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.
Deze oefening maakt deel uit van de cursus
Explainable AI in Python
Oefeninstructies
- 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.
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
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()