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# app.py | |
# ============= | |
# This is a complete app.py file for a Gradio application that allows users to upload an audio file and generate a video with frequency visualization. | |
import gradio as gr | |
import numpy as np | |
import matplotlib.pyplot as plt | |
import librosa | |
import librosa.display | |
import os | |
import moviepy.video.io.ImageSequenceClip | |
# Function to generate frequency visualization frames from audio | |
def generate_frequency_visualization(audio_path): | |
try: | |
# Load the audio file | |
y, sr = librosa.load(audio_path, sr=None) | |
print(f"Loaded audio file with sampling rate: {sr}, and duration: {librosa.get_duration(y=y, sr=sr)} seconds.") | |
if sr == 0 or len(y) == 0: | |
raise ValueError("Invalid audio file: sampling rate or audio data is zero.") | |
# Perform Short-Time Fourier Transform (STFT) | |
n_fft = 2048 # Ensure n_fft is set to a valid number | |
hop_length = 512 # Ensure hop_length is set to a valid number | |
D = librosa.amplitude_to_db(np.abs(librosa.stft(y, n_fft=n_fft, hop_length=hop_length)), ref=np.max) | |
# Create a directory to save the frames | |
os.makedirs('frames', exist_ok=True) | |
# Generate and save each frame | |
for i in range(D.shape[1]): # Iterate over columns of D (time frames) | |
plt.figure(figsize=(10, 6)) | |
librosa.display.specshow(D[:, i].reshape(-1, 1), sr=sr, x_axis='time', y_axis='log', hop_length=hop_length, cmap='viridis') | |
plt.axis('off') | |
plt.savefig(f'frames/frame_{i:04d}.png', bbox_inches='tight', pad_inches=0) | |
plt.close() | |
print(f"Generated {D.shape[1]} frames for visualization.") | |
return 'frames' | |
except Exception as e: | |
print(f"Error generating frequency visualization: {e}") | |
# Fallback: Generate a default visualization | |
generate_default_visualization() | |
return 'frames' | |
# Function to generate a default visualization | |
def generate_default_visualization(): | |
# Create a directory to save the frames | |
os.makedirs('frames', exist_ok=True) | |
# Generate and save default frames | |
for i in range(10): # Generate 10 default frames | |
plt.figure(figsize=(10, 6)) | |
plt.plot(np.sin(np.linspace(0, 10, 100)) * (i + 1)) | |
plt.axis('off') | |
plt.savefig(f'frames/frame_{i:04d}.png', bbox_inches='tight', pad_inches=0) | |
plt.close() | |
# Function to create a video from the generated frames | |
def create_video_from_frames(frames_directory): | |
try: | |
# Get the list of frame files | |
frame_files = [os.path.join(frames_directory, f) for f in os.listdir(frames_directory) if f.endswith('.png')] | |
frame_files.sort() | |
if not frame_files: | |
raise ValueError("No frames found to create the video.") | |
# Create a video from the frames | |
clip = moviepy.video.io.ImageSequenceClip.ImageSequenceClip(frame_files, fps=10) # Set fps to 10 for better visibility | |
video_path = 'output_video.mp4' | |
clip.write_videofile(video_path, codec='libx264') | |
print(f"Video created with {len(frame_files)} frames.") | |
return video_path | |
except Exception as e: | |
print(f"Error creating video from frames: {e}") | |
return None | |
# Gradio interface function | |
def process_audio(audio): | |
audio_path = audio | |
frames_directory = generate_frequency_visualization(audio_path) | |
video_path = create_video_from_frames(frames_directory) | |
return video_path | |
# Create the Gradio interface with explanations and recommendations | |
iface = gr.Interface( | |
fn=process_audio, | |
inputs=gr.Audio(type="filepath", label="Upload Audio File"), | |
outputs=gr.Video(label="Generated Video"), | |
title="Audio Frequency Visualization", | |
description="Upload an audio file to generate a video with frequency visualization. " | |
"Supported file types: WAV, MP3, FLAC. " | |
"Recommended file duration: 10 seconds to 5 minutes. " | |
"If the file is invalid or cannot be processed, a default visualization will be generated.", | |
) | |
# Launch the Gradio interface | |
if __name__ == "__main__": | |
iface.launch() | |
# Dependencies | |
# ============= | |
# The following dependencies are required to run this app: | |
# - librosa | |
# - numpy | |
# - matplotlib | |
# - moviepy | |