Update app.py
Browse files
app.py
CHANGED
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import os
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import gradio as gr
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from lib.infer import infer_audio
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from pydub import AudioSegment
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import
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#
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def process_audio(MODEL_NAME, SOUND_PATH, F0_CHANGE, F0_METHOD, MIN_PITCH, MAX_PITCH, CREPE_HOP_LENGTH, INDEX_RATE,
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FILTER_RADIUS, RMS_MIX_RATE, PROTECT, SPLIT_INFER, MIN_SILENCE, SILENCE_THRESHOLD, SEEK_STEP,
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KEEP_SILENCE, FORMANT_SHIFT, QUEFRENCY, TIMBRE, F0_AUTOTUNE, OUTPUT_FORMAT, upload_audio=None):
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@@ -45,30 +82,52 @@ def process_audio(MODEL_NAME, SOUND_PATH, F0_CHANGE, F0_METHOD, MIN_PITCH, MAX_P
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OUTPUT_FORMAT
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# Output the inferred audio file
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return inferred_audio
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# Gradio Blocks Interface
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with gr.Blocks(
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gr.Markdown("
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with gr.Row():
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with gr.Row():
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SOUND_PATH = gr.Textbox(label="Audio Path (Optional)", placeholder="Leave blank to upload audio")
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upload_audio = gr.File(label="Upload Audio", type='filepath', file_types=["audio"])
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with gr.Row():
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F0_CHANGE = gr.Number(label="Pitch Change (semitones)", value=0)
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F0_METHOD = gr.Dropdown(choices=["crepe", "harvest", "mangio-crepe", "rmvpe", "rmvpe+", "fcpe",
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"hybrid[mangio-crepe+rmvpe]", "hybrid[mangio-crepe+fcpe]",
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"hybrid[rmvpe+fcpe]", "hybrid[mangio-crepe+rmvpe+fcpe]"],
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label="F0 Method", value="fcpe")
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# Other Settings
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with gr.Row():
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MIN_PITCH = gr.Textbox(label="Min Pitch", value="50")
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MAX_PITCH = gr.Textbox(label="Max Pitch", value="1100")
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FILTER_RADIUS = gr.Number(label="Filter Radius", value=3)
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RMS_MIX_RATE = gr.Slider(label="RMS Mix Rate", minimum=0, maximum=1, value=0.25)
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PROTECT = gr.Slider(label="Protect", minimum=0, maximum=1, value=0.33)
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with gr.Accordion("Advanced Settings", open=False):
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SPLIT_INFER = gr.Checkbox(label="Enable Split Inference", value=False)
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MIN_SILENCE = gr.Number(label="Min Silence (ms)", value=500)
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QUEFRENCY = gr.Number(label="Quefrency", value=0)
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TIMBRE = gr.Number(label="Timbre", value=1)
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F0_AUTOTUNE = gr.Checkbox(label="Enable F0 Autotune", value=False)
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# Output Settings
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OUTPUT_FORMAT = gr.Dropdown(choices=["wav", "flac", "mp3"], label="Output Format", value="wav")
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run_button = gr.Button("Run Inference")
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# Audio Output
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output_audio = gr.Audio(label="Generated Audio", type='filepath')
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# Run the process_audio function on button click
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run_button.click(
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process_audio,
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inputs=[MODEL_NAME, SOUND_PATH, F0_CHANGE, F0_METHOD, MIN_PITCH, MAX_PITCH, CREPE_HOP_LENGTH, INDEX_RATE,
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)
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# Launch the Gradio app
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app.launch()
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import os
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import gradio as gr
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from pydub import AudioSegment
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from audio_separator.separator import Separator
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from lib.infer import infer_audio
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# Define a function to handle the entire separation process
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def separate_audio(input_audio, output_dir, model_voc_inst, model_deecho, model_back_voc):
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# Create output directory if it doesn't exist
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if not os.path.exists(output_dir):
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os.makedirs(output_dir)
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separator = Separator(output_dir=output_dir)
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# Define output files
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vocals = os.path.join(output_dir, 'Vocals.wav')
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instrumental = os.path.join(output_dir, 'Instrumental.wav')
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vocals_reverb = os.path.join(output_dir, 'Vocals (Reverb).wav')
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vocals_no_reverb = os.path.join(output_dir, 'Vocals (No Reverb).wav')
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lead_vocals = os.path.join(output_dir, 'Lead Vocals.wav')
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backing_vocals = os.path.join(output_dir, 'Backing Vocals.wav')
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# Splitting a track into Vocal and Instrumental
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separator.load_model(model_filename=model_voc_inst)
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voc_inst = separator.separate(input_audio)
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os.rename(os.path.join(output_dir, voc_inst[0]), instrumental) # Rename to “Instrumental.wav”
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os.rename(os.path.join(output_dir, voc_inst[1]), vocals) # Rename to “Vocals.wav”
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# Applying DeEcho-DeReverb to Vocals
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separator.load_model(model_filename=model_deecho)
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voc_no_reverb = separator.separate(vocals)
