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import gradio as gr
import numpy as np
from moviepy.editor import AudioFileClip, ImageClip, CompositeVideoClip
import matplotlib.pyplot as plt
import tempfile
import os
def create_waveform_video(image, audio_path):
# Save uploaded image temporarily
image_path = tempfile.mktemp(suffix=".png")
video_path = tempfile.mktemp(suffix=".mp4")
waveform_path = tempfile.mktemp(suffix=".png")
image.save(image_path)
# Load audio
audio_clip = AudioFileClip(audio_path)
# Generate waveform as an image
waveform = audio_clip.to_soundarray(fps=22050).mean(axis=1) # Convert stereo to mono
waveform = np.interp(waveform, (waveform.min(), waveform.max()), (-1, 1)) # Normalize
# Plot waveform using matplotlib
plt.figure(figsize=(10, 2))
plt.plot(waveform, color="blue")
plt.axis("off")
plt.savefig(waveform_path, bbox_inches="tight", pad_inches=0)
plt.close()
# Load image and create a video clip of the same duration as the audio
img_clip = ImageClip(image_path).set_duration(audio_clip.duration).resize(height=720)
waveform_clip = ImageClip(waveform_path).set_duration(audio_clip.duration).resize(width=img_clip.w)
waveform_clip = waveform_clip.set_position(("center", img_clip.h - waveform_clip.h - 20))
# Combine image, waveform overlay, and audio into one video
final_clip = CompositeVideoClip([img_clip, waveform_clip.set_opacity(0.7)]).set_audio(audio_clip)
final_clip.write_videofile(video_path, codec="libx264", fps=24)
# Cleanup temporary files
os.remove(image_path)
os.remove(waveform_path)
return video_path
iface = gr.Interface(
fn=create_waveform_video,
inputs=[
gr.Image(type="pil", label="Upload Image"),
gr.Audio(type="filepath", label="Upload Audio")
],
outputs=gr.Video(label="Generated Video"),
title="Image + Audio to Video with Waveform Overlay"
)
iface.launch()
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