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import streamlit as st
import whisper
from TTS.api import TTS
from moviepy.editor import VideoFileClip, AudioFileClip
import os
from tempfile import NamedTemporaryFile
# Page config
st.set_page_config(page_title="AI Voiceover Generator", layout="centered")
st.title("🎤 AI Voiceover + Subtitle Enhancer")
# Load models
@st.cache_resource
def load_whisper_model():
return whisper.load_model("small")
@st.cache_resource
def load_tts_model():
return TTS(model_name="tts_models/en/ljspeech/tacotron2-DDC", progress_bar=False, gpu=False)
whisper_model = load_whisper_model()
tts = load_tts_model()
# Upload video
video_file = st.file_uploader("Upload a short video clip (MP4 preferred)", type=["mp4", "mov", "avi"])
if video_file:
with NamedTemporaryFile(delete=False, suffix=".mp4") as tmp_video:
tmp_video.write(video_file.read())
tmp_video_path = tmp_video.name
st.video(tmp_video_path)
# Extract audio
video = VideoFileClip(tmp_video_path)
audio_path = tmp_video_path.replace(".mp4", ".wav")
video.audio.write_audiofile(audio_path)
# Transcribe
st.info("Transcribing using Whisper...")
result = whisper_model.transcribe(audio_path)
st.subheader("📝 Detected Speech")
st.write(result["text"])
# User input for voiceover
custom_text = st.text_area("Enter your custom voiceover text:", "Here’s my voiceover explaining the video...")
if st.button("Generate AI Voiceover"):
voice_output_path = audio_path.replace(".wav", "_ai_voice.wav")
tts.tts_to_file(text=custom_text, file_path=voice_output_path)
st.audio(voice_output_path)
# Replace original audio with new one
final_video = video.set_audio(AudioFileClip(voice_output_path))
final_path = tmp_video_path.replace(".mp4", "_final.mp4")
final_video.write_videofile(final_path, codec="libx264", audio_codec="aac")
with open(final_path, "rb") as f:
st.download_button(label="📥 Download Final Video", data=f, file_name="final_ai_video.mp4")
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