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os.rename(os.path.join(output_dir, voc_no_reverb[0]), vocals_no_reverb) # Rename to “Vocals (No Reverb).wav”
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os.rename(os.path.join(output_dir, voc_no_reverb[1]), vocals_reverb) # Rename to “Vocals (Reverb).wav”
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# Separating Back Vocals from Main Vocals
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separator.load_model(model_filename=model_back_voc)
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backing_voc = separator.separate(vocals_no_reverb)
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os.rename(os.path.join(output_dir, backing_voc[0]), backing_vocals) # Rename to “Backing Vocals.wav”
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os.rename(os.path.join(output_dir, backing_voc[1]), lead_vocals) # Rename to “Lead Vocals.wav”
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return instrumental, vocals, vocals_reverb, vocals_no_reverb, lead_vocals, backing_vocals
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# Main function to process audio (Inference)
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def process_audio(MODEL_NAME, SOUND_PATH, F0_CHANGE, F0_METHOD, MIN_PITCH, MAX_PITCH, CREPE_HOP_LENGTH, INDEX_RATE,
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FILTER_RADIUS, RMS_MIX_RATE, PROTECT, SPLIT_INFER, MIN_SILENCE, SILENCE_THRESHOLD, SEEK_STEP,
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KEEP_SILENCE, FORMANT_SHIFT, QUEFRENCY, TIMBRE, F0_AUTOTUNE, OUTPUT_FORMAT, upload_audio=None):
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OUTPUT_FORMAT
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)
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return inferred_audio
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# Gradio Blocks Interface with Tabs
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with gr.Blocks(title="Hex RVC") as app:
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gr.Markdown("# Hex RVC")
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with gr.Tab("Audio Separation"):
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with gr.Row():
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input_audio = gr.Audio(source="upload", type="filepath", label="Upload Audio File")
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output_dir = gr.Textbox(value="/content/output", label="Output Directory")
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with gr.Row():
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model_voc_inst = gr.Textbox(value='model_bs_roformer_ep_317_sdr_12.9755.ckpt', label="Vocal & Instrumental Model")
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model_deecho = gr.Textbox(value='UVR-DeEcho-DeReverb.pth', label="DeEcho-DeReverb Model")
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model_back_voc = gr.Textbox(value='mel_band_roformer_karaoke_aufr33_viperx_sdr_10.1956.ckpt', label="Backing Vocals Model")
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separate_button = gr.Button("Separate Audio")
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with gr.Row():
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instrumental_out = gr.Audio(label="Instrumental")
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vocals_out = gr.Audio(label="Vocals")
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vocals_reverb_out = gr.Audio(label="Vocals (Reverb)")
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vocals_no_reverb_out = gr.Audio(label="Vocals (No Reverb)")
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lead_vocals_out = gr.Audio(label="Lead Vocals")
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backing_vocals_out = gr.Audio(label="Backing Vocals")
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separate_button.click(
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separate_audio,
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inputs=[input_audio, output_dir, model_voc_inst, model_deecho, model_back_voc],
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outputs=[instrumental_out, vocals_out, vocals_reverb_out, vocals_no_reverb_out, lead_vocals_out, backing_vocals_out]
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)
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with gr.Tab("Inference"):
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with gr.Row():
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MODEL_NAME = gr.Textbox(label="Model Name", placeholder="Enter model name")
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SOUND_PATH = gr.Textbox(label="Audio Path (Optional)", placeholder="Leave blank to upload audio")
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upload_audio = gr.File(label="Upload Audio", type='filepath', file_types=["audio"])
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with gr.Row():
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F0_CHANGE = gr.Number(label="Pitch Change (semitones)", value=0)
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F0_METHOD = gr.Dropdown(choices=["crepe", "harvest", "mangio-crepe", "rmvpe", "rmvpe+", "fcpe",
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"hybrid[mangio-crepe+rmvpe]", "hybrid[mangio-crepe+fcpe]",
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"hybrid[rmvpe+fcpe]", "hybrid[mangio-crepe+rmvpe+fcpe]"],
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label="F0 Method", value="fcpe")
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with gr.Row():
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MIN_PITCH = gr.Textbox(label="Min Pitch", value="50")
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MAX_PITCH = gr.Textbox(label="Max Pitch", value="1100")
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FILTER_RADIUS = gr.Number(label="Filter Radius", value=3)
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RMS_MIX_RATE = gr.Slider(label="RMS Mix Rate", minimum=0, maximum=1, value=0.25)
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PROTECT = gr.Slider(label="Protect", minimum=0, maximum=1, value=0.33)
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with gr.Accordion("Advanced Settings", open=False):
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SPLIT_INFER = gr.Checkbox(label="Enable Split Inference", value=False)
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MIN_SILENCE = gr.Number(label="Min Silence (ms)", value=500)
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QUEFRENCY = gr.Number(label="Quefrency", value=0)
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TIMBRE = gr.Number(label="Timbre", value=1)
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F0_AUTOTUNE = gr.Checkbox(label="Enable F0 Autotune", value=False)
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OUTPUT_FORMAT = gr.Dropdown(choices=["wav", "flac", "mp3"], label="Output Format", value="wav")
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run_button = gr.Button("Run Inference")
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output_audio = gr.Audio(label="Generated Audio", type='filepath')
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run_button.click(
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process_audio,
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inputs=[MODEL_NAME, SOUND_PATH, F0_CHANGE, F0_METHOD, MIN_PITCH, MAX_PITCH, CREPE_HOP_LENGTH, INDEX_RATE,
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)
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# Launch the Gradio app
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app.launch()
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