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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() |