Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| import librosa | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| from matplotlib.animation import FuncAnimation | |
| import tempfile | |
| import os | |
| # Import custom visualizers | |
| from felguk import felguk_viz | |
| from result_video_audio_vizualizer import result_video_viz | |
| from piepy import piepy_viz | |
| from pyz import pyz_viz | |
| # List of visualizers | |
| VISUALIZERS = { | |
| "Waveform": lambda y, sr: librosa.display.waveshow(y, sr=sr), | |
| "Spectrogram": lambda y, sr: librosa.display.specshow(librosa.amplitude_to_db(np.abs(librosa.stft(y)), ref=np.max), sr=sr, x_axis='time', y_axis='log'), | |
| "Mel Spectrogram": lambda y, sr: librosa.display.specshow(librosa.feature.melspectrogram(y=y, sr=sr), sr=sr, x_axis='time', y_axis='mel'), | |
| "Chromagram": lambda y, sr: librosa.display.specshow(librosa.feature.chroma_stft(y=y, sr=sr), sr=sr, x_axis='time', y_axis='chroma'), | |
| "Felguk Visualizer": felguk_viz, | |
| "Result Video Visualizer": result_video_viz, | |
| "Piepy Visualizer": piepy_viz, | |
| "Pyz Visualizer": pyz_viz, | |
| "Tempogram": lambda y, sr: librosa.display.specshow(librosa.feature.tempogram(y=y, sr=sr)), | |
| "Spectral Contrast": lambda y, sr: librosa.display.specshow(librosa.feature.spectral_contrast(y=y, sr=sr), sr=sr, x_axis='time'), | |
| } | |
| # Function to generate a video | |
| def generate_video(y, sr, visualizer): | |
| fig, ax = plt.subplots(figsize=(10, 4)) | |
| def animate(i): | |
| ax.clear() | |
| visualizer(y[:i * 1000], sr) # Update visualization for each frame | |
| ax.set_title(f"Frame {i}") | |
| anim = FuncAnimation(fig, animate, frames=len(y) // 1000, interval=50) | |
| # Save the animation as a video file | |
| video_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") | |
| anim.save(video_file.name, writer="ffmpeg", fps=30) | |
| plt.close() | |
| return video_file.name | |
| # Streamlit app | |
| st.title("Audio Visualizer") | |
| st.write("Upload an audio file to visualize it in different ways.") | |
| # Upload audio file | |
| audio_file = st.file_uploader("Upload an audio file", type=["wav", "mp3", "ogg"]) | |
| if audio_file is not None: | |
| st.audio(audio_file, format='audio/wav') | |
| y, sr = librosa.load(audio_file, sr=None) | |
| # Select visualizer | |
| selected_viz = st.selectbox("Select a visualizer", list(VISUALIZERS.keys())) | |
| # Plot the selected visualizer | |
| st.write(f"### {selected_viz}") | |
| plt.figure(figsize=(10, 4)) | |
| VISUALIZERS[selected_viz](y, sr) | |
| plt.colorbar(format="%+2.0f dB") | |
| st.pyplot(plt) | |
| # Generate and return video | |
| if st.button("Generate Video"): | |
| video_path = generate_video(y, sr, VISUALIZERS[selected_viz]) | |
| st.video(video_path) | |
| with open(video_path, "rb") as file: | |
| st.download_button( | |
| label="Download Video", | |
| data=file, | |
| file_name="audio_visualization.mp4", | |
| mime="video/mp4" | |
| ) | |
| os.unlink(video_path) # Clean up the temporary file |