When I input a trimap with all unknown region, i.e. no foreground and background, it raised an error there , https://github.com/pymatting/pymatting/blob/master/pymatting/util/util.py#L491.

Got this error both on macOS 10.14 and Ubuntu 16.04

When installing the package I used --ignore-installed llvmlite flag for pip because I got Cannot uninstall 'llvmlite'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.. I am not sure if this is relevant.

pytest
============================================================================== test session starts ===============================================================================
platform darwin -- Python 3.7.4, pytest-5.2.1, py-1.8.0, pluggy-0.13.0
rootdir: /Users/user/pymatting-master
plugins: arraydiff-0.3, remotedata-0.3.2, doctestplus-0.4.0, openfiles-0.4.0
collected 11 items                                                                                                                                                               

tests/test_boxfilter.py .                                                                                                                                                  [  9%]
tests/test_cg.py .                                                                                                                                                         [ 18%]
tests/test_estimate_alpha.py F                                                                                                                                             [ 27%]
tests/test_foreground.py .                                                                                                                                                 [ 36%]
tests/test_ichol.py .                                                                                                                                                      [ 45%]
tests/test_kdtree.py Fatal Python error: Segmentation fault

Current thread 0x00000001086d7dc0 (most recent call first):
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pymatting/util/kdtree.py", line 280 in __init__
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pymatting/util/kdtree.py", line 347 in knn
  File "/Users/user/pymatting-master/tests/test_kdtree.py", line 20 in run_kdtree
  File "/Users/user/pymatting-master/tests/test_kdtree.py", line 46 in test_kdtree
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/python.py", line 170 in pytest_pyfunc_call
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/callers.py", line 187 in _multicall
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/manager.py", line 86 in <lambda>
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/manager.py", line 92 in _hookexec
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/hooks.py", line 286 in __call__
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/python.py", line 1423 in runtest
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/runner.py", line 125 in pytest_runtest_call
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/callers.py", line 187 in _multicall
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/manager.py", line 86 in <lambda>
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/manager.py", line 92 in _hookexec
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/hooks.py", line 286 in __call__
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/runner.py", line 201 in <lambda>
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/runner.py", line 229 in from_call
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/runner.py", line 201 in call_runtest_hook
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/runner.py", line 176 in call_and_report
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/runner.py", line 95 in runtestprotocol
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/runner.py", line 80 in pytest_runtest_protocol
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/callers.py", line 187 in _multicall
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/manager.py", line 86 in <lambda>
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/manager.py", line 92 in _hookexec
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/hooks.py", line 286 in __call__
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/main.py", line 256 in pytest_runtestloop
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/callers.py", line 187 in _multicall
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/manager.py", line 86 in <lambda>
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/manager.py", line 92 in _hookexec
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/hooks.py", line 286 in __call__
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/main.py", line 235 in _main
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/main.py", line 191 in wrap_session
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/main.py", line 228 in pytest_cmdline_main
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/callers.py", line 187 in _multicall
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/manager.py", line 86 in <lambda>
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/manager.py", line 92 in _hookexec
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/pluggy/hooks.py", line 286 in __call__
  File "/Users/user/opt/anaconda3/lib/python3.7/site-packages/_pytest/config/__init__.py", line 90 in main
  File "/Users/user/opt/anaconda3/bin/pytest", line 11 in <module>
[1]    99661 segmentation fault  pytest

Hey！This tool can bring me very good results, but I did statistics, and it took me nearly 10 minutes to process 1,000 images without counting the IO time. 1,000 images generally correspond to a 30-second video. This efficiency is Not ideal, looking forward to reply

Bug description

$ python test2.py Failed to import ahead-of-time-compiled modules. This is expected on first import. Compiling modules and trying again (this might take a minute). Traceback (most recent call last): File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/pymatting_aot/cc.py", line 21, in import pymatting_aot.aot ModuleNotFoundError: No module named 'pymatting_aot.aot'

