Merge pull request #186 from BWagener/feature/container-optimizations

optimize container related configuration and documentation

.dockerignore

@@ -0,0 +1,20 @@
+evaluation
+.git
+
+.env
+.vscode/
+# virtual environment
+venv
+.venv
+
+# python
+**__pycache__
+
+# test data
+test_input
+test_output
+
+# default output folder
+output
+/UltraSinger*.spec
+/registry_path.txt

Dockerfile

@@ -1,18 +1,27 @@
-FROM nvidia/cuda:12.5.0-runtime-ubuntu22.04
+FROM nvidia/cuda:12.6.3-runtime-ubuntu22.04
 
-WORKDIR /app
-RUN apt-get update && apt-get install git python3-pip -y && apt-get clean && rm -rf /var/lib/apt/lists/*
+# note: the python3-pip package contains Python 3.10 on Ubuntu 22.04
+RUN apt-get update \
+    && apt-get install git python3-pip python3.10-venv ffmpeg curl -y  \
+    && apt-get clean  \
+    && rm -rf /var/lib/apt/lists/*
 
-RUN git clone https://github.com/rakuri255/UltraSinger.git
+COPY . /app/UltraSinger
 WORKDIR /app/UltraSinger
-RUN apt-get update && apt-get install ffmpeg curl -y && apt-get clean && rm -rf /var/lib/apt/lists/*
-RUN pip install --no-cache-dir -r requirements.txt
-RUN pip install --no-cache-dir  torch==2.3.0 torchvision==0.18.0 torchaudio==2.3.0 --index-url https://download.pytorch.org/whl/cu121 
-RUN pip install --no-cache-dir  tensorflow[and-cuda]==2.16.1
-ENV UID=0
-ENV GID=0
-ENV UMASK=022
 
-EXPOSE 8088 
+# no need to run as root
+RUN chown -R 1000:1000 /app/UltraSinger
+USER 1000:1000
+
+# setup venv
+ENV VIRTUAL_ENV=/app/UltraSinger/.venv
+RUN python3 -m venv $VIRTUAL_ENV
+ENV PATH="$VIRTUAL_ENV/bin:$PATH"
+
+# install dependencies
+RUN pip install --no-cache-dir -r requirements.txt \
+    && pip install --no-cache-dir torch==2.3.0 torchvision==0.18.0 torchaudio==2.3.0 --index-url https://download.pytorch.org/whl/cu121 \
+    && pip install --no-cache-dir tensorflow[and-cuda]==2.16.1
+
 WORKDIR /app/UltraSinger/src
 CMD ["bash" ]

README.md

@@ -61,8 +61,8 @@ This will help me a lot to keep this project alive and improve it.
     - [🏆 Ultrastar Score Calculation](#-ultrastar-score-calculation)
     - [📟 Use GPU](#-use-gpu)
       - [Considerations for Windows users](#considerations-for-windows-users)
-      - [Info](#info)
-      - [Docker](#docker)
+      - [Crashes due to low VRAM](#crashes-due-to-low-vram)
+    - [📦 Containerized](#containerized-docker-or-podman)
 
 ## 💻 How to use this source code
 
@@ -285,65 +285,15 @@ TensorFlow dropped GPU support for Windows for versions >2.10 as you can see in
 
 For now UltraSinger runs the latest version available that still supports GPUs on windows.
 
-For running later versions of TensorFlow on windows while still taking advantage of GPU support the suggested solution is:
+For running later versions of TensorFlow on windows while still taking advantage of GPU support the suggested solution is to [run UltraSinger in a container](container/README.md).
 
-* [install WSL2](https://learn.microsoft.com/en-us/windows/wsl/install)
-* within the Ubuntu WSL2 installation
-  * run `sudo apt update && sudo apt install nvidia-cuda-toolkit`
-  * follow the setup instructions for UltraSinger at the top of this document
-
-#### Info
+#### Crashes due to low VRAM
 
 If something crashes because of low VRAM then use a smaller model.
 Whisper needs more than 8GB VRAM in the `large` model!
 
 You can also force cpu usage with the extra option `--force_cpu`.
 
-#### Docker
-to run the docker run `git clone https://github.com/rakuri255/UltraSinger.git`
-enter the UltraSinger folder.
-run this command to build the docker
-`docker build -t ultrasinger .` make sure to include the "." at the end
-let this run till complete.
-then run this command
-`docker run --gpus all -it --name UltraSinger -v  $pwd/src/output:/app/src/output ultrasinger`
-
-Docker-Compose
-there are two files that you can pick from.
-cd into `docker-compose` folder and then cd into `Nvidia` or `NonGPU`
-Run `docker-compose up` to download and setup
-
-Nvidia is for if you have a nvidia gpu to use with UltraSinger.
-NonGPU is for if you wish to only use the CPU for UltraSinger.
-
-Output
-by default the docker-compose will setup the output folder as `/output` inside the docker.
-on the host machine it will map to the folder with the `docker-compose.yml` file under `output`
-you may chnage this by editing the `docker-compose.yml`
-
-to edit the file.
-use any text editor you wish. i would recoment nano.
-run `nano docker-compose.yml`
-then change this line
-`            -  ./output:/app/UltraSinger/src/output`
-to anything you line for on your host machine.
-`            -  /yourfolderpathhere:/app/UltraSinger/src/output`
-sample
-`            -  /mnt/user/appdata/UltraSinger:/output`
-note the blank space before the `-`
-formating is important here in this file.
-
-this will create and drop you into the docker.
-now run this command.
-`python3 UltraSinger.py -i file`
-or
-`python3 UltraSinger.py -i youtube_url`
-to use mp3's in the folder you git cloned you must place all songs you like in UltraSinger/src/output.
-this will be the place for youtube links aswell.
-
-
-to quit the docker just type exit.
-
-to reenter docker run this command
-`docker start UltraSinger && Docker exec -it UltraSinger /bin/bash`
+### Containerized (Docker or Podman)
 
