Update app.py

app.py

@@ -1,6 +1,9 @@
 import streamlit as st
 from PIL import Image, ImageDraw
 import numpy as np
+import torchaudio
+from audiocraft.models import MusicGen
+from audiocraft.data.audio import audio_write
 
 def greet(name):
     return "Saluuuuuuuut " + name + "! Monstre !"
@@ -14,10 +17,8 @@ if name:
     st.write("Output:")
     st.write(result)
 
-
-
     
-
+    
     # Sélection de l'image
     uploaded_image = st.file_uploader("Sélectionnez une image", type=["jpg", "png", "jpeg"])
 
@@ -27,3 +28,22 @@ if name:
 
         # Afficher l'image d'origine
         st.image(image, caption="Image d'origine", use_column_width=True)
+
+
+
+
+
+
+model = MusicGen.get_pretrained('melody')
+model.set_generation_params(duration=8)  # generate 8 seconds.
+
+descriptions = ['happy rock', 'energetic EDM', 'sad jazz']
+
+melody, sr = torchaudio.load('./assets/bach.mp3')
+# generates using the melody from the given audio and the provided descriptions.
+wav = model.generate_with_chroma(descriptions, melody[None].expand(3, -1, -1), sr)
+
+for idx, one_wav in enumerate(wav):
+    # Will save under {idx}.wav, with loudness normalization at -14 db LUFS.
+    audio_write(f'{idx}', one_wav.cpu(), model.sample_rate, strategy="loudness")
+