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "test2.py", line 1, in from pymatting import cutout File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/pymatting/init.py", line 2, in import pymatting_aot.cc File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/pymatting_aot/cc.py", line 28, in compile_modules() File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/pymatting_aot/cc.py", line 6, in compile_modules cc = CC("aot") File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/numba/pycc/cc.py", line 65, in init self._toolchain = Toolchain() File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/numba/pycc/platform.py", line 78, in init self._raise_external_compiler_error() File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/numba/pycc/platform.py", line 121, in _raise_external_compiler_error raise RuntimeError(msg) RuntimeError: Attempted to compile AOT function without the compiler used by numpy.distutils present. If using conda try:

#> conda install gcc_linux-64 gxx_linux-64

To Reproduce

installed pymatting with pip install rembg on Fedora 33 within venv for Python3.8 create test2.py: from pymatting import cutout

cutout( # input image path "data/lemur/lemur.png", # input trimap path "data/lemur/lemur_trimap.png", # output cutout path "lemur_cutout.png") launch: python test2.py within venv for Python3.8

Expected behavior

runed without errors

Images

(Add relevant images.)

Library versions:

(Run the following commands and paste the result here.)

python --version --version
Python 3.8.6 (default, Sep 25 2020, 00:00:00) 
[GCC 10.2.1 20200826 (Red Hat 10.2.1-3)]
(envrembg) [sav@localhost envrembg]$ python -c "import numpy; numpy.show_config()"

python -c "import numpy; numpy.show_config()"
blas_mkl_info:
  NOT AVAILABLE
blis_info:
  NOT AVAILABLE
openblas_info:
    libraries = ['openblas', 'openblas']
    library_dirs = ['/usr/local/lib']
    language = c
    define_macros = [('HAVE_CBLAS', None)]
blas_opt_info:
    libraries = ['openblas', 'openblas']
    library_dirs = ['/usr/local/lib']
    language = c
    define_macros = [('HAVE_CBLAS', None)]
lapack_mkl_info:
  NOT AVAILABLE
openblas_lapack_info:
    libraries = ['openblas', 'openblas']
    library_dirs = ['/usr/local/lib']
    language = c
    define_macros = [('HAVE_CBLAS', None)]
lapack_opt_info:
    libraries = ['openblas', 'openblas']
    library_dirs = ['/usr/local/lib']
    language = c
    define_macros = [('HAVE_CBLAS', None)]

python -c "import scipy;scipy.show_config()"
lapack_mkl_info:
  NOT AVAILABLE
openblas_lapack_info:
    libraries = ['openblas', 'openblas']
    library_dirs = ['/usr/local/lib']
    language = c
    define_macros = [('HAVE_CBLAS', None)]
lapack_opt_info:
    libraries = ['openblas', 'openblas']
    library_dirs = ['/usr/local/lib']
    language = c
    define_macros = [('HAVE_CBLAS', None)]
blas_mkl_info:
  NOT AVAILABLE
blis_info:
  NOT AVAILABLE
openblas_info:
    libraries = ['openblas', 'openblas']
    library_dirs = ['/usr/local/lib']
    language = c
    define_macros = [('HAVE_CBLAS', None)]
blas_opt_info:
    libraries = ['openblas', 'openblas']
    library_dirs = ['/usr/local/lib']
    language = c
    define_macros = [('HAVE_CBLAS', None)]

python -c "import numba;print('Numba version:', numba.__version__)"
Numba version: 0.51.2

python -c "import PIL;print('PIL version:', PIL.__version__)"
PIL version: 8.0.1

python -c "from pymatting.__about__ import __version__;print('PyMatting version:', __version__)"
Failed to import ahead-of-time-compiled modules. This is expected on first import.
Compiling modules and trying again (this might take a minute).
Traceback (most recent call last):
  File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/pymatting_aot/cc.py", line 21, in <module>
    import pymatting_aot.aot
ModuleNotFoundError: No module named 'pymatting_aot.aot'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/pymatting/__init__.py", line 2, in <module>
    import pymatting_aot.cc
  File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/pymatting_aot/cc.py", line 28, in <module>
    compile_modules()
  File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/pymatting_aot/cc.py", line 6, in compile_modules
    cc = CC("aot")
  File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/numba/pycc/cc.py", line 65, in __init__
    self._toolchain = Toolchain()
  File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/numba/pycc/platform.py", line 78, in __init__
    self._raise_external_compiler_error()
  File "/home/sav/pytest/envrembg/lib64/python3.8/site-packages/numba/pycc/platform.py", line 121, in _raise_external_compiler_error
    raise RuntimeError(msg)
RuntimeError: Attempted to compile AOT function without the compiler used by `numpy.distutils` present. If using conda try:

