Updated workdir for docker images, added docker docs to readme

Dockerfile.cpu

@@ -2,7 +2,7 @@
 FROM python:3.11-slim
 
 # Set the working directory in the container
-WORKDIR /usr/src/app
+WORKDIR /workdir
 
 RUN apt-get update; apt-get install -y ffmpeg
 RUN python -m pip install --upgrade pip

Dockerfile.gpu

@@ -2,7 +2,7 @@
 FROM nvidia/cuda:11.8.0-base-ubuntu22.04
 
 # Set the working directory in the container
-WORKDIR /usr/src/app
+WORKDIR /workdir
 
 RUN apt-get update && apt-get install -y \
     ffmpeg \

README.md

@@ -1,6 +1,7 @@
 # Audio Separator 🎶
 
 [![PyPI version](https://badge.fury.io/py/audio-separator.svg)](https://badge.fury.io/py/audio-separator)
+[![Docker pulls](https://img.shields.io/docker/pulls/beveradb/audio-separator.svg)](https://hub.docker.com/r/beveradb/audio-separator/tags)
 
 Summary: Easy to use vocal separation on CLI or as a python package, using the amazing MDX-Net models from UVR trained by @Anjok07
 
@@ -68,6 +69,27 @@ Depending on your CUDA version and hardware, you may need to install torch from
 
 > Note: if anyone knows how to make this cleaner so we can support both different platform-specific dependencies for hardware acceleration without a separate installation process for each, please let me know or raise a PR!
 
+## Usage in Docker 🐳
+
+There are [images published on Docker Hub](https://hub.docker.com/r/beveradb/audio-separator/tags) for GPU (CUDA) and CPU inferencing, for both `amd64` and `arm64` platforms.
+
+You probably want to volume-mount a folder containing whatever file you want to separate, which can then also be used as the output folder.
+
+For example, if the current directory contains your input file `input.wav`, you could run `audio-separator` like so:
+
+```
+docker run -it -v `pwd`:/usr/src/app beveradb/audio-separator input.wav
+```
+
+If you're using a machine with a GPU, you'll want to use the GPU specific image and pass in the GPU device to the container, like this:
+
+```
+docker run -it --gpus all -v `pwd`:/usr/src/app beveradb/audio-separator:gpu input.wav
+```
+
+If the GPU isn't being detected, make sure your docker runtime environment is passing through the GPU correctly - there are [various guides](https://www.celantur.com/blog/run-cuda-in-docker-on-linux/) online to help with that.
+
+
 ## Usage 🚀
 
 ### Command Line Interface (CLI)

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "audio-separator"
-version = "0.9.5"
+version = "0.9.6"
 description = "Easy to use vocal separation on CLI or as a python package, using the amazing MDX-Net models from UVR trained by @Anjok07"
 authors = ["Andrew Beveridge <[email protected]>"]
 license = "MIT"