update

.CondaPkg/env/Lib/site-packages/skimage/data/README.txt

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+This directory contains sample data from scikit-image.
+
+By default, it only contains a small subset of the entire dataset.
+
+The full detaset can be downloaded by using the following commands from
+a python console.
+
+  >>> from skimage.data import download_all
+  >>> download_all()

.CondaPkg/env/Lib/site-packages/skimage/data/__init__.py

@@ -0,0 +1,14 @@
+"""
+Test images and datasets.
+
+A curated set of general purpose and scientific images used in tests, examples,
+and documentation.
+
+Newer datasets are no longer included as part of the package, but are
+downloaded on demand. To make data available offline, use :func:`download_all`.
+
+"""
+
+import lazy_loader as lazy
+
+__getattr__, __dir__, __all__ = lazy.attach_stub(__name__, __file__)

.CondaPkg/env/Lib/site-packages/skimage/data/__init__.pyi

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+__all__ = [
+    'astronaut',
+    'binary_blobs',
+    'brain',
+    'brick',
+    'camera',
+    'cat',
+    'cell',
+    'cells3d',
+    'checkerboard',
+    'chelsea',
+    'clock',
+    'coffee',
+    'coins',
+    'colorwheel',
+    'data_dir',
+    'download_all',
+    'eagle',
+    'file_hash',
+    'grass',
+    'gravel',
+    'horse',
+    'hubble_deep_field',
+    'human_mitosis',
+    'immunohistochemistry',
+    'kidney',
+    'lbp_frontal_face_cascade_filename',
+    'lfw_subset',
+    'lily',
+    'logo',
+    'microaneurysms',
+    'moon',
+    'nickel_solidification',
+    'page',
+    'protein_transport',
+    'retina',
+    'rocket',
+    'shepp_logan_phantom',
+    'skin',
+    'stereo_motorcycle',
+    'text',
+    'vortex',
+]
+
+from ._binary_blobs import binary_blobs
+from ._fetchers import (
+    astronaut,
+    brain,
+    brick,
+    camera,
+    cat,
+    cell,
+    cells3d,
+    checkerboard,
+    chelsea,
+    clock,
+    coffee,
+    coins,
+    colorwheel,
+    data_dir,
+    download_all,
+    eagle,
+    file_hash,
+    grass,
+    gravel,
+    horse,
+    hubble_deep_field,
+    human_mitosis,
+    immunohistochemistry,
+    kidney,
+    lbp_frontal_face_cascade_filename,
+    lfw_subset,
+    lily,
+    logo,
+    microaneurysms,
+    moon,
+    nickel_solidification,
+    page,
+    palisades_of_vogt,
+    protein_transport,
+    retina,
+    rocket,
+    shepp_logan_phantom,
+    skin,
+    stereo_motorcycle,
+    text,
+    vortex,
+)

.CondaPkg/env/Lib/site-packages/skimage/data/_binary_blobs.py

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+import numpy as np
+
+from .._shared.filters import gaussian
+
+
+def binary_blobs(
+    length=512, blob_size_fraction=0.1, n_dim=2, volume_fraction=0.5, rng=None
+):
+    """
+    Generate synthetic binary image with several rounded blob-like objects.
+
+    Parameters
+    ----------
+    length : int, optional
+        Linear size of output image.
+    blob_size_fraction : float, optional
+        Typical linear size of blob, as a fraction of ``length``, should be
+        smaller than 1.
+    n_dim : int, optional
+        Number of dimensions of output image.
+    volume_fraction : float, default 0.5
+        Fraction of image pixels covered by the blobs (where the output is 1).
+        Should be in [0, 1].
+    rng : {`numpy.random.Generator`, int}, optional
+        Pseudo-random number generator.
+        By default, a PCG64 generator is used (see :func:`numpy.random.default_rng`).
+        If `rng` is an int, it is used to seed the generator.
+
+    Returns
+    -------
+    blobs : ndarray of bools
+        Output binary image
+
+    Examples
+    --------
+    >>> from skimage import data
+    >>> data.binary_blobs(length=5, blob_size_fraction=0.2)  # doctest: +SKIP
+    array([[ True, False,  True,  True,  True],
+           [ True,  True,  True, False,  True],
+           [False,  True, False,  True,  True],
+           [ True, False, False,  True,  True],
+           [ True, False, False, False,  True]])
+    >>> blobs = data.binary_blobs(length=256, blob_size_fraction=0.1)
+    >>> # Finer structures
+    >>> blobs = data.binary_blobs(length=256, blob_size_fraction=0.05)
+    >>> # Blobs cover a smaller volume fraction of the image
+    >>> blobs = data.binary_blobs(length=256, volume_fraction=0.3)
+
+    """
+
+    rs = np.random.default_rng(rng)
+    shape = tuple([length] * n_dim)
+    mask = np.zeros(shape)
+    n_pts = max(int(1.0 / blob_size_fraction) ** n_dim, 1)
+    points = (length * rs.random((n_dim, n_pts))).astype(int)
+    mask[tuple(indices for indices in points)] = 1
+    mask = gaussian(
+        mask, sigma=0.25 * length * blob_size_fraction, preserve_range=False
+    )
+    threshold = np.percentile(mask, 100 * (1 - volume_fraction))
+    return np.logical_not(mask < threshold)