#> conda install gcc_linux-64 gxx_linux-64

Hi

I have setup the pymatting under container environment and executed the test. Pytest was able to complete it however I got following warnings:

tests/test_foreground.py::test_foreground /pymatting/tests/test_foreground.py:32: UserWarning: Tests for GPU implementation skipped, because of missing packages. "Tests for GPU implementation skipped, because of missing packages."

-- Docs: https://docs.pytest.org/en/stable/warnings.html

I noticed that similar issue was reported earlier as well but couldn't find conclusion

I have got Nvidia GPUs but somehow it is not being detected. I have individually installed cuPy, pyopencl, libcutensor and some other output on installed cuda packages:

root@10e16f343455:/pymatting# dpkg --list | grep cuda
ii  cuda-command-line-tools-10-2  10.2.89-1                           amd64        CUDA command-line tools
ii  cuda-compat-10-2              440.95.01-1                         amd64        CUDA Compatibility Platform
ii  cuda-compiler-10-2            10.2.89-1                           amd64        CUDA compiler
ii  cuda-cudart-10-2              10.2.89-1                           amd64        CUDA Runtime native Libraries
ii  cuda-cudart-dev-10-2          10.2.89-1                           amd64        CUDA Runtime native dev links, headers
ii  cuda-cufft-10-2               10.2.89-1                           amd64        CUFFT native runtime libraries
ii  cuda-cufft-dev-10-2           10.2.89-1                           amd64        CUFFT native dev links, headers
ii  cuda-cuobjdump-10-2           10.2.89-1                           amd64        CUDA cuobjdump
ii  cuda-cupti-10-2               10.2.89-1                           amd64        CUDA profiling tools runtime libs.
ii  cuda-cupti-dev-10-2           10.2.89-1                           amd64        CUDA profiling tools interface.
ii  cuda-curand-10-2              10.2.89-1                           amd64        CURAND native runtime libraries
ii  cuda-curand-dev-10-2          10.2.89-1                           amd64        CURAND native dev links, headers
ii  cuda-cusolver-10-2            10.2.89-1                           amd64        CUDA solver native runtime libraries
ii  cuda-cusolver-dev-10-2        10.2.89-1                           amd64        CUDA solver native dev links, headers
ii  cuda-cusparse-10-2            10.2.89-1                           amd64        CUSPARSE native runtime libraries
ii  cuda-cusparse-dev-10-2        10.2.89-1                           amd64        CUSPARSE native dev links, headers
ii  cuda-driver-dev-10-2          10.2.89-1                           amd64        CUDA Driver native dev stub library
ii  cuda-gdb-10-2                 10.2.89-1                           amd64        CUDA-GDB
ii  cuda-libraries-10-2           10.2.89-1                           amd64        CUDA Libraries 10.2 meta-package
ii  cuda-libraries-dev-10-2       10.2.89-1                           amd64        CUDA Libraries 10.2 development meta-package
ii  cuda-license-10-2             10.2.89-1                           amd64        CUDA licenses
ii  cuda-memcheck-10-2            10.2.89-1                           amd64        CUDA-MEMCHECK
ii  cuda-minimal-build-10-2       10.2.89-1                           amd64        Minimal CUDA 10.2 toolkit build packages.
ii  cuda-misc-headers-10-2        10.2.89-1                           amd64        CUDA miscellaneous headers
ii  cuda-npp-10-2                 10.2.89-1                           amd64        NPP native runtime libraries
ii  cuda-npp-dev-10-2             10.2.89-1                           amd64        NPP native dev links, headers
ii  cuda-nvcc-10-2                10.2.89-1                           amd64        CUDA nvcc
ii  cuda-nvdisasm-10-2            10.2.89-1                           amd64        CUDA disassembler
ii  cuda-nvgraph-10-2             10.2.89-1                           amd64        NVGRAPH native runtime libraries
ii  cuda-nvgraph-dev-10-2         10.2.89-1                           amd64        NVGRAPH native dev links, headers
ii  cuda-nvjpeg-10-2              10.2.89-1                           amd64        NVJPEG native runtime libraries
ii  cuda-nvjpeg-dev-10-2          10.2.89-1                           amd64        NVJPEG native dev links, headers
ii  cuda-nvml-dev-10-2            10.2.89-1                           amd64        NVML native dev links, headers
ii  cuda-nvprof-10-2              10.2.89-1                           amd64        CUDA Profiler tools
ii  cuda-nvprune-10-2             10.2.89-1                           amd64        CUDA nvprune
ii  cuda-nvrtc-10-2               10.2.89-1                           amd64        NVRTC native runtime libraries
ii  cuda-nvrtc-dev-10-2           10.2.89-1                           amd64        NVRTC native dev links, headers
ii  cuda-nvtx-10-2                10.2.89-1                           amd64        NVIDIA Tools Extension
ii  cuda-sanitizer-api-10-2       10.2.89-1                           amd64        CUDA Sanitizer API
hi  libcudnn7                     7.6.5.32-1+cuda10.2                 amd64        cuDNN runtime libraries
ii  libcudnn7-dev                 7.6.5.32-1+cuda10.2                 amd64        cuDNN development libraries and headers
hi  libnccl-dev                   2.7.8-1+cuda10.2                    amd64        NVIDIA Collectives Communication Library (NCCL) Development Files
hi  libnccl2                      2.7.8-1+cuda10.2                    amd64        NVIDIA Collectives Communication Library (NCCL) Runtime

