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diff --git a/silx/image/marchingsquares/__init__.py b/silx/image/marchingsquares/__init__.py
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--- a/silx/image/marchingsquares/__init__.py
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-# coding: utf-8
-# /*##########################################################################
-# Copyright (C) 2018 European Synchrotron Radiation Facility
-#
-# Permission is hereby granted, free of charge, to any person obtaining a copy
-# of this software and associated documentation files (the "Software"), to deal
-# in the Software without restriction, including without limitation the rights
-# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-# copies of the Software, and to permit persons to whom the Software is
-# furnished to do so, subject to the following conditions:
-#
-# The above copyright notice and this permission notice shall be included in
-# all copies or substantial portions of the Software.
-#
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
-# THE SOFTWARE.
-#
-# ############################################################################*/
-"""
-This module provides implementations based on marching squares algorithms.
-
-The main implementation is done by :class:`MarchingSquaresMergeImpl`. It was
-designed to speed up the computation of iso surface using Cython and OpenMP.
-It also provides features like support of mask, and cache of min/max per tiles
-which is very efficient to find many iso contours from image gradient.
-
-Utilitary functions are provided as facade for simple use.
-:meth:`find_contours` to find iso contours from an image and using the same
-main signature as `find_contours` from `skimage`, but supporting mask.
-And :meth:`find_pixels` which returns a set of pixel coords containing the
-points of the iso contours.
-"""
-
-__authors__ = ["V. Valls"]
-__license__ = "MIT"
-__date__ = "02/07/2018"
-
-
-from ._mergeimpl import MarchingSquaresMergeImpl
-
-
-def _factory(engine, image, mask):
-    """Factory to create the marching square implementation from the engine
-    name"""
-    if engine == "merge":
-        return MarchingSquaresMergeImpl(image, mask)
-    elif engine == "skimage":
-        from _skimage import MarchingSquaresSciKitImage
-        return MarchingSquaresSciKitImage(image, mask)
-    else:
-        raise ValueError("Engine '%s' is not supported ('merge' or 'skimage' expected).")
-
-
-def find_pixels(image, level, mask=None):
-    """
-    Find the pixels following the iso contours at the given `level`.
-
-    These pixels are localized by the bound of the segment generated by the
-    iso contour algorithm.
-
-    The result is returned as a numpy array storing a list of coordinates y/x.
-
-    .. code-block:: python
-
-        # Example using a mask
-        shape = 100, 100
-        image = numpy.random.random(shape)
-        mask = numpy.random.random(shape) < 0.01
-        pixels = silx.image.marchingsquares.find_pixels(image, 0.5, mask=mask)
-
-    :param numpy.ndarray image: Image to process
-    :param float level: Level of the requested iso contours.
-    :param numpy.ndarray mask: An optional mask (a non-zero value invalidate
-        the pixels of the image)
-    :returns: An array of coordinates in y/x
-    :rtype: numpy.ndarray
-    """
-    assert(image is not None)
-    if mask is not None:
-        assert(image.shape == mask.shape)
-    engine = "merge"
-    impl = _factory(engine, image, mask)
-    return impl.find_pixels(level)
-
-
-def find_contours(image, level, mask=None):
-    """
-    Find the iso contours at the given `level`.
-
-    The result is returned as a list of polygons.
-
-    .. code-block:: python
-
-        # Example using a mask
-        shape = 100, 100
-        image = numpy.random.random(shape)
-        mask = numpy.random.random(shape) < 0.01
-        polygons = silx.image.marchingsquares.find_contours(image, 0.5, mask=mask)
-
-    :param numpy.ndarray image: Image to process
-    :param float level: Level of the requested iso contours.
-    :param numpy.ndarray mask: An optional mask (a non-zero value invalidate
-        the pixels of the image)
-    :returns: A list of array containing y-x coordinates of points
-    :rtype: List[numpy.ndarray]
-    """
-    assert(image is not None)
-    if mask is not None:
-        assert(image.shape == mask.shape)
-    engine = "merge"
-    impl = _factory(engine, image, mask)
-    return impl.find_contours(level)