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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="sliceguard-issues.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
df.to_parquet(cache_file)
print("Dataset saved to cache.")
df_cv=pd.read_parquet(cache_file_enrichment)
df = pd.concat([df, df_cv], axis=1)
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, issues=issues, port=7860, host="0.0.0.0", layout="sliceguard-layout.json",
dtype={"image": spotlight.Image, "embedding_reduced": spotlight.Embedding}, allow_filebrowsing=False)
view.close()