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Face Swapping using traditional Computer Vision and Deep Learning methods

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Project2 - FaceSwap

Authors:

  1. Saket Seshadri Gudimetla Hanumath (saketsgh@terpmail.umd.edu, UID: 116332293)
  2. Chayan Kumar Patodi (ckp1804@terpmail.umd.edu, UID: 116327428)

Things to Download:

PRNet Model : https://drive.google.com/file/d/1UoE-XuW1SDLUjZmJPkIZ1MLxvQFgmTFH/view Download this model and put in in the path "/Code/prnet/Data/net-data/"

DLib Model : http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2 Download this model and put it in the path "Code/dlib_model/

How To Run:

To run the program, type the following:-" python2.7 Wrapper.py " The usage of argument parser is given below:

usage: Wrapper.py [-h] [--video VIDEO] [--target TARGET] [--method METHOD] [--mode MODE] [--isDlib ISDLIB]

optional arguments: -h, --help show this help message and exit --video VIDEO Provide Video Name and extension with path here --target TARGET Provide Image to be swapped in the image. --method METHOD Provide Method of image transformation: delaunay(deln), Thin Plate Spline(tps), Position Map Regression Network (prnet) --mode MODE If swapping 1 image in a video, use 1, If swapping 2 faces in a single video, use 2 --isDlib ISDLIB True if dlib should be used prediction of facial landmarks. False for using PrNet for the same.

Default arguments are given in the code itself.

Note: Make sure that all the videos and images, you want to run the code on, are present in the Data and TestSet2_P2 folder present in the current directory.

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Face Swapping using traditional Computer Vision and Deep Learning methods

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