Scripts for computing IoU about deepglobe-road-extraction-challenge HOT 4 CLOSED

There is no script for computing IoU or mIoU in this repository. Computing IoU using numpy just like this.
def iou(a, b): a //= 255 b //= 255 o = a+b i = (o==2).sum() u = (o>=1).sum() if u == 0: return 1.0 return 1.0*i/u

from deepglobe-road-extraction-challenge.

Thanks for the reply.

Another question: how did you do the validation if the validation masks are not available in the dataset?
(I had also seen the same question of yours on the DeepGlobe forum, but there was no reply there)

from deepglobe-road-extraction-challenge.

For your question, I did not validate my models in the final phase.

I tried several methods in the development phase, and found that D-LinkNet34 is better than the ensemble of LinkNet34 and Unet on the validation set.
Therefore, I trained D-LinkNet50, D-LinkNet101 and D-Unet in the final phase, and submitted the predictions on the test set only.

It would be more standard to use some kind of validation such as cross-validation. However, due to the time limitation and no many training images, I did not partition some of the data as validation set.

from deepglobe-road-extraction-challenge.

@zlkanata
Thanks for the help!

from deepglobe-road-extraction-challenge.