Change to gradio blocks, add radio for selecting the model

app.py

@@ -10,31 +10,63 @@ from inferencemodel import InferenceModel
 from utils import upload_audio
 
 SAMPLE_RATE = 16000
-SF2_PATH = 'SGM-v2.01-Sal-Guit-Bass-V1.3.sf2'
+SF2_PATH = "SGM-v2.01-Sal-Guit-Bass-V1.3.sf2"
 
 # Start inference model
-inference_model = InferenceModel('/home/user/app/checkpoints/mt3/', 'mt3')
+inference_model = InferenceModel("/home/user/app/checkpoints/mt3/", "mt3")
+current_model = "mt3"
+
+def change_model(model):
+    global current_model
+    if model == current_model:
+        return
+    global inference_model 
+    inference_model = InferenceModel("/home/user/app/checkpoints/mt3/", model)
+    current_model = model
 
 def inference(audio):
-  with open(audio, 'rb') as fd:
-      contents = fd.read()
+    with open(audio, "rb") as fd:
+        contents = fd.read()
 
-  audio = upload_audio(contents,sample_rate=16000)
+    audio = upload_audio(contents,sample_rate=16000)
 
-  est_ns = inference_model(audio)
-  
-  note_seq.sequence_proto_to_midi_file(est_ns, './transcribed.mid')
- 
-  return './transcribed.mid'
+    est_ns = inference_model(audio)
+    
+    note_seq.sequence_proto_to_midi_file(est_ns, "./transcribed.mid")
+    
+    return "./transcribed.mid"
   
-title = "MT3"
-description = "Gradio demo for MT3: Multi-Task Multitrack Music Transcription. To use it, simply upload your audio file, or click one of the examples to load them. Read more at the links below."
+title = "Transcribe music from YouTube videos using Transformers."
+description = """"
+Gradio demo for Music Transcription with Transformers Read more in the links below.
+"""
 
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2111.03017' target='_blank'>MT3: Multi-Task Multitrack Music Transcription</a> | <a href='https://github.com/magenta/mt3' target='_blank'>Github Repo</a></p>"
 
-examples=[['download.wav']]
+# Create a block object
+demo = gr.Blocks()
 
-gr.Interface(
+# Use your Block object as a context
+with demo:
+    gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>" 
+                + title 
+                + "</h1>")
+    gr.Markdown(description)
+    with gr.Box():
+        with gr.Row():
+            gr.Markdown("<h2>Select your model</h2>")
+            gr.Markdown("""
+                        The ismir2021 model transcribes piano only, with note velocities. 
+                        The mt3 model transcribes multiple simultaneous instruments, but without velocities."
+                        """)
+            model = gr.Radio(
+                ["mt3", "ismir2021"], label="What kind of model you want to use?"
+            )
+            model.change(fn=change_model, inputs=model, outputs=[])
+
+demo.launch()  
+  
+""" gr.Interface(
     inference, 
     gr.inputs.Audio(type="filepath", label="Input"), 
     [gr.outputs.File(label="Output")],
@@ -42,4 +74,4 @@ gr.Interface(
     description=description,
     article=article,
     examples=examples,
-    ).launch().queue()
+    ).launch().queue() """