formatting and remove midi2audio

app.py

@@ -1,13 +1,15 @@
 import os
-import torch
-import librosa
 import binascii
 import warnings
-import midi2audio      # to convert midi to wav
+
+import torch
+import librosa
 import numpy as np
-import pytube as pt    # to download the youtube videos as audios
+import pytube as pt  # to download the youtube videos as audios
 import gradio as gr
-import soundfile as sf # to make the stereo mix
+import soundfile as sf  # to make the stereo mix
+
+from pytube.exceptions import VideoUnavailable
 from transformers import Pop2PianoForConditionalGeneration, Pop2PianoProcessor
 
 
@@ -28,37 +30,41 @@ def get_audio_from_yt_video(yt_link):
         t = yt.streams.filter(only_audio=True)
         filename = os.path.join(yt_video_dir, binascii.hexlify(os.urandom(8)).decode() + ".mp4")
         t[0].download(filename=filename)
-    except:
-        warnings.warn(f"Video Not Found at {yt_link}")
+    except VideoUnavailable as e:
+        warnings.warn(f"Video Not Found at {yt_link} ({e})")
         filename = None
-    
+
     return filename, filename
-    
+
+
 def inference(file_uploaded, composer):
     # to save the native sampling rate of the file, sr=None is used, but this can cause some silent errors where the
     # generated output will not be upto the desired quality. If that happens please consider switching sr to 44100 Hz.
-    waveform, sr = librosa.load(file_uploaded, sr=None) 
-    
+    waveform, sr = librosa.load(file_uploaded, sr=None)
+
     inputs = processor(audio=waveform, sampling_rate=sr, return_tensors="pt").to(device)
     model_output = model.generate(input_features=inputs["input_features"], composer=composer)
-    tokenizer_output = processor.batch_decode(token_ids=model_output.to("cpu"), feature_extractor_output=inputs.to("cpu"))["pretty_midi_objects"]
+    tokenizer_output = processor.batch_decode(
+        token_ids=model_output.to("cpu"), feature_extractor_output=inputs.to("cpu")
+    )["pretty_midi_objects"]
+
+    return prepare_output_file(tokenizer_output, sr)
 
-    return prepare_output_file(tokenizer_output, sr)    
 
-def prepare_output_file(tokenizer_output, sr):
+def prepare_output_file(tokenizer_output, sr:int):
     # Add some random values so that no two file names are same
     output_file_name = "output_" + binascii.hexlify(os.urandom(8)).decode()
     midi_output = os.path.join(outputs_dir, output_file_name + ".mid")
-        
-    # write the .mid file
+
+    # write the .mid and its wav files
     tokenizer_output[0].write(midi_output)
-    
-    # convert .mid file to .wav using `midi2audio`
-    wav_output = midi_output.replace(".mid", ".wav")
-    midi2audio.FluidSynth().midi_to_audio(midi_output, wav_output)
-    
+    midi_wav:np.ndarray = tokenizer_output[0].fluidsynth(sr)
+    wav_output:str = midi_output.replace(".mid", ".wav")
+    sf.write(wav_output, midi_wav, samplerate=sr)
+
     return wav_output, wav_output, midi_output
 
+
 def get_stereo(pop_path, midi, pop_scale=0.5):
     pop_y, sr = librosa.load(pop_path, sr=None)
     midi_y, _ = librosa.load(midi.name, sr=None)
@@ -68,10 +74,15 @@ def get_stereo(pop_path, midi, pop_scale=0.5):
     elif len(pop_y) < len(midi_y):
         pop_y = np.pad(pop_y, (0, -len(pop_y) + len(midi_y)))
     stereo = np.stack((midi_y, pop_y * pop_scale))
-    
-    stereo_mix_path = pop_path.replace("output", "output_stereo_mix") 
-    sf.write(file=stereo_mix_path, data=stereo.T, samplerate=sr, format="wav",)
-    
+
+    stereo_mix_path = pop_path.replace("output", "output_stereo_mix")
+    sf.write(
+        file=stereo_mix_path,
+        data=stereo.T,
+        samplerate=sr,
+        format="wav",
+    )
+
     return stereo_mix_path, stereo_mix_path
 
