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https://github.com/winstxnhdw/capgen
A fast CPU-first video/audio transcriber for generating caption files with Whisper and CTranslate2, hosted on Hugging Face Spaces.
https://github.com/winstxnhdw/capgen
asr automatic-speech-recognition caddy ctranslate2 docker fastapi huggingface huggingface-spaces uvicorn-gunicorn whisper
Last synced: 3 months ago
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A fast CPU-first video/audio transcriber for generating caption files with Whisper and CTranslate2, hosted on Hugging Face Spaces.
- Host: GitHub
- URL: https://github.com/winstxnhdw/capgen
- Owner: winstxnhdw
- Created: 2023-09-16T18:44:19.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-05-28T11:07:44.000Z (8 months ago)
- Last Synced: 2024-05-29T02:45:49.488Z (8 months ago)
- Topics: asr, automatic-speech-recognition, caddy, ctranslate2, docker, fastapi, huggingface, huggingface-spaces, uvicorn-gunicorn, whisper
- Language: Python
- Homepage: https://huggingface.co/spaces/winstxnhdw/CapGen
- Size: 786 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# CapGen
[](https://github.com/PyCQA/pylint)
[](https://github.com/winstxnhdw/CapGen/actions/workflows/main.yml)
[](https://github.com/winstxnhdw/CapGen/actions/workflows/deploy.yml)
[](https://github.com/winstxnhdw/CapGen/actions/workflows/formatter.yml)
[](https://github.com/winstxnhdw/CapGen/actions/workflows/warmer.yml)
[](https://github.com/winstxnhdw/CapGen/actions/workflows/dependabot.yml)
[](https://huggingface.co/spaces/winstxnhdw/CapGen)
[](https://github.com/winstxnhdw/CapGen/compare)
A fast cross-platform CPU-first video/audio English-only transcriber for generating caption files with [Whisper](https://openai.com/research/whisper) and [CTranslate2](https://github.com/OpenNMT/CTranslate2), hosted on Hugging Face Spaces. A `pip` installable offline CLI tool with CUDA support is provided. By default, Voice Activity Detection (VAD) preprocessing is always enabled.
## Requirements
- Python 3.11
- 4 GB RAM
## Usage (API)
Simply cURL the endpoint like in the following. Currently, the only available caption format are `srt`, `vtt` and `txt`.
```bash
curl "https://winstxnhdw-CapGen.hf.space/api/v1/transcribe?caption_format=$CAPTION_FORMAT" \
-F "request=@$AUDIO_FILE_PATH"
```
You can also redirect the output to a file.
```bash
curl "https://winstxnhdw-CapGen.hf.space/api/v1/transcribe?caption_format=$CAPTION_FORMAT" \
-F "request=@$AUDIO_FILE_PATH" | jq -r ".result" > result.srt
```
You can stream the captions in real-time with the following.
```bash
curl -N "https://winstxnhdw-CapGen.hf.space/api/v1/transcribe/stream?caption_format=$CAPTION_FORMAT" \
-F "request=@$AUDIO_FILE_PATH"
```
## Usage (CLI)
`CapGen` is available as a CLI tool with CUDA support. You can install it with `pip`.
```bash
pip install git+https://github.com/winstxnhdw/CapGen
```
You may also install `CapGen` with the necessary CUDA binaries.
```bash
pip install "capgen[cuda] @ git+https://github.com/winstxnhdw/CapGen"
```
Now, you can run the CLI tool with the following command.
```bash
capgen -c srt -o ./result.srt --cuda < ~/Downloads/audio.mp3
```
```yaml
usage: capgen [-h] [-g] [-t] [-w] -c -o [file]
transcribe a compatible audio/video file into a chosen caption file format
positional arguments:
file the file path to a compatible audio/video
options:
-h, --help show this help message and exit
-g, --cuda whether to use CUDA for inference
cpu:
-t, --threads the number of CPU threads
-w, --workers the number of CPU workers
required:
-c, --caption the chosen caption file format
-o, --output the output file path
```
## Development
You can install the required dependencies for your editor with the following.
```bash
poetry install
```
You can spin the server up locally with the following. You can access the Swagger UI at [localhost:7860/api/docs](http://localhost:7860/api/docs).
```bash
docker build -f Dockerfile.build -t capgen .
docker run --rm -e SERVER_PORT=7860 -p 7860:7860 capgen
```