run.py

import pickle
import datasets
from renumics import spotlight
import os

if __name__ == "__main__":
    cache_file = "dataset_cache.pkl"
    issue_cache_file="sliceline.pkl"
    if os.path.exists(cache_file):
        # Load dataset from cache
        with open(cache_file, "rb") as file:
            dataset = pickle.load(file)
        print("Dataset loaded from cache.")
    else:
        # Load dataset using datasets.load_dataset()
        dataset = datasets.load_dataset("renumics/cifar100-enriched", split="train")
        print("Dataset loaded using datasets.load_dataset().")

        # Save dataset to cache
        with open(cache_file, "wb") as file:
            pickle.dump(dataset, file)

        print("Dataset saved to cache.")
    
    with open(issue_cache_file, "rb") as issue_file:
         issues = pickle.load(issue_file)

    df = dataset.to_pandas()
    df_show = df.drop(columns=['embedding', 'probabilities'])
    while True:
        view = spotlight.show(df_show, port=7860, host="0.0.0.0", issues=issues,
                    dtype={"image": spotlight.Image, "embedding_reduced": spotlight.Embedding}, allow_filebrowsing=False)
        view.close()