Warp, morph and average human faces!
Project description
Built with Python, OpenCV, Numpy, Scipy, Stasm.
Requirements
Install OpenCV: Mac installation steps
Note: OpenCV must be installed either from Homebrew or source as stasm requires the library files.
pip install -r requirements.txt
Either:
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 [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 (using stasm)
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:
(out.avi played and recorded as gif)
Save the frames to a folder:
Plot the frames:
Average all face images in a folder:
85 images used
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
Details
Face points are detected with stasm. This library relies on the python wrapper around stasm.
Documentation
http://alyssaq.github.io/face_morpher
Build & publish Docs
./scripts/publish_ghpages.sh
License
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