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https://github.com/mike10004/torch-deb

Torch installer for Debian/Ubuntu
https://github.com/mike10004/torch-deb

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Torch installer for Debian/Ubuntu

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# torch-deb

This project produces a `.deb` installation package for Torch. The motivation
is that there were many cases where I had to go through the whole Torch build
process to run OpenFace in a new environment, and I wanted to speed the setup
of that environment.

To build a workable package, it is best to execute the build inside the
container specified by the Dockerfile in the project root directory.

# Building inside the container

## Build the image

To build the Docker image, change to this project directory and execute

$ docker build -t torch-deb .

To build the `.deb` file, you can run the default container command and then
copy the output file from the container filesystem to your host filesystem,
or you can run a bash shell and build from within the container.

## Build the deb

### Use the default command

Execute

$ docker run --mount type=bind,src=/tmp,dst=/mnt torch-deb

to build the `.deb` and copy it to `/tmp`. Change `src=/tmp` to point to a
different destination directory if you so please.

### ...or start a shell

To start a shell, execute

$ docker run --rm -it torch-deb /bin/bash -l

To build the `.deb` from within that container, execute

$ mvn -f /root/torch-parent/pom.xml install -Pcontainer

## OpenFace continuation

You can do this on your host computer or in a Docker container. For a suitable
container, execute

$ docker run --rm -it ubuntu:18.04 /bin/bash -l

You can also just use the `torch-deb` container to avoid having to install all
the dependencies.

OpenFace setup is as follows:

# apt update

# apt install --yes ./torch-private_7.0-1_all.deb python-pip wget git cmake

# git clone https://github.com/cmusatyalab/openface.git

# cd openface

From here on, you might prefer to use an Anaconda or virtualenv environment.
To create an Anaconda environment, execute `conda create --name openface python=2.7`.
After entering the environment (`conda activate openface`), continue as follows.

# pip install -r requirements.txt

# pip install dlib==19.16.0 opencv-python==4.0.0.21

# models/get-models.sh

At this point, your OpenFace is functional. To demonstrate, execute this:

# PYTHONPATH=. demos/compare.py images/examples/{lennon-*,clapton-*}