A python vlc player that transcribes subtitles while watching a video. The model used to automatically generate the subtitles is Whisper, by Open-AI. The default model version is the tiny one, for low memory impact, which doesn't have a translation capability, so the subtitle translations are done using the google-trans package.
The Whisper model is compiled using the Intel® NPU Acceleration Library, so that it ultimately runs on the Intel NPU, releaving the CPU or GPU of the processing for a low-powered and efficient inference.
./src : source files of the application
./media : various media files used by the project, including a test video file
For the application to run properly, install the following prerequisites:
- the VLC media player, as the python package is just an API
- the FFmpeg suite for proper handling of video and audio files.
The video player runs on the python3 programming language. Testing was done on version 3.10.11.
Package requirements:
googletrans==3.0.0
PyQt6==6.6.1
torch==1.11.0
intel_npu_acceleration_library==1.0.0
openai-whisper==20231117
python-vlc==3.0.20123Install:
pip install -r /src/requirements.txtThe app GUI can be started by running the main.py file:
python src/main.pyoptions:
--model {tiny,base,small,medium,large}
Whisper-AI model version
--in_lan {af,sq,am,ar,hy,az,eu,be,bn,bs,bg,ca,ceb,ny,zh-cn,zh-tw,co,hr,cs,da,nl,en...} , default=en
Input lanuage of media file
--out_lan {af,sq,am,ar,hy,az,eu,be,bn,bs,bg,ca,ceb,ny,zh-cn,zh-tw,co,hr,cs,da,nl,en...}, default=en
Output language for subtitles
--gen_sub_file True/False, default=False
Generates a subtitle fileFor the model version, keep in mind the various resources needed for running: Source: openai-whisper pip package
| Size | Parameters | model | Required VRAM | Relative speed |
|---|---|---|---|---|
| tiny | 39 M | tiny | ~1 GB | ~32x |
| base | 74 M | base | ~1 GB | ~16x |
| small | 244 M | small | ~2 GB | ~6x |
| medium | 769 M | medium | ~5 GB | ~2x |
| large | 1550 M | large | ~10 GB | 1x |
