Add installation instructions for installation with conda
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@ -181,3 +181,33 @@ to download pre-trained OpenFace
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models on the combined CASIA-WebFace and FaceScrub database.
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This also downloads dlib's pre-trained model for face landmark detection.
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This will incur about 200MB of network traffic.
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# Installing open face using `conda` (OSX and GNU/Linux)
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Step 1. Install `miniconda` with the following commands
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* `wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh`
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* `bash Miniconda3-latest-Linux-x86_64.sh` and follow instructions.
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* Add a Python 2.7 environment with: `conda create --name openface python=2.7`
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* Activate the new env with: `source activate openface`
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Step 2. Install dependencies
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* Add the `conda-forge` channel with: `conda config --add channels conda-forge`
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* `conda install opencv numpy pandas scipy scikit-learn scikit-image dlib`
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Step 3. Install Torch and dependencies
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* Deactivate the `openface` environment by opening a new terminal.
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* `git clone https://github.com/torch/distro.git ~/torch --recursive`
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* `cd ~/torch; bash install-deps;`
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* `./install.sh`
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* Execute the following to install the Torch deps `for NAME in dpnn nn optim optnet csvigo cutorch cunn fblualib torchx tds; do luarocks install $NAME; done`
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Step 4. Install open face in `openface` environment using
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* `source activate openface`
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* `git clone https://github.com/cmusatyalab/openface.git ~/openface`
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* `cd openface`
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* `python setup.py install`
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* Download `dlib`s models with: `./models/get-models.sh`
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Open face is now installed. Test it with
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* `./demos/classifier.py infer models/openface/celeb-classifier.nn4.small2.v1.pkl ./images/examples/carell.jpg`
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