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)