Face Morpher

Warp, average and morph human faces!

Scripts will automatically detect frontal faces and skip images if none is detected.

Built with Python, dlib, Numpy, Scipy, dlib.

Supported on Python 2.7, Python 3.6+

Tested on macOS Mojave and 64bit Linux (dockerized).

Requirements

• pip install -r requirements.txt
• Download http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2 and extract file.
• Export environment variable DLIB_DATA_DIR to the folder where shape_predictor_68_face_landmarks.dat is located. Default data. E.g export DLIB_DATA_DIR=/Downloads/data

Either:

• Use as local command-line utility
• Use as pip library
• Try out in a docker container

Use as local command-line utility

$ git clone https://github.com/alyssaq/face_morpher

Morphing Faces

Morph from a source to destination image:

python facemorpher/morpher.py --src=<src_imgpath> --dest=<dest_imgpath> --plot

Morph through a series of images in a folder:

python facemorpher/morpher.py --images=<folder> --out_video=out.avi

All options listed in morpher.py (pasted below):

Morph from source to destination face or
Morph through all images in a folder

Usage:
    morpher.py (--src=<src_path> --dest=<dest_path> | --images=<folder>)
            [--width=<width>] [--height=<height>]
            [--num=<num_frames>] [--fps=<frames_per_second>]
            [--out_frames=<folder>] [--out_video=<filename>]
            [--plot] [--background=(black|transparent|average)]

Options:
    -h, --help              Show this screen.
    --src=<src_imgpath>     Filepath to source image (.jpg, .jpeg, .png)
    --dest=<dest_imgpath>   Filepath to destination image (.jpg, .jpeg, .png)
    --images=<folder>       Folderpath to images
    --width=<width>         Custom width of the images/video [default: 500]
    --height=<height>       Custom height of the images/video [default: 600]
    --num=<num_frames>      Number of morph frames [default: 20]
    --fps=<fps>             Number frames per second for the video [default: 10]
    --out_frames=<folder>   Folder path to save all image frames
    --out_video=<filename>  Filename to save a video
    --plot                  Flag to plot images to result.png [default: False]
    --background=<bg>       Background of images to be one of (black|transparent|average) [default: black]
    --version               Show version.

Averaging Faces

Average faces from all images in a folder:

python facemorpher/averager.py --images=<images_folder> --out=average.png

All options listed in averager.py (pasted below):

Face averager

Usage:
    averager.py --images=<images_folder> [--blur] [--plot]
            [--background=(black|transparent|average)]
            [--width=<width>] [--height=<height>]
            [--out=<filename>] [--destimg=<filename>]

Options:
    -h, --help             Show this screen.
    --images=<folder>      Folder to images (.jpg, .jpeg, .png)
    --blur                 Flag to blur edges of image [default: False]
    --width=<width>        Custom width of the images/video [default: 500]
    --height=<height>      Custom height of the images/video [default: 600]
    --out=<filename>       Filename to save the average face [default: result.png]
    --destimg=<filename>   Destination face image to overlay average face
    --plot                 Flag to display the average face [default: False]
    --background=<bg>      Background of image to be one of (black|transparent|average) [default: black]
    --version              Show version.

Steps (facemorpher folder)

1. Locator

• Locates face points
• For a different locator, return an array of (x, y) control face points

2. Aligner

• Align faces by resizing, centering and cropping to given size

3. Warper

• Given 2 images and its face points, warp one image to the other
• Triangulates face points
• Affine transforms each triangle with bilinear interpolation

4a. Morpher

• Morph between 2 or more images

4b. Averager

• Average faces from 2 or more images

Blender

Optional blending of warped image:

• Weighted average
• Alpha feathering
• Poisson blend

Examples - Being John Malkovich

Create a morphing video between the 2 images:

> python facemorpher/morpher.py --src=alyssa.jpg --dest=john_malkovich.jpg

--out_video=out.avi

(out.avi played and recorded as gif)

Save the frames to a folder:

> python facemorpher/morpher.py --src=alyssa.jpg --dest=john_malkovich.jpg

--out_frames=out_folder --num=30

Plot the frames:

> python facemorpher/morpher.py --src=alyssa.jpg --dest=john_malkovich.jpg

--num=12 --plot

Average all face images in a folder:

85 images used

> python facemorpher/averager.py --images=images --blur --background=transparent

--width=220 --height=250

Use as pip library

$ pip install facemorpher

Examples

Additional options are exactly the same as the command line

import facemorpher

# Get a list of image paths in a folder
imgpaths = facemorpher.list_imgpaths('imagefolder')

# To morph, supply an array of face images:
facemorpher.morpher(imgpaths, plot=True)

# To average, supply an array of face images:
facemorpher.averager(['image1.png', 'image2.png'], plot=True)

Once pip installed, 2 binaries are also available as a command line utility:

$ facemorpher --src=<src_imgpath> --dest=<dest_imgpath> --plot
$ faceaverager --images=<images_folder> --plot

Try out in a docker container

Mount local folder to /images in docker container, run it and enter a bash session. --rm removes the container when you close it.

$ docker run -v  /Users/alyssa/Desktop/images:/images --name py3 --rm -it jjanzic/docker-python3-opencv bash

Once you're in the container, install facemorpher and try the examples listed above

root@0dad0912ebbe:/# pip install facemorpher
root@0dad0912ebbe:/# facemorpher --src=<img1> --dest=<img2> --plot

Documentation

http://alyssaq.github.io/face_morpher

Build & publish Docs

./scripts/publish_ghpages.sh

License

MIT