cadic/whisper repository overview
Whisper
(English/Japanese/Multi-lingual)
Modules • Code structure • Installing the application • Makefile commands • Environments • Dataset• Running the application• Notes•
Modules
At a granular level, whisper is a library that consists of the following components:
| Component | Description |
|---|---|
| whisper | Speech Recognition package |
| whisper.infer | whisper Inference from audio files |
| whisper.tests | Unittests |
Code structure
import os
import pkg_resources
from setuptools import setup, find_packages
from whisper import __version__
setup(
name="whisper",
py_modules=["whisper"],
version=__version__,
description="Robust Speech Recognition via Large-Scale Weak Supervision",
long_description="".join(open("README.md", "r").readlines()),
long_description_content_type="text/markdown",
readme="README.md",
python_requires=">=3.7",
author="OpenAI, CADIC Jean Maximilien",
include_package_data=True,
package_data={"": ["*.flac", "*.txt", "*.json", "*.npz"]},
url="https://github.com/openai/whisper",
license="MIT",
packages=find_packages(),
install_requires=[
str(r)
for r in pkg_resources.parse_requirements(
open(os.path.join(os.path.dirname(__file__), "requirements.txt"))
)
],
entry_points={
"console_scripts": ["whisper=whisper.transcribe:cli"],
},
)
Installing the application
To clone and run this application, you'll need the following installed on your computer:
Install bpd:
# Clone this repository and install the code
git clone https://github.com/JeanMaximilienCadic/whisper
# Go into the repository
cd whisper
Makefile commands
Exhaustive list of make commands:
build_dockers # Build the docker images
sandbox # Launch a sandbox
tests # Test the code
Environments
Install PyTorch Install Nvidia Docker2
Docker
Note
Running this application by using Docker is recommended.
To build and run the docker image
make build_dockers
make sandbox
PythonEnv
Warning
Running this application by using PythonEnv is possible but not recommended.
pip install dist/*.whl
Test
make tests
Pretrained model
python -m whisper.infer --audio_path <PATH TO AUDIO FILE (EN/JA/Others)>
Acknowledgements
Thanks to Jong Wook Kim and OpenAI for their contributions!
This is a fork from https://github.com/openai/whisper.
For any question please contact me at j.cadic[at]protonmail.ch lar
Tag summary
Content type
Image
Digest
sha256:11207a0b5…
Size
9.2 GB
Last updated
almost 4 years ago
docker pull cadic/whisper:sandbox-whisper_1.0.0