Update app.py

app.py

@@ -3,13 +3,16 @@ import gradio as gr
 from scipy.io.wavfile import write
 
 
-def separate_audio(audio):
+def inference(audio):
     os.makedirs("out", exist_ok=True)
-    write('test.wav', audio[0], audio[1])
-    os.system("python3 -m demucs.separate -n htdemucs --two-stems=vocals -d cpu test.wav -o out")
-    vocals_file = "./out/htdemucs/test/vocals.wav"
-    instrumental_file = "./out/htdemucs/test/no_vocals.wav"
-    return vocals_file, instrumental_file
+    vocals_files = []
+    instrumental_files = []
+    for audio_file in audio:
+        write('test.wav', audio_file[0], audio_file[1])
+        os.system("python3 -m demucs.separate -n htdemucs --two-stems=vocals -d cpu test.wav -o out")
+        vocals_files.append("./out/htdemucs/test/vocals.wav")
+        instrumental_files.append("./out/htdemucs/test/no_vocals.wav")
+    return vocals_files, instrumental_files
 
 
 def download_file(filepath):
@@ -18,11 +21,11 @@ def download_file(filepath):
     return file_bytes
 
 
-title = "Demucs Music Source Separation (v4)"
+title = "Source Separation (v4)"
 description = "This is the latest 'bleeding edge version' which enables the new v4 Hybrid Transformer model. <br> for this space, 2 stem separation (Karaoke Mode) is enabled and CPU mode which has been optimized for best quality & processing time. <p>| Gradio demo for Demucs(v4): Music Source Separation in the Waveform Domain. To use it, simply upload your audio, or click one of the examples to load them. Read more at the links below.</p>"
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1911.13254' target='_blank'>Music Source Separation in the Waveform Domain</a> | <a href='https://github.com/facebookresearch/demucs' target='_blank'>Github Repo</a> | <a href='https://www.thafx.com' target='_blank'>//THAFX</a></p>"
 
-audio_input = gr.inputs.Audio(label="Input")
+audio_input = gr.inputs.Audio(label="Input", type="file", multiple=True)
 vocals_output = gr.outputs.Audio(label="Vocals", type="file", process=download_file)
 instrumental_output = gr.outputs.Audio(label="No Vocals / Instrumental", type="file", process=download_file)
 
@@ -30,7 +33,7 @@ examples = [['test.mp3']]
 
 # Create the Gradio interface
 gr.Interface(
-    fn=separate_audio,
+    fn=inference,
     inputs=audio_input,
     outputs=[vocals_output, instrumental_output],
     title=title,