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| 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']) | |
| 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() | |