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Update app.py
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app.py
CHANGED
@@ -4,71 +4,48 @@ import gradio as gr
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import librosa
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def binauralize(audio_file, simulate_rotation, rotation_speed, auto_rotation):
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Simulate a binaural (stereo) effect by applying a dynamic panning effect
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to an input audio file. No HRIR files are required.
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If auto_rotation is enabled, AI beat detection (via librosa) is used to
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determine the rotation speed based on the tempo of the audio.
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Parameters:
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audio_file (str): Path to input audio file (mono or stereo).
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simulate_rotation (bool): If True, apply a dynamic rotation (panning) effect.
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rotation_speed (float): Speed of the rotation effect (in Hz).
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auto_rotation (bool): If True, auto-detect rotation speed using AI beat detection.
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Returns:
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output_file (str): Path to the output stereo audio file.
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status (str): Status message.
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"""
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try:
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audio, sr = sf.read(audio_file)
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except Exception as e:
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return None, f"Error reading input audio file: {e}"
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# If the audio is stereo, convert to mono by averaging channels
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if audio.ndim > 1:
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audio = np.mean(audio, axis=1)
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# If auto_rotation is enabled, use librosa to detect tempo and adjust rotation speed.
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if auto_rotation:
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try:
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audio_float = audio.astype(np.float32)
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tempo, _ = librosa.beat.beat_track(y=audio_float, sr=sr)
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tempo = float(tempo)
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rotation_speed = tempo / 60.0
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status_msg = f"Auto rotation enabled: Detected tempo = {tempo:.1f} BPM, setting rotation speed = {rotation_speed:.3f} Hz."
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except Exception as e:
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status_msg = f"Auto rotation failed, using user provided rotation speed. Error: {e}"
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else:
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status_msg = "Using user provided rotation speed."
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t = np.arange(len(audio)) / sr
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if simulate_rotation:
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angle = 2 * np.pi * rotation_speed * t
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# Constant power panning: left uses cosine, right uses sine.
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left = np.cos(angle) * audio
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right = np.sin(angle) * audio
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else:
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# If rotation is not enabled, duplicate the audio to both channels.
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left = audio
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right = audio
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# Combine the channels into a stereo signal.
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binaural_audio = np.stack((left, right), axis=-1)
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# Normalize to prevent clipping.
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max_val = np.max(np.abs(binaural_audio))
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if max_val > 0:
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binaural_audio = binaural_audio / max_val
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# Save the output to a WAV file.
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output_file = "output_binaural.wav"
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try:
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sf.write(output_file, binaural_audio, sr)
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@@ -77,7 +54,6 @@ def binauralize(audio_file, simulate_rotation, rotation_speed, auto_rotation):
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return output_file, f"Binaural conversion complete! {status_msg}"
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# Create an enhanced UI using Gradio Blocks and Tabs.
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with gr.Blocks(title="SonicOrbit", css="""
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/* Custom CSS to enhance spacing and font styling */
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.title { font-size: 2.5em; font-weight: bold; text-align: center; margin-bottom: 0.5em; }
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import librosa
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def binauralize(audio_file, simulate_rotation, rotation_speed, auto_rotation):
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try:
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audio, sr = sf.read(audio_file)
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except Exception as e:
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return None, f"Error reading input audio file: {e}"
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if audio.ndim > 1:
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audio = np.mean(audio, axis=1)
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if auto_rotation:
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try:
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audio_float = audio.astype(np.float32)
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tempo, _ = librosa.beat.beat_track(y=audio_float, sr=sr)
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tempo = float(tempo)
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rotation_speed = tempo / 60.0
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status_msg = f"Auto rotation enabled: Detected tempo = {tempo:.1f} BPM, setting rotation speed = {rotation_speed:.3f} Hz."
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except Exception as e:
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status_msg = f"Auto rotation failed, using user provided rotation speed. Error: {e}"
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else:
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status_msg = "Using user provided rotation speed."
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t = np.arange(len(audio)) / sr
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if simulate_rotation:
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angle = 2 * np.pi * rotation_speed * t
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left = np.cos(angle) * audio
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right = np.sin(angle) * audio
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else:
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left = audio
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right = audio
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binaural_audio = np.stack((left, right), axis=-1)
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max_val = np.max(np.abs(binaural_audio))
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if max_val > 0:
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binaural_audio = binaural_audio / max_val
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output_file = "output_binaural.wav"
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try:
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sf.write(output_file, binaural_audio, sr)
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return output_file, f"Binaural conversion complete! {status_msg}"
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with gr.Blocks(title="SonicOrbit", css="""
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/* Custom CSS to enhance spacing and font styling */
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.title { font-size: 2.5em; font-weight: bold; text-align: center; margin-bottom: 0.5em; }
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