Muhammad Tanveer

Hi same issue with me. Did you find any solution?

Change your data path train_config.yml file. Then it will generate nns folder by itself.

> pytorch_data_dir You should change your data directory here to the potsdam data where it exists in your system.

> The path '/home/STEGO/src/datadrive/pytorch-data' which I have provided in PyTorch_data_dir _is_ the path to the potsdam directory. Yet precompute_knns.py apparently looks for '/home/STEGO/src/datadrive/pytorch-data/cropped/cocostuff27_None_crop_0.5/img/val'. I cannot figure out, why that path...

> I was wondering if it's possible to adapt the model to bigger image resolutions. If so, it's possible to use non-square images? Hi I am looking for the thing.....

> Sorry, I have only used the model in inference mode for the moment. However, input and output images are 320x320 resolution. > > My question is more oriented toward...

> My insight is that the model complexity (i.e. trainable params) would increase unreasonable, so prepare your GPUs... > > Jokes aside, please let me know about your progress on...

> > > > Hey, did you make any progress training with higher res images? Yes I trained model with high resolution. I used my own dataset and I experienced...

> Hi @BradNeuberg , Will you show some example how did you use Bayesian hyperparameter optimizer, SigOpt to optimize the hyperparameters for STEGO model?

> Let's say you have 27 classes and your dataset is relatively balanced, that is p(C)=1/27. If you pick two random images, they will likely not have the same class,...