run.py

import pickle
import datasets
from renumics import spotlight
import os
import pandas as pd

if __name__ == "__main__":
    cache_file = "dataset_cache.parquet"
    cache_file_enrichment="cifar100-enrichment-cv.parquet"
    cache_file_issues="sliceline.pkl"
    
    if os.path.exists(cache_file):
        # Load dataset from cache
        df = pd.read_parquet(cache_file) 
        

        
        print("Dataset loaded from cache.")
    else:
        # Load dataset using datasets.load_dataset()
        dataset = datasets.load_dataset("renumics/cifar100-enriched", split="test")
        print("Dataset loaded using datasets.load_dataset().")
        
        df = dataset.to_pandas()       
       

        # Save dataset to cache
        #save df as parquet
        df.to_parquet(cache_file)

        print("Dataset saved to cache.")

    #df_cv=pd.read_parquet(cache_file) 
     
    #with open(cache_file_issues, "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.sample(5000, random_state=1), port=7860, host="0.0.0.0", 
                    dtype={"image": spotlight.Image, "embedding_reduced": spotlight.Embedding}, allow_filebrowsing=False)
        view.close()