Because this script uses dlib, and in particular the dlib landmark detector, it can not be run from Blender. Instead we must run the script from a terminal window.
Open a terminal window (command prompt), and go to the AutoFace directory and then to the standalone subdirectory. On my Windows 7 machine, the full path is
C:\Users\Thomas\AppData\Roaming\Blender Foundation\Blender\2.79
\scripts\addons\autoface\standalone
Then run the following command:
python landmarks.py <input image> <basemesh> [-d <directory>]
The standalone scripts look for input images at the following locations:
- A directory explicitly specified with the optional -d (or --dir) keyword.
- In the directory AUTOFACE_DIR/inputs/.
- In the example folder, autoface/exprnet/figures/ included with the add-on.
AutoFace comes with three example images, located in the subdirectory exprnet/figures, which we will upload to Google Drive eventually.
Image credit: The images of Secretary Hillary Clinton and Senator Ted Cruz are in the Public Domain, while the image of Donald Trump is licensed under Creative Commons Attribution-Share Alike 2.0 Generic license.
To find the landmarks of two of the images, one male and one female, we issue the commands
python landmarks.py donald_trump.jpg g8m
python landmarks.py hillary_clinton.jpg g8f
When the script has finished, the image with the detected landmarks shown.
This script also creates five new directories under the AUTOFACE_DIR directory specified in config.txt.
- icons: Contains a small copy of the original image, to be used as thumbnails in DAZ Studio.
- figures: A copy of the input image and a csv file specifying the face's bounding box. This directory will be uploaded to Google Drive for analysis with the deep neural network.
- results: Contains data about the image, to be used by other scripts.
- parameters: Will contain the amplitudes for the eigenfaces after analysis by the deep neural network.
- textures: Will contain the modified textures generated by the patch.py script.
