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| import numpy as np | |
| import librosa | |
| from pydub import AudioSegment | |
| import gradio as gr | |
| def load_audio(file_path): | |
| audio, sr = librosa.load(file_path, sr=None) | |
| return audio, sr | |
| def get_segment(audio, sr): | |
| # Calculate onset envelope and detect onsets | |
| onset_env = librosa.onset.onset_strength(audio, sr=sr) | |
| onset_frames = librosa.onset.onset_detect(onset_envelope=onset_env, sr=sr, backtrack=True) | |
| # If no onsets are detected, return a segment from the beginning | |
| if len(onset_frames) == 0: | |
| return audio[:2048] # Return the first segment of 1 second | |
| # Extract the pitch and dynamic range | |
| pitches, magnitudes = librosa.piptrack(y=audio, sr=sr) | |
| dynamic_range = np.max(audio) - np.min(audio) | |
| # Calculate energy over time | |
| energy = np.array([np.sum(np.abs(audio[i:i + 2048]**2)) for i in range(0, len(audio), 2048)]) | |
| # Threshold to consider a segment musically relevant | |
| energy_threshold = np.mean(energy) + np.std(energy) | |
| # Find onsets that exceed the energy threshold | |
| relevant_onsets = [f for f in onset_frames if energy[f] > energy_threshold] | |
| # If no relevant onsets are found, fall back to the first detected onset | |
| if len(relevant_onsets) == 0: | |
| start_frame = onset_frames[0] | |
| else: | |
| start_frame = relevant_onsets[0] | |
| start_sample = librosa.frames_to_samples(start_frame) | |
| # Define a segment length in samples (1 second) | |
| segment_length = sr # 1 second segment | |
| end_sample = min(start_sample + segment_length, len(audio)) | |
| # Optionally add overlap for smoother transitions | |
| overlap_length = int(sr * 0.5) # 0.5 seconds overlap | |
| overlap_start = max(start_sample - overlap_length, 0) | |
| # Return the selected segment with some context | |
| segment_with_context = audio[overlap_start:end_sample] | |
| return segment_with_context | |
| def extend_music(file_path, added_minutes): | |
| audio, sr = load_audio(file_path) | |
| # Extract a segment from the audio | |
| segment = get_segment(audio, sr) | |
| # Convert the original audio to pydub format for manipulation | |
| original_audio_segment = AudioSegment.from_file(file_path) | |
| # Calculate the original duration in seconds | |
| original_duration_seconds = len(audio) / sr | |
| # Calculate the new duration in seconds | |
| new_duration_seconds = original_duration_seconds + (added_minutes * 60) | |
| # Calculate how many times to repeat the segment based on new duration | |
| num_repeats = int(new_duration_seconds // (len(segment) / sr)) | |
| # Create the extended audio by repeating the segment | |
| extended_audio = original_audio_segment + segment.tobytes() * num_repeats | |
| return extended_audio | |
| def process_audio(file, added_minutes): | |
| extended_audio = extend_music(file, added_minutes) | |
| output_path = "extended_audio.mp3" | |
| extended_audio.export(output_path, format="mp3") | |
| return output_path | |
| # Create the Gradio interface | |
| iface = gr.Interface( | |
| fn=process_audio, | |
| inputs=[ | |
| gr.inputs.Audio(source="upload", type="filepath"), | |
| gr.inputs.Slider(minimum=0, maximum=10, default=1, label="Additional Minutes") # Adjust max as needed | |
| ], | |
| outputs=gr.outputs.Audio(type="file"), | |
| title="Advanced Music Extender", | |
| description="Upload an audio file, and this app will extend the music by cutting and appending a segment based on advanced audio features. Choose additional minutes to extend the audio duration." | |
| ) | |
| iface.launch() | |