import pickle import datasets from renumics import spotlight import os if __name__ == "__main__": cache_file = "dataset_cache.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.") df = dataset.to_pandas() df_show = df.drop(columns=['embedding', 'probabilities']) 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)