%run compute_quantile.py ../audio_test_article/*/*

import sklearn
import sklearn.metrics

df = pd.read_pickle("results_all_article_vit.pkl")
df = df.dropna()

df['groundtrue'] = df['file'].str.contains("-1.WAV")
df['groundtrue'].sum()
df['sess'] = df['file'].str.split("/", expand=True)[3]
df['lot'] = df['file'].str.split("/", expand=True)[2]

acc = sklearn.metrics.accuracy_score(df['groundtrue'], df['prediction']>0.5)

acc = sklearn.metrics.recall_score(df['groundtrue']==True, df['prediction']>0.5)
rec = sklearn.metrics.recall_score(df['groundtrue']==True, df['prediction']>0.5)
prec = sklearn.metrics.precision_score(df['groundtrue']==True, df['prediction']>0.5)

acc, prec, rec