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import numpy as np
from lime import lime_image
from skimage.segmentation import mark_boundaries
explainer = lime_image.LimeImageExplainer()
def explain_with_lime(model, img_array):
def predict_fn(images): return model.predict(np.array(images), verbose=0)
explanation = explainer.explain_instance(
image=img_array,
classifier_fn=predict_fn,
top_labels=1,
hide_color=0,
num_samples=1000
)
temp, mask = explanation.get_image_and_mask(
label=explanation.top_labels[0],
positive_only=True,
num_features=10,
hide_rest=False
)
return mark_boundaries(temp, mask)
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