+See [container/README.md](container/README.md)

container/README.md

@@ -0,0 +1,16 @@
+# Containerized UltraSinger
+
+## Getting started
+
+1. There are specific instructions for either Docker or Podman:
+    1. [Docker](docker.md)
+    1. [Podman](podman.md)
+
+## Why run UltraSinger as a container?
+
+Running UltraSinger in a container bears the following advantages
+
+- Environment Consistency: Containers ensure that the application runs in the same environment across different machines, reducing the "it works on my machine" problem.
+- Isolation: Containers isolate the application from the host system, preventing conflicts with other applications and dependencies.
+- Simplified Deployment: Containers package the application and its dependencies together, simplifying the deployment process.
+- Security: Containers provide an additional layer of security by isolating applications from the host system and each other.

container/docker.md

@@ -0,0 +1,47 @@
+# Containerized UltraSinger (Docker)
+
+To run the docker run `git clone https://github.com/rakuri255/UltraSinger.git`
+enter the UltraSinger folder.
+run this command to build the docker
+`docker build -t ultrasinger .` make sure to include the "." at the end
+let this run till complete.
+then run this command
+`docker run --gpus all -it --name UltraSinger -v  $pwd/src/output:/app/src/output ultrasinger`
+
+Docker-Compose
+- there are two files that you can pick from.
+- cd into the `container` folder
+- to download and setup, run either
+  - `docker-compose -f compose-gpu.yml up` if you have an nvidia gpu to use with UltraSinger 
+  - or`docker-compose -f compose-nogpu.yml up` if you wish to only use the CPU for UltraSinger
+
+Output
+by default the docker-compose will setup the output folder as `/output` inside the docker.
+on the host machine it will map to the folder with the `compose<gpu|nogpu>.yml` file under `output`
+you may change this by editing the `compose<gpu|nogpu>.yml`
+
+to edit the file.
+use any text editor you wish. i would recoment nano.
+run `nano compose<gpu|nogpu>.yml`
+then change this line
+`            -  ./output:/app/UltraSinger/src/output`
+to anything you line for on your host machine.
+`            -  /yourfolderpathhere:/app/UltraSinger/src/output`
+sample
+`            -  /mnt/user/appdata/UltraSinger:/output`
+note the blank space before the `-`
+formating is important here in this file.
+
+this will create and drop you into the docker.
+now run this command.
+`python3 UltraSinger.py -i file`
+or
+`python3 UltraSinger.py -i youtube_url`
+to use mp3's in the folder you git cloned you must place all songs you like in UltraSinger/src/output.
+this will be the place for youtube links aswell.
+
+
+to quit the docker just type exit.
+
+to reenter docker run this command
+`docker start UltraSinger && Docker exec -it UltraSinger /bin/bash`

container/podman.md

@@ -0,0 +1,52 @@
+# Containerized UltraSinger (Podman)
+
+1. prerequisites
+   1. Podman installed (for Windows WSL2 machine provider is recommended) -> [installation instructions](https://podman-desktop.io/docs/installation)
+   1. (optional) for GPU acceleration Nvidia Container Toolkit installed -> [GPU container access](https://podman-desktop.io/docs/podman/gpu)
+1. clone this repository:
+    ```commandline
+    git clone https://github.com/rakuri255/UltraSinger.git
+    ```
+1. build the container image 
+    ```commandline
+    podman build -t ultrasinger .
+    ```
+1. run the container (note that the first time you run the container models will be downloaded which may take a while)
+   1. PowerShell:
+      ```powershell
+      # remember to replace <desired-output-folder> below
+      podman run `
+        --rm -it --name ultrasinger `
+        --device nvidia.com/gpu=all `
+        -v $env:USERPROFILE\.cache:/app/UltraSinger/src/.cache `
+        -v <desired-output-folder>:/app/UltraSinger/src/output `
+        ultrasinger `
+        python3 UltraSinger.py -i <refer to top-level README.md>
+      
+      # explanation:
+      podman run `
+        --rm -it --name ultrasinger ` # remove container after run, interactive mode, name the container
+        --device nvidia.com/gpu=all ` # optional, enables GPU acceleration if available, requires step 1.ii
+        -v $env:USERPROFILE\.cache:/app/UltraSinger/src/.cache ` # cache directory for models
+        -v <desired-output-folder>:/app/UltraSinger/src/output ` # output directory
+        ultrasinger ` # container image name, we built this in step 3
+        python3 UltraSinger.py -i <refer to top-level README.md> # run UltraSinger, refer to top-level README.md for all options
+      ```
+   1. Bash:
+      ```bash
+      # remember to replace <desired-output-folder> below
+      podman run \
+        --rm -it --name ultrasinger \
+        --device nvidia.com/gpu=all \
+        -v $HOME/.cache:/app/UltraSinger/src/.cache \
+        -v <desired-output-folder>:/app/UltraSinger/src/output \
+        ultrasinger \
+        python3 UltraSinger.py -i <refer to top-level README.md>
+   1. to use cookies for YouTube downloads, you can mount your cookies.txt file into the container:
+      ```powershell
+      podman run `
+        ... ` # same as above
+        -v <path-to-cookies.txt>:/app/UltraSinger/src/cookies.txt `
+        ultrasinger `
+        python3 UltraSinger.py --cookiefile cookies.txt -i <refer to top-level README.md>
+      ```