TensorFlow Extended visualizers for Streamlit apps
Project description
streamlit-tfx: TensorFlow Extended visualizers for Streamlit apps
streamlit-tfx
provides utilities for visualizing TensorFlow Extended
artifacts in Streamlit apps.
🌱 Just sprouting!
This project is in the very beginning stages of development. It's not well tested and is only intended to be used as a demo.
Installation
pip install streamlit-tfx
Getting started
import streamlit_tfx as st_tfx
st_tfx.display(item)
st_tfx.display_statistics(statistics)
st_tfx.display_schema(schema)
st_tfx.display_anomalies(anomalies)
st_tfx.display_eval_result_plot(eval_result)
st_tfx.display_eval_result_slicing_attributions(eval_result)
st_tfx.display_eval_result_slicing_metrics(eval_result)
st_tfx.display_eval_results_time_series(eval_results)
Most artifacts in tests/artifacts/
were generated by running the TFX Keras Component tutorial.
The anomalies artifact with anomalies was generated by running the TensorFlow Model Analysis tutorial.
🚀 Inspired by spacy-streamlit and streamlit-player.
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