Explaining food image predictions
You have a model that classifies food, and your task is to use LIME to identify the regions the model mostly focuses on while making its prediction for the image below.
The model responsible for predictions, the model_predict function and the sample image shown below are pre-loaded for you.
Questo esercizio fa parte del corso
Explainable AI in Python
Istruzioni dell'esercizio
- Create a LIME image explainer named
explainer. - Generate an
explanationfor themodel's prediction on the givenimage. - Extract the areas of interest from the
imagebased on themodel's explanation.
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
from lime import lime_image
np.random.seed(10)
# Create a LIME explainer
explainer = ____
# Generate the explanation
explanation = explainer.____(____, ____, hide_color=0, num_samples=50)
# Display the explanation
temp, _ = explanation.____(____, ____)
plt.imshow(temp)
plt.title('LIME Explanation')
plt.axis('off')
plt.show()