.g. 900 * 900. 512*512)? Thank you.

[jakubczakon]

Sorry for late reply @cvKDean.
I think you just need to change https://github.com/neptune-ml/open-solution-mapping-challenge/blob/master/neptune.yaml#L75-L76 to your size and you should be good to go.

[cvKDean]

Thank you for the response @jakubczakon.
I was able to train on my own temporary dataset. However, the training seems to be finished at around epoch 30-31, when the number of epochs in my neptune.yaml file is set to 100.
Is there something in the model that makes it finish training even before it reaches the defined number of epochs?