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add transcribe button
Browse files- app.py +8 -4
- gradio_components/prediction.py +25 -1
app.py
CHANGED
@@ -2,7 +2,7 @@ import os
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import gradio as gr
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from gradio_components.prediction import predict
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theme = gr.themes.Glass(
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primary_hue="fuchsia",
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@@ -136,13 +136,17 @@ def UI():
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)
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with gr.Row():
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submit = gr.Button("Generate Music")
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-
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submit.click(
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fn=predict,
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inputs=[model_path, prompt, melody, duration, topk, topp, temperature,
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sample_rate],
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outputs=
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)
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gr.Examples(
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@@ -204,7 +208,7 @@ def UI():
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],
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inputs=[melody, difficulty, sample_rate, duration],
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label="Audio Examples",
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outputs=[
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# cache_examples=True,
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)
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demo.queue().launch()
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import gradio as gr
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from gradio_components.prediction import predict, transcribe
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theme = gr.themes.Glass(
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primary_hue="fuchsia",
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)
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with gr.Row():
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submit = gr.Button("Generate Music")
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output_audio = gr.Audio("listen to the generated music", type="filepath")
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with gr.Row():
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transcribe_button = gr.Button("Transcribe")
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d = gr.DownloadButton("Download the file", visible=False)
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transcribe_button.click(transcribe, inputs=[output_audio], outputs=d)
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submit.click(
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fn=predict,
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inputs=[model_path, prompt, melody, duration, topk, topp, temperature,
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sample_rate],
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outputs=output_audio
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)
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gr.Examples(
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],
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inputs=[melody, difficulty, sample_rate, duration],
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label="Audio Examples",
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outputs=[output_audio],
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# cache_examples=True,
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)
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demo.queue().launch()
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gradio_components/prediction.py
CHANGED
@@ -9,6 +9,9 @@ from audiocraft.models import MusicGen
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from tempfile import NamedTemporaryFile
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from pathlib import Path
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from transformers import AutoModelForSeq2SeqLM
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def load_model(version='facebook/musicgen-melody'):
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@@ -103,4 +106,25 @@ def predict(model_path, text, melody, duration, topk, topp, temperature, target_
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top_p=topp,
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temperature=temperature,
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gradio_progress=progress)
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return wavs[0]
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from tempfile import NamedTemporaryFile
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from pathlib import Path
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from transformers import AutoModelForSeq2SeqLM
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import basic_pitch
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import basic_pitch.inference
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from basic_pitch import ICASSP_2022_MODEL_PATH
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def load_model(version='facebook/musicgen-melody'):
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top_p=topp,
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temperature=temperature,
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gradio_progress=progress)
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return wavs[0]
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def transcribe(audio_path):
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# model_output, midi_data, note_events = predict("generated_0.wav")
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model_output, midi_data, note_events = basic_pitch.inference.predict(
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audio_path=audio_path,
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model_or_model_path=ICASSP_2022_MODEL_PATH,
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)
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with NamedTemporaryFile("wb", suffix=".mid", delete=False) as file:
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try:
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midi_data.write(file)
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print(f"midi file saved to {file.name}")
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except Exception as e:
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print(f"Error while writing midi file: {e}")
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raise e
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return gr.DownloadButton(
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value=file.name,
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label=f"Download MIDI file {file.name}",
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visible=True)
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