Could you please advise on what package might be missing? Thank you.

=== warnings summary ===

tests/test_foreground.py::test_foreground /home/ferg/git/pymatting/tests/test_foreground.py:31: UserWarning: Tests for GPU implementation skipped, because of missing packages.

I'm on Fedora 31 and here are my pip 3 package versions which above the required dependencies.

Requirement already satisfied: numpy in /usr/lib64/python3.7/site-packages (1.17.4) Requirement already satisfied: pillow in /usr/lib64/python3.7/site-packages (6.1.0) Requirement already satisfied: numba in /home/ferg/.local/lib/python3.7/site-packages (0.48.0) Requirement already satisfied: scipy in /home/ferg/.local/lib/python3.7/site-packages (1.4.1)

I'm attempting to get this package into a binary format on conda-forge; would it be possible to include a MANIFEST.in file? Currently some of the required files are not included in the sdist (e.g. requirement.txt)

https://packaging.python.org/guides/using-manifest-in/

I was reading about trimap, I found 2 different definition on it

• An image consisting of only 3 colors: black, white and a single shade of grey
• An image consisting of black, white and shades of grey (where all shades of grey correspond to unknown region)

Which one is correct?

@vlsav, thanks for reporting this issue! Have you tried running conda install gcc_linux-64 gxx_linux-64 (as suggested)?

Originally posted by @tuelwer in https://github.com/pymatting/pymatting/issues/37#issuecomment-731645867

Hi, I installed the lib but there are a problem with the importation of your package.

I am using python 3.8.1 with : numpy=1.18.1 (>=1.16.0) pillow=6.2.1 (>=5.2.0) numba=0.47.0 (>=0.44.0) scipy=1.3.3 (>=1.1.0)

*** ValueError: Failed in nopython mode pipeline (step: convert to parfors) Cannot add edge as dest node 26 not in nodes {130, 132, 262, 264, 528, 30, 418, 302, 564, 565, 566, 568, 322, 450, 196, 452, 324, 340, 212, 86, 214, 348, 94, 228, 356, 494, 118, 246, 248, 378, 380}

(you can read all here: https://gyazo.com/b6b9756f0c8d75a30a63dada09c5f82e)

Thank you for your work :+1:

Bug description

I used pymatting in torch data preprocessing, but the new version of pymatting does not seem to support multi-threading. In addition, 1.0.4 works.

To Reproduce

Pymatting 1.1.4, Torch 1.10, 5900x with 3090, CUDA 11.4。 torch.dataset/dataloader. number_workers>=1.

