pop2piano_dev / app.py
susnato's picture
Create app.py
e9a98af
raw
history blame
5.53 kB
import os
import torch
import shutil
import librosa
import binascii
import warnings
import midi2audio
import pytube as pt # to download the youtube videos as audios
import gradio as gr
from transformers import Pop2PianoForConditionalGeneration, Pop2PianoProcessor
yt_video_dir = "./yt_dir"
outputs_dir = "./midi_wav_outputs"
os.makedirs(outputs_dir, exist_ok=True)
os.makedirs(yt_video_dir, exist_ok=True)
device = "cuda" if torch.cuda.is_available() else "cpu"
model = Pop2PianoForConditionalGeneration.from_pretrained("sweetcocoa/pop2piano").to(device)
processor = Pop2PianoProcessor.from_pretrained("sweetcocoa/pop2piano")
composers = model.generation_config.composer_to_feature_token.keys()
def get_audio_from_yt_video(yt_link):
try:
yt = pt.YouTube(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}")
filename = None
return filename, filename
def prepare_output_file(tokenizer_output):
# 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
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)
from IPython.display import Audio
return wav_output, wav_output, midi_output
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)
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"]
return prepare_output_file(tokenizer_output)
block = gr.Blocks()
with block:
gr.HTML(
"""
<div style="text-align: center; max-width: 700px; margin: 0 auto;">
<div
style="
display: inline-flex;
align-items: center;
gap: 0.8rem;
font-size: 1.75rem;
"
>
<h1 style="font-weight: 900; margin-bottom: 7px;">
Pop2piano
</h1>
</div>
<p style="margin-bottom: 10px; font-size: 94%">
A demo for Pop2Piano:Pop Audio-based Piano Cover Generation.<br>
Please select the composer(Arranger) and upload the pop audio or enter the YouTube link and then click Generate.
</p>
</div>
"""
)
with gr.Group():
with gr.Box():
with gr.Row().style(mobile_collapse=False, equal_height=True):
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")
yt_btn = gr.Button("Get Audio from the YT link(Press this before pressing Generate)")
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.Box():
with gr.Row().style(mobile_collapse=False, equal_height=True):
composer = gr.Dropdown(label="Arranger", choices=composers, value="composer1")
with gr.Row().style(mobile_collapse=False, equal_height=True):
btn = gr.Button("Generate")
with gr.Box():
with gr.Row().style(mobile_collapse=False, equal_height=True):
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)")
btn.click(inference, inputs=[file_uploaded, composer], outputs=[wav_output1, wav_output2, midi_output])
gr.Examples([
["./examples/custom_song.mp3", "composer1"],
["./examples/BornThisWay.mp3", "composer1"],
["./examples/Sk8erBoi.mp3", "composer2"],
],
fn=inference,
inputs=[file_uploaded, composer],
outputs=[wav_output1, wav_output2, midi_output],
cache_examples=True
)
gr.HTML(
"""
<div class="footer">
<p><a href="http://sweetcocoa.github.io/pop2piano_samples" style="text-decoration: underline;" target="_blank">Project Page</a>
</p>
</div>
"""
)
block.launch(debug=False)
shutil.rmtree("./midi_wav_outputs")