Skip to main content

Implementation of LIME focused on producing user-centric local explanations for image classifiers.

Project description

VisuaLIME

VisuaLIME is an implementation of LIME (Local Interpretable Model-Agnostic Explanations) [1] focused on producing visual local explanations for image classifiers.

In contrast to the reference implementation, VisuaLIME exclusively supports image classification and gives its users full control over the properties of the generated explanations. It was written to produce stable, reliable, and expressive explanations at scale.

VisuaLIME was created as part of the XAI Demonstrator project.

A full documentation is available on visualime.readthedocs.io.

Getting Started

💡 If you're new to LIME, you might want to check out the Grokking LIME talk/tutorial for a general introduction prior to diving into VisuaLIME.

To install VisuaLIME, run:

pip install visualime

VisuaLIME provides two functions that package its building blocks into a reference explanation pipeline:

import numpy as np
from visualime.explain import explain_classification, render_explanation

image = ...  # a numpy array of shape (width, height, 3) representing an RGB image

def predict_fn(images: np.ndarray) -> np.ndarray:
    # a function that takes a numpy array of shape (num_of_samples, width, height, 3)
    # representing num_of_samples RGB images and returns a numpy array of
    # shape (num_of_samples, num_of_classes) where each entry corresponds to the
    # classifiers output for the respective image
    predictions = ...
    return predictions

segment_mask, segment_weights = explain_classification(image, predict_fn)

explanation = render_explanation(
        image,
        segment_mask,
        segment_weights,
        positive="green",
        negative="red",
        coverage=0.2,
    )

For a full example, see the example notebook on GitHub.

References

[1] Ribeiro et al.: "Why Should I Trust You?": Explaining the Predictions of Any Classifier (arXiv:1602.04938, 2016)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

visualime-0.1.0.tar.gz (23.1 kB view hashes)

Uploaded Source

Built Distribution

visualime-0.1.0-py3-none-any.whl (21.5 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page