Several tests (for example, the one in test_estimate_alpha.py) fail because a required image is missing:

FAILED tests/test_estimate_alpha.py::test_alpha - FileNotFoundError: [Errno 2] No such file or directory: 'data/input_training_lowres/GT01.png'
FAILED tests/test_laplacians.py::test_laplacians - FileNotFoundError: [Errno 2] No such file or directory: 'data/input_training_lowres/GT01.png'
FAILED tests/test_lkm.py::test_lkm - FileNotFoundError: [Errno 2] No such file or directory: 'data/input_training_lowres/GT01.png'
FAILED tests/test_preconditioners.py::test_preconditioners - FileNotFoundError: [Errno 2] No such file or directory: 'data/input_training_lowres/GT01.png'

Could/should GT01.png be included?

Currently, the packages specified in requirements.txt are copied into setup.py:

    install_requires=load_text("requirements.txt").strip().split("\n"),

This is bad practice and can cause problems downstream.

requirements.txt should be used to define a repeatable installation, such as a development environment or a production environment. As such, versions of dependencies contained therein should be as specific as possible.

install_requires should be used to indicate dependencies necessary to run the package. As such, versions of dependencies contained therein should be as broad as possible.

Please see “install_requires vs requirements files” on python.org or “requirements.txt vs setup.py” on stackoverflow for more information.

I'd be happy to contribute a PR with loose dependency specifications in setup.py and concrete specifications in requirements.txt.

PyMatting can be made available on conda-forge by submitting a pull request to the staged-reciples repository. Detailed instructions can be found here.

Hi,

Thank you for your amazing repo. I try to convert estimate_fg_bg_numpy.py to TensorFlow. However, the inference speed is not satisfactory. In GPU 1080Ti, the cupy version just cost 2ms, the TensorFlow version will cost 20ms for 144x256 resolution. Do you know how to correctly revise the numpy code to TensorFlow? Thank you very much.

import numpy as np
from PIL import Image
import time
import tensorflow as tf


def inv2(mat):
    a = mat[..., 0, 0]
    b = mat[..., 0, 1]
    c = mat[..., 1, 0]
    d = mat[..., 1, 1]

    inv_det = 1 / (a * d - b * c)

    inv00 = inv_det * d
    inv01 = inv_det * -b
    inv10 = inv_det * -c
    inv11 = inv_det * a
    inv00 = inv00[:, tf.newaxis, tf.newaxis]
    inv01 = inv01[:, tf.newaxis, tf.newaxis]
    inv10 = inv10[:, tf.newaxis, tf.newaxis]
    inv11 = inv11[:, tf.newaxis, tf.newaxis]
    inv_temp1 = tf.concat([inv00, inv10], axis=1)
    inv_temp2 = tf.concat([inv01, inv11], axis=1)
    inv = tf.concat([inv_temp1, inv_temp2], axis=2)

    return inv


def pixel_coordinates(w, h, flat=False):
    x, y = tf.meshgrid(np.arange(w), np.arange(h))

    if flat:
        x = tf.reshape(x, [-1])
        y = tf.reshape(y, [-1])

    return x, y


def vec_vec_outer(a, b):
    return tf.einsum("...i,...j", a, b)

def estimate_fb_ml(
        input_image,
        input_alpha,
        min_size=2,
        growth_factor=2,
        regularization=1e-5,
        n_iter_func=2,
        print_info=True,):

