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Pull request #1: Improve README

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Merge in EAI/platform-demo-scripts from switching_to_pytorch_lightning_and_pick_benchmark_rev1 to switching_to_pytorch_lightning_and_pick_benchmark

* commit '447b5cf5d58d83f0590448cee4a01a33361931bc':
  Improve README
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Hubert Siejkowski 2023-08-29 15:07:52 +02:00 committed by Krystyna Milian
commit ca7506bd1d
1 changed files with 18 additions and 2 deletions
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README.md
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@ -13,7 +13,13 @@ This repo contains notebooks and scripts demonstrating how to:
### Acknowledgments
This code is based on the [pick-benchmark](https://github.com/seisbench/pick-benchmark), the repository accompanying the paper:
[Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers](https://github.com/seisbench/pick-benchmark#:~:text=Which%20picker%20fits%20my%20data%3F%20A%20quantitative%20evaluation%20of%20deep%20learning%20based%20seismic%20pickers)
[Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers](https://doi.org/10.1029/2021JB023499)
### Before running
Please [install Poetry](https://python-poetry.org/docs/#installation), a tool for dependency management and packaging in Python.
Then we will use only Poetry for creating Python environment and installing dependencies.
### Usage
1. Install all dependencies with poetry, run:
@ -27,7 +33,7 @@ This code is based on the [pick-benchmark](https://github.com/seisbench/pick-ben
WANDB_PROJECT="training_seisbench_models_on_igf_data"
BENCHMARK_DEFAULT_WORKER=2
3. Transform data into seisbench format.
3. Transform data into seisbench format. (unofficial)
* Download original data from the [drive](https://drive.google.com/drive/folders/1InVI9DLaD7gdzraM2jMzeIrtiBSu-UIK?usp=drive_link)
* Run the notebook: `utils/Transforming mseeds to SeisBench dataset.ipynb`
@ -58,3 +64,13 @@ This code is based on the [pick-benchmark](https://github.com/seisbench/pick-ben
* `wandb: ERROR Run .. errored: OSError(24, 'Too many open files')`
-> https://github.com/wandb/wandb/issues/2825
### Licence
TODO
### Copyright
Copyright © 2023 ACK Cyfronet AGH, Poland.
This work was partially funded by EPOS Project funded in frame of PL-POIR4.2