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Artistically stylizing portrait photos using portrait paintings
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documents
examples
output
README.md
facial_landmark_detection.py
facial_landmark_detection_video.py
main.py
moving_least_squares.py
moving_least_squares_demo.py
shape_predictor_68_face_landmarks.dat

README.md

Artistically Stylizing Portrait Photos using Portrait Paintings

Sample output: see this report

Usage:

python main.py ./examples/art/01.jpg ./examples/target/01.jpg

Dependencies:

cv2, dlib (use https://pypi.python.org/simple/dlib/ to install on Windows), skimage, numpy, matplotlib

Face landmark model:

http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2

Moving Least Square implementation:

https://github.com/Jarvis73/Moving-Least-Squares

Reference:

Face landmark detection starter code: http://dlib.net/face_landmark_detection.py.html & https://www.pyimagesearch.com/2017/04/03/facial-landmarks-dlib-opencv-python/

Workflow inspired by: Jakub Fiser, Ondrej Jamriska, David Simons, Eli Shechtman, Jingwan Lu, Paul Asente, Michal Lukac and Daniel Sykora. “Example-Based Synthesis of Stylized Facial Animations”. ACM Transactions on Graphics 36(4):155, 2017 (SIGGRAPH 2017). July 2017.

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