SeismoAI Model module - noise classifier for seismic traces
Project description
seismoai-model-mlops
SeismoAI Model Module — A noise classifier for seismic traces built on the Utah FORGE dataset.
Install
pip install seismoai-model-mlops
What it does
This module is part of the SeismoAI library. It trains a Random Forest classifier to detect good, noisy, and dead seismic traces.
Functions
extract_features(traces)— Extracts 6 statistical features from each tracetrain_classifier(traces, labels)— Trains a Random Forest on QC labelspredict_traces(traces, model_dict)— Predicts labels for new traces
Usage
from seismoai_model import extract_features, train_classifier, predict_traces
import numpy as np
traces = np.random.randn(30, 4001).astype(np.float32)
labels = ['good'] * 15 + ['noisy'] * 15
model_dict = train_classifier(traces, labels)
preds, probs = predict_traces(traces[:5], model_dict)
print(preds)
Author
Qurat UI Ain and Malaika Saeed — MLOps Course, SeismoAI Group Project
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