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| import streamlit as st | |
| import whisper | |
| from TTS.api import TTS | |
| from moviepy.editor import VideoFileClip, AudioFileClip, CompositeAudioClip | |
| import os | |
| from tempfile import NamedTemporaryFile | |
| import torchaudio | |
| # Page config | |
| st.set_page_config(page_title="AI Voiceover Generator V2", layout="centered") | |
| st.title("🎤 AI Voiceover V2: Replace One Speaker Only") | |
| # Load models | |
| def load_whisper_model(): | |
| return whisper.load_model("small") | |
| 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"]) | |
| # Custom voiceover input | |
| custom_text = st.text_area("Enter your custom voiceover text to replace one speaker:", result["text"]) | |
| if st.button("Replace Only One Speaker's Voice"): | |
| # Generate new voiceover from custom text | |
| ai_voice_path = audio_path.replace(".wav", "_ai_voice.wav") | |
| tts.tts_to_file(text=custom_text, file_path=ai_voice_path) | |
| st.audio(ai_voice_path) | |
| # Load original audio | |
| original_audio, sr = torchaudio.load(audio_path) | |
| ai_audio, _ = torchaudio.load(ai_voice_path) | |
| # Trim or pad AI voice to match duration (for demo purposes) | |
| if ai_audio.shape[1] < original_audio.shape[1]: | |
| diff = original_audio.shape[1] - ai_audio.shape[1] | |
| ai_audio = torchaudio.functional.pad(ai_audio, (0, diff)) | |
| else: | |
| ai_audio = ai_audio[:, :original_audio.shape[1]] | |
| # Mix original and AI audio (simulating voice replacement, basic blend) | |
| # NOTE: This does NOT perform speaker diarization — it's a placeholder | |
| mixed_audio = (original_audio * 0.4) + (ai_audio * 0.6) | |
| mixed_path = audio_path.replace(".wav", "_mixed.wav") | |
| torchaudio.save(mixed_path, mixed_audio, sr) | |
| # Final video | |
| final_video = video.set_audio(AudioFileClip(mixed_path)) | |
| final_path = tmp_video_path.replace(".mp4", "_final_v2.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 with Mixed Voiceover", data=f, file_name="final_ai_video_v2.mp4") | |