    h0, w0 = 144, 256

    # Find initial image size.
    w = int(np.ceil(min_size * w0 / h0))
    h = min_size

    # Generate initial foreground and background from input image
    F = tf.image.resize_nearest_neighbor(input_image[tf.newaxis], [h, w])[0]
    B = F * 1.0
    while True:
        if print_info:
            print("New level of size: %d-by-%d" % (w, h))
        # Resize image and alpha to size of current level
        image = tf.image.resize_nearest_neighbor(input_image[tf.newaxis], [h, w])[0]
        alpha = tf.image.resize_nearest_neighbor(input_alpha[tf.newaxis, :, :, tf.newaxis], [h, w])[0, :, :, 0]
        # Iterate a few times
        n_iter = n_iter_func
        for iteration in range(n_iter):
            x, y = pixel_coordinates(w, h, flat=True) # w: 4, h: 2
            # Make alpha into a vector
            a = tf.reshape(alpha, [-1])
            # Build system of linear equations
            U = tf.stack([a, 1 - a], axis=1)
            A = vec_vec_outer(U, U) # 8 x 2 x 2
            b = vec_vec_outer(U, tf.reshape(image, [w*h, 3])) # 8 x 2 x 3
            # For each neighbor
            for dx, dy in [(-1, 0), (1, 0), (0, -1), (0, 1)]:
                x2 = tf.clip_by_value(x + dx, 0, w - 1)
                y2 = tf.clip_by_value(y + dy, 0, h - 1)
                # Vectorized neighbor coordinates
                j = x2 + y2 * w
                # Gradient of alpha
                a_j = tf.nn.embedding_lookup(a, j)
                da = regularization + tf.abs(a - a_j)
                # Update matrix of linear equation system
                A00 = A[:, 0, 0] + da
                A01 = A[:, 0, 1]
                A10 = A[:, 1, 0]
                A11 = A[:, 1, 1] + da
                A00 = A00[:, tf.newaxis, tf.newaxis]
                A01 = A01[:, tf.newaxis, tf.newaxis]
                A10 = A10[:, tf.newaxis, tf.newaxis]
                A11 = A11[:, tf.newaxis, tf.newaxis]
                A_temp1 = tf.concat([A00, A10], axis=1)
                A_temp2 = tf.concat([A01, A11], axis=1)
                A = tf.concat([A_temp1, A_temp2], axis=2)
                # Update rhs of linear equation system
                F_resp = tf.reshape(F, [w * h, 3])
                F_resp_j = tf.nn.embedding_lookup(F_resp, j)
                B_resp = tf.reshape(B, [w * h, 3])
                B_resp_j = tf.nn.embedding_lookup(B_resp, j)
                da_resp = tf.reshape(da, [w * h, 1])
                b0 = b[:, 0, :] + da_resp * F_resp_j
                b1 = b[:, 1, :] + da_resp * B_resp_j
                b = tf.concat([b0[:, tf.newaxis, :], b1[:, tf.newaxis, :]], axis=1)
                # Solve linear equation system for foreground and background
            fb = tf.clip_by_value(tf.matmul(inv2(A), b), 0, 1)

            F = tf.reshape(fb[:, 0, :], [h, w, 3])
            B = tf.reshape(fb[:, 1, :], [h, w, 3])

        # If original image size is reached, return result
        if w >= w0 and h >= h0:
            return F, B

        # Grow image size to next level
        w = min(w0, int(np.ceil(w * growth_factor)))
        h = min(h0, int(np.ceil(h * growth_factor)))

        F = tf.image.resize_nearest_neighbor(F[tf.newaxis], [h, w])[0]
        B = tf.image.resize_nearest_neighbor(B[tf.newaxis], [h, w])[0]



######################################################################
def estimate_foreground_background_tf():
    image_np = np.array(Image.open("./image.png").resize([256, 144]))[:, :, :3] / 255
    alpha_np = np.array(Image.open("./alpha.png").resize([256, 144])) / 255
    image = tf.placeholder(tf.float32, [144, 256, 3])
    alpha = tf.placeholder(tf.float32, [144, 256])
    foreground, background = estimate_fb_ml(image, alpha, n_iter_func=2)
    sess = tf.Session()
    for i in range(10):
        s = time.time()
        sess.run(foreground, feed_dict={image: image_np, alpha: alpha_np})
        e = time.time()
        print("time: ", e - s)


######################################################################
def main():
    estimate_foreground_background_tf()


if __name__ == "__main__":
    main()

i am getting division by zero errors in estimate_foreground_ml()

what i tried:

• pymatting 1.1.1 and 1.1.3
• making sure both the image and the mask are not uniform (i've seen the error when both have min_val=0 and max_val=1)
• default parameters and different variations

the environment is google colab. also sometime this (or something else in pymatting) causes the colab itself to crash and disconnect.