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seisbench-model-api
An overview of the core model API of SeisBench, a Python framework for training and applying machine learning algorithms to seismic data. It is useful for annotating waveforms using pretrained SOTA ML models, for tasks like phase picking, earthquake detection, waveform denoising and depth estimation. For any waveform, you can manipulate it into an obspy stream object and it will work seamlessly with seisbench models.
tasks/seismic-phase-picking/environment/skills/seisbench-model-api/SKILL.md
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# SeisBench Model API
## Installing SeisBench
The recommended way is installation through pip. Simply run:
```
pip install seisbench
```
## Overview
SeisBench offers the abstract class `WaveformModel` that every SeisBench model should subclass. This class offers two core functions, `annotate` and `classify`. Both of the functions are automatically generated based on configurations and submethods implemented in the specific model.
The `SeisBenchModel` bridges the gap between the pytorch interface of the models and the obspy interface common in seismology. It automatically assembles obspy streams into pytorch tensors and reassembles the results into streams. It also takes care of batch processing. Computations can be run on GPU by simply moving the model to GPU.