.CondaPkg/env/Lib/site-packages/skimage/data/_registry.py

@@ -0,0 +1,187 @@
+# flake8: noqa
+
+# This minimal dataset was available as part of
+# scikit-image 0.15 and will be retained until
+# further notice.
+# Testing data and additional datasets should only
+# be made available by pooch
+legacy_datasets = [
+    'astronaut.png',
+    'brick.png',
+    'camera.png',
+    'chessboard_GRAY.png',
+    'chessboard_RGB.png',
+    'chelsea.png',
+    'clock_motion.png',
+    'coffee.png',
+    'coins.png',
+    'color.png',
+    'cell.png',
+    'grass.png',
+    'gravel.png',
+    'horse.png',
+    'hubble_deep_field.jpg',
+    'ihc.png',
+    'lbpcascade_frontalface_opencv.xml',
+    'lfw_subset.npy',
+    'logo.png',
+    'microaneurysms.png',
+    'moon.png',
+    'page.png',
+    'text.png',
+    'retina.jpg',
+    'rocket.jpg',
+    'phantom.png',
+    'motorcycle_disp.npz',
+    'motorcycle_left.png',
+    'motorcycle_right.png',
+]
+
+# Registry of datafiles that can be downloaded along with their SHA256 hashes
+# To generate the SHA256 hash, use the command
+# openssl sha256 filename
+registry = {
+    "color/tests/data/lab_array_a_10.npy": "a3ef76f1530e374f9121020f1f220bc89767dc866f4bbd1b1f47e5b84891a38c",
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+    "data/bw_text_skeleton.npy": "9ff4fc23c6a01497d7987f14e3a97cbcc39cce54b2b3b7ee33b84c1b661d0ae1",
+    "data/_blobs_3d_fiji_skeleton.tif": "e3449ad9819425959952050c147278555e5ffe1c2c4a30df29f6a1f9023e10c3",
+    "data/checker_bilevel.png": "2e207e486545874a2a3e69ba653b28fdef923157be9017559540e65d1bcb8e28",
+    "restoration/tests/astronaut_rl.npy": "3f8373e2c6182a89366e51cef6624e3625deac75fdda1079cbdad2a33322152c",
+    "restoration/tests/camera_rl.npy": "fd4f59af84dd471fbbe79ee70c1b7e68a69864c461f0db5ac587e7975363f78f",
+    "restoration/tests/camera_unsup.npy": "3de10a0b97267352b18886b25d66a967f9e1d78ada61050577d78586cab82baa",
+    "restoration/tests/camera_unsup2.npy": "29cdc60605eb528c5f014baa8564d7d1ba0bd4b3170a66522058cbe5aed0960b",
+    "restoration/tests/camera_wiener.npy": "4505ea8b0d63d03250c6d756560d615751b76dd6ffc4a95972fa260c0c84633e",
+    "registration/tests/data/OriginalX-130Y130.png": "bf24a06d99ae131c97e582ef5e1cd0c648a8dad0caab31281f3564045492811f",
+    "registration/tests/data/OriginalX130Y130.png": "7fdd4c06d504fec35ee0703bd7ed2c08830b075a74c8506bae4a70d682f5a2db",
+    "registration/tests/data/OriginalX75Y75.png": "c5cd58893c93140df02896df80b13ecf432f5c86eeaaf8fb311aec52a65c7016",
+    "registration/tests/data/TransformedX-130Y130.png": "1cda90ed69c921eb7605b73b76d141cf4ea03fb8ce3336445ca08080e40d7375",
+    "registration/tests/data/TransformedX130Y130.png": "bb10c6ae3f91a313b0ac543efdb7ca69c4b95e55674c65a88472a6c4f4692a25",
+    "registration/tests/data/TransformedX75Y75.png": "a1e9ead5f8e4a0f604271e1f9c50e89baf53f068f1d19fab2876af4938e695ea",
+    "data/brain.tiff": "bcdbaf424fbad7b1fb0f855f608c68e5a838f35affc323ff04ea17f678eef5c6",
+    "data/cells3d.tif": "afc7c7d80d38bfde09788b4064ac1e64ec14e88454ab785ebdc8dbba5ca3b222",
