Here's a video on how to use this code.
Make sure you have a video, in this case named video.py and the requirements installed python -m pip install -r requirements.txt and then run python main.py and you should have a trascribed video!
Here's a video on how to use this code.
Make sure you have a video, in this case named video.py and the requirements installed python -m pip install -r requirements.txt and then run python main.py and you should have a trascribed video!
| # Video https://youtube.com/shorts/MNUdPGIjMPw | |
| # Python 3.10 | |
| # pip install openai-whisper | |
| # pip install git+https://github.com/openai/whisper.git | |
| # install ffmpeg | |
| # brew install ffmpeg | |
| import subprocess | |
| import whisper | |
| model = whisper.load_model("base") | |
| video_in = 'video.mp4' | |
| audio_out = 'audio.mp3' | |
| ffmpeg_cmd = f"ffmpeg -i {video_in} -vn -c:a libmp3lame -b:a 192k {audio_out}" | |
| subprocess.run(["ffmpeg", "-i", video_in, "-vn", "-c:a", "libmp3lame", "-b:a", "192k", audio_out]) | |
| result = model.transcribe(audio_out) | |
| print(result["text"]) |
| openai-whisper |