 
@@ -108,12 +119,20 @@ with block:
                 file_uploaded = gr.Audio(label="Upload an audio", type="filepath")
             with gr.Column():
                 with gr.Row():
-                    yt_link = gr.Textbox(label="Enter YouTube Link of the Video", autofocus=True, lines=3)
+                    yt_link = gr.Textbox(
+                        label="Enter YouTube Link of the Video", autofocus=True, lines=3
+                    )
                     yt_btn = gr.Button("Download Audio from YouTube Link", size="lg")
 
-                yt_audio_path = gr.Audio(label="Audio Extracted from the YouTube Video", interactive=False)
-                yt_btn.click(get_audio_from_yt_video, inputs=[yt_link], outputs=[yt_audio_path, file_uploaded])
-    
+                yt_audio_path = gr.Audio(
+                    label="Audio Extracted from the YouTube Video", interactive=False
+                )
+                yt_btn.click(
+                    get_audio_from_yt_video,
+                    inputs=[yt_link],
+                    outputs=[yt_audio_path, file_uploaded],
+                )
+
     with gr.Group():
         with gr.Column():
             composer = gr.Dropdown(label="Arranger", choices=composers, value="composer1")
@@ -123,32 +142,48 @@ with block:
             wav_output2 = gr.File(label="Download the Generated MIDI (.wav)")
             wav_output1 = gr.Audio(label="Listen to the Generated MIDI")
             midi_output = gr.File(label="Download the Generated MIDI (.mid)")
-            generate_btn.click(inference, 
-                               inputs=[file_uploaded, composer], 
-                               outputs=[wav_output1, wav_output2, midi_output])
-            
+            generate_btn.click(
+                inference,
+                inputs=[file_uploaded, composer],
+                outputs=[wav_output1, wav_output2, midi_output],
+            )
+
     with gr.Group():
         gr.HTML(
             """
             <div> <h3> <center> Get the Stereo Mix from the Pop Music and Generated MIDI </h3> </div>
             """
         )
-        pop_scale = gr.Slider(0, 1, value=0.5, label="Choose the ratio between Pop and MIDI", info="1.0 = Only Pop, 0.0=Only MIDI", interactive=True),
+        pop_scale = (
+            gr.Slider(
+                0,
+                1,
+                value=0.5,
+                label="Choose the ratio between Pop and MIDI",
+                info="1.0 = Only Pop, 0.0=Only MIDI",
+                interactive=True,
+            ),
+        )
         stereo_btn = gr.Button("Get Stereo Mix")
         with gr.Row():
             stereo_mix1 = gr.Audio(label="Listen to the Stereo Mix")
             stereo_mix2 = gr.File(label="Download the Stereo Mix")
-        
-        stereo_btn.click(get_stereo, inputs=[file_uploaded, wav_output2, pop_scale[0]], outputs=[stereo_mix1, stereo_mix2])
-                
+
+        stereo_btn.click(
+            get_stereo,
+            inputs=[file_uploaded, wav_output2, pop_scale[0]],
+            outputs=[stereo_mix1, stereo_mix2],
+        )
+
     with gr.Group():
-        gr.Examples([
-            ["./examples/custom_song.mp3", "composer1"],
-        ],
+        gr.Examples(
+            [
+                ["./examples/custom_song.mp3", "composer1"],
+            ],
             fn=inference,
             inputs=[file_uploaded, composer],
             outputs=[wav_output1, wav_output2, midi_output],
-            cache_examples=True
+            cache_examples=True,
         )
         gr.HTML(
             """
@@ -157,7 +192,7 @@ with block:
         </div>
         """
         )
-        
+
         gr.HTML(
             """
         <div class="footer">
@@ -169,4 +204,4 @@ with block:
         """
         )
 
-block.launch(debug=False)
+block.launch(debug=False)

requirements.txt

@@ -4,7 +4,6 @@ pretty-midi==0.2.9
 essentia==2.1b6.dev1034
 pyFluidSynth==1.3.0
 git+https://github.com/huggingface/transformers
-midi2audio
 pytube
 gradio
 resampy