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import librosa
import numpy as np
import soundfile as sf
import gradio as gr
import argparse
def auto_tune(audio_path, target_pitch=440.0):
# Load the audio file
y, sr = librosa.load(audio_path)
# Extract pitch using librosa's piptrack method
pitches, magnitudes = librosa.core.piptrack(y=y, sr=sr)
# Convert 2D pitch and magnitude arrays to 1D
pitches = pitches[magnitudes > np.median(magnitudes)]
# Filter out zero values (unvoiced frames)
pitches = pitches[pitches > 0]
if len(pitches) == 0:
raise ValueError("No pitch detected in the audio. Ensure the input audio contains a detectable pitch.")
# Calculate the tuning ratio to shift the pitch to the target pitch
median_pitch = np.median(pitches)
tuning_ratio = target_pitch / median_pitch
# Adjust the pitch of the audio
y_tuned = librosa.effects.pitch_shift(y, sr, n_steps=np.log2(tuning_ratio))
return y_tuned, sr
def run_gradio():
def gradio_interface(audio, target_pitch):
if audio is None:
return "Error: No audio input provided."
try:
# Save the input audio file
audio_path = "input_audio.wav"
sf.write(audio_path, audio[1], audio[0])
# Apply auto-tune
y_tuned, sr = auto_tune(audio_path, target_pitch=target_pitch)
# Return the tuned audio to Gradio for playback
return (sr, y_tuned)
except Exception as e:
return f"Error occurred: {str(e)}"
iface = gr.Interface(
fn=gradio_interface,
inputs=[gr.Audio(type="numpy"), gr.Number(value=440.0, label="Target Pitch")],
outputs=gr.Audio(type="numpy", label="Tuned Audio"),
title="Auto-Tune Voice",
description="Upload or record your voice and apply auto-tune.",
)
iface.launch()
if __name__ == "__main__":
run_gradio()
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