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A Python Library for Alpha Matting

A Python Library for Alpha Matting

PyMatting

We introduce the PyMatting package for Python which implements various methods to solve the alpha matting problem.

Given an input image and a hand-drawn trimap (top row), alpha matting estimates the alpha channel of a foreground object which can then be composed onto a different background (bottom row).

PyMatting provides:

  • Alpha matting implementations for:
    • Closed Form Alpha Matting [1]
    • Large Kernel Matting [2]
    • KNN Matting [3]
    • Learning Based Digital Matting [4]
    • Random Walk Matting [5]
  • Foreground estimation implementations for:
    • Closed Form Foreground Estimation [1]
    • Multilevel Foreground Estimation (CPU, CUDA and OpenCL)
  • Fast multithreaded KNN search
  • Preconditioners to accelerate the convergence rate of conjugate gradient descent:
    • The incomplete thresholded Cholesky decomposition (Incomplete is part of the name. The implementation is quite complete.)
    • The V-Cycle Geometric Multigrid preconditioner
  • Readable code leveraging NumPy, SciPy and Numba

Getting Started

Requirements

Minimal requiremens

  • numpy>=1.16.0
  • pillow>=5.2.0
  • numba>=0.47.0
  • scipy>=1.1.0

Additional requirements for GPU support

  • cupy-cuda90>=6.5.0 or similar
  • pyopencl>=2019.1.2

Requirements to run the tests

  • pytest>=5.3.4

Installation with PyPI

pip3 install pymatting

Installation from Source

git clone https://github.com/pymatting/pymatting
cd pymatting
pip3 install .

Example

from pymatting import cutout

cutout(
    # input image path
    "data/lemur.png",
    # input trimap path
    "data/lemur_trimap.png",
    # output cutout path
    "lemur_cutout.png")

More advanced examples

Testing

Run the tests from the main directory:

 python3 tests/download_images.py
 pip3 install -r requirements_tests.txt
 pytest

Currently 89% of the code is covered by tests.

Authors

  • Thomas Germer
  • Tobias Uelwer
  • Stefan Conrad
  • Stefan Harmeling

GitHub