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import gradio as gr |
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import torch |
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import whisper |
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from moviepy.editor import AudioFileClip, ColorClip, concatenate_videoclips |
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from moviepy.video.VideoClip import TextClip |
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def generate_video(audio_path, language, lag, progress=gr.Progress(track_tqdm=True)): |
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progress(0.0, "Transcribing audio...") |
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result = model.transcribe(audio_path, language=language) |
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progress(0.30, "Audio transcribed!") |
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clips = [] |
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total_segments = len(result["segments"]) |
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running_progress = 0.0 |
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current_time = 0.0 |
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for segment in result["segments"]: |
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running_progress += 0.4 / total_segments |
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if segment["start"] > current_time: |
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clips.append( |
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ColorClip((1280, 720), color=(0, 0, 0)).set_duration( |
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segment["start"] - current_time |
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) |
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) |
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text_clip = ( |
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TextClip( |
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segment["text"], |
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fontsize=24, |
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font="Arial", |
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color="white", |
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bg_color="black", |
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size=(1280, 720), |
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) |
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.set_duration(segment["end"] - segment["start"]) |
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.set_start(segment["start"]) |
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) |
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clips.append(text_clip) |
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current_time = segment["end"] |
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progress(min(0.3 + running_progress, 0.7), "Generating video frames...") |
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if lag > 0: |
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clips.insert(0, ColorClip((1280, 720), color=(0, 0, 0)).set_duration(lag)) |
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progress(0.7, "Video frames generated!") |
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progress(0.75, "Concatenating video clips...") |
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video = concatenate_videoclips(clips, method="compose") |
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progress(0.85, "Adding audio to video...") |
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video = video.set_audio(AudioFileClip(audio_path)) |
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progress(0.90, "Exporting video...") |
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output_path = "./transcribed_video.mp4" |
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video.write_videofile(output_path, fps=6, codec="libx264", audio_codec="aac") |
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progress(1.0, "Video exported!") |
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return output_path |
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if __name__ == "__main__": |
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DEVICE = "cuda" if torch.cuda.is_available() else "cpu" |
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model = whisper.load_model("base", device=DEVICE) |
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iface = gr.Interface( |
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fn=generate_video, |
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inputs=[ |
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gr.Audio( |
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sources=["upload", "microphone"], type="filepath", label="Audio File" |
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), |
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gr.Dropdown( |
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["en", "es", "fr", "de", "it", "nl", "ru", "zh"], |
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label="Language", |
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value="en", |
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), |
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gr.Slider( |
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minimum=0, |
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maximum=10, |
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step=1, |
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value=0, |
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label="Lag (seconds): delay the transcription by this amount of time.", |
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), |
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], |
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outputs=gr.Video(label="Play Video", show_download_button=True), |
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title="Audio Transcription Video Generator", |
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description="Upload your audio file and select the language for transcription.", |
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) |
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iface.launch() |
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