Second commit

metrics/audio_comparison_results_normalized.csv

+folder,mse_mixture_target,snr_mixture_target,sdr_mixture_target,mse_vocals_target,snr_vocals_target,sdr_vocals_target,snr_mixture_target_nonormalization
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+236,0.009277348,4.627535939216614,12.563825858774226,0.0678541,-4.013985991477966,14.43347847473677,-4.013985991477966

metrics/checkallnorm.csv

+folder,max_mixture_before,rms_mixture_before,max_target_before,rms_target_before,max_vocals_before,rms_vocals_before,max_mixture_after,rms_mixture_after,max_target_after,rms_target_after,max_vocals_after,rms_vocals_after
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+221,1.0,0.7984779,0.9999695,0.26655915,0.2561798,0.14755145,0.2561798,0.14755145,0.9999695,0.26655915,1.0,0.7984779
+222,1.0,0.8958758,0.9999695,0.23114307,0.22177124,0.15142082,0.22177124,0.15142082,0.9999695,0.23114307,1.0,0.8958758
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+230,1.0,0.9034575,1.0,0.17453949,0.29162598,0.17607535,0.29162598,0.17607535,1.0,0.17453949,1.0,0.9034575
+231,1.0,0.7408744,1.0,0.14465925,0.22711182,0.124446176,0.22711182,0.124446176,1.0,0.14465925,1.0,0.7408744
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+234,1.0,0.8327209,1.0,0.17052877,0.24266052,0.13855661,0.24266052,0.13855661,1.0,0.17052877,1.0,0.8327209
+235,1.0,0.950823,1.0,0.21684563,0.23652649,0.16192593,0.23652649,0.16192593,1.0,0.21684563,1.0,0.950823
+236,1.0,0.41858575,1.0,0.16409251,0.18333435,0.071942195,0.18333435,0.071942195,1.0,0.16409251,1.0,0.41858575

metrics/metricsresult.py

+import pandas as pd
+import matplotlib.pyplot as plt
+import numpy as np
+
+# Charger le fichier CSV
+df = pd.read_csv("audio_comparison_results_normalized.csv")
+
+# Calculer les moyennes pour les différentes métriques
+mse_vocals_target_avg = df["mse_vocals_target"].mean()
+snr_vocals_target_avg = df["snr_vocals_target"].mean()
+sdr_vocals_target_avg = df["sdr_vocals_target"].mean()
+
+mse_mixture_target_avg = df["mse_mixture_target"].mean()
+snr_mixture_target_avg = df["snr_mixture_target"].mean()
+sdr_mixture_target_avg = df["sdr_mixture_target"].mean()
+
+# Construire le tableau des valeurs
+metrics_table = [
+    ["DemucsV3", "SNR", "SDR", "MSE"],
+    ["vocals vs target", f"{snr_vocals_target_avg:.2f}", f"{sdr_vocals_target_avg:.2f}", f"{mse_vocals_target_avg:.2f}"],
+    ["mixture vs target", f"{snr_mixture_target_avg:.2f}", f"{sdr_mixture_target_avg:.2f}", f"{mse_mixture_target_avg:.2f}"]
+]
+
+# Créer la figure et l'axe pour le tableau
+fig, ax = plt.subplots(figsize=(8, 3))
+ax.axis('off')  # Masquer les axes
+
+# Créer le tableau
+ax.table(
+    cellText=metrics_table,
+    colLabels=None,
+    cellLoc='center',
+    loc='center',
+    colWidths=[0.2] * 4
+)
+
+# Sauvegarder l'image du tableau
+plt.savefig("metrics.jpg", bbox_inches='tight')
+plt.show()