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F3 Netherlands Patch Experiments

In this folder are training and testing scripts that work on the F3 Netherlands dataset. You can run five different models on this dataset:

All these models take 2D patches of the dataset as input and provide predictions for those patches. The patches need to be stitched together to form a whole inline or crossline.

To understand the configuration files and the dafault parameters refer to this section in the top level README

Setup

Please set up a conda environment following the instructions in the top-level README.md file. Also follow instructions for downloading and preparing the data.

Running experiments

Now you're all set to run training and testing experiments on the F3 Netherlands dataset. Please start from the train.sh and test.sh scripts under the local/ and distributed/ directories, which invoke the corresponding python scripts. Take a look at the project configurations in (e.g in default.py) for experiment options and modify if necessary.

Monitoring progress with TensorBoard

  • from the this directory, run tensorboard --logdir='output' (all runtime logging information is written to the output folder
  • open a web-browser and go to either vmpublicip:6006 if running remotely or localhost:6006 if running locally

NOTE:If running remotely remember that the port must be open and accessible

More information on Tensorboard can be found here.