+    "data/palisades_of_vogt.tif": "7f205b626407e194974cead67c4d3909344cf59c42d229a349da0198183e5bd0",
+    "data/kidney.tif": "80c0799bc58b08cf6eaa53ecd202305eb42fd7bc73746cb6c5064dbeae7e8476",
+    "data/lily.tif": "395c2f0194c25b9824a8cd79266920362a0816bc9e906dd392adce2d8309af03",
+    "data/mitosis.tif": "2751ba667c4067c5d30817cff004aa06f6f6287f1cdbb5b8c9c6a500308cb456",
+    "data/skin.jpg": "8759fe080509712163453f4b17106582b8513e73b0788d80160abf840e272075",
+    "data/pivchallenge-B-B001_1.tif": "e95e09abbcecba723df283ac7d361766328abd943701a2ec2f345d4a2014da2a",
+    "data/pivchallenge-B-B001_2.tif": "4ceb5407e4e333476a0f264c14b7a3f6c0e753fcdc99ee1c4b8196e5f823805e",
+    "data/protein_transport.tif": "a8e24e8d187f33e92ee28508d5615286c850ca75374af7e74e527d290e8b06ea",
+    "data/solidification.tif": "50ef9a52c621b7c0c506ad1fe1b8ee8a158a4d7c8e50ddfce1e273a422dca3f9",
+}
+
+registry_urls = {
+    "data/brain.tiff": "https://gitlab.com/scikit-image/data/-/raw/2cdc5ce89b334d28f06a58c9f0ca21aa6992a5ba/brain.tiff",
+    "data/cells3d.tif": "https://gitlab.com/scikit-image/data/-/raw/2cdc5ce89b334d28f06a58c9f0ca21aa6992a5ba/cells3d.tif",
+    "data/palisades_of_vogt.tif": "https://gitlab.com/scikit-image/data/-/raw/b2bc880f3bac23a583724befe8388dae368c52fe/in-vivo-cornea-spots.tif",
+    "data/eagle.png": "https://gitlab.com/scikit-image/data/-/raw/1e4f62ac31ba4553d176d4473a5967ad1b076d62/eagle.png",
+    "data/kidney.tif": "https://gitlab.com/scikit-image/data/-/raw/2cdc5ce89b334d28f06a58c9f0ca21aa6992a5ba/kidney-tissue-fluorescence.tif",
+    "data/lily.tif": "https://gitlab.com/scikit-image/data/-/raw/2cdc5ce89b334d28f06a58c9f0ca21aa6992a5ba/lily-of-the-valley-fluorescence.tif",
+    "data/mitosis.tif": "https://gitlab.com/scikit-image/data/-/raw/2cdc5ce89b334d28f06a58c9f0ca21aa6992a5ba/AS_09125_050116030001_D03f00d0.tif",
+    "data/rank_filters_tests_3d.npz": "https://gitlab.com/scikit-image/data/-/raw/2cdc5ce89b334d28f06a58c9f0ca21aa6992a5ba/Tests_besides_Equalize_Otsu/add18_entropy/rank_filters_tests_3d.npz",
+    "data/skin.jpg": "https://gitlab.com/scikit-image/data/-/raw/2cdc5ce89b334d28f06a58c9f0ca21aa6992a5ba/Normal_Epidermis_and_Dermis_with_Intradermal_Nevus_10x.JPG",
+    "data/pivchallenge-B-B001_1.tif": "https://gitlab.com/scikit-image/data/-/raw/2cdc5ce89b334d28f06a58c9f0ca21aa6992a5ba/pivchallenge/B/B001_1.tif",
+    "data/pivchallenge-B-B001_2.tif": "https://gitlab.com/scikit-image/data/-/raw/2cdc5ce89b334d28f06a58c9f0ca21aa6992a5ba/pivchallenge/B/B001_2.tif",
+    "data/protein_transport.tif": "https://gitlab.com/scikit-image/data/-/raw/2cdc5ce89b334d28f06a58c9f0ca21aa6992a5ba/NPCsingleNucleus.tif",
+    "data/solidification.tif": "https://gitlab.com/scikit-image/data/-/raw/2cdc5ce89b334d28f06a58c9f0ca21aa6992a5ba/nickel_solidification.tif",
+    "restoration/tests/astronaut_rl.npy": "https://gitlab.com/scikit-image/data/-/raw/2cdc5ce89b334d28f06a58c9f0ca21aa6992a5ba/astronaut_rl.npy",
+    "data/gray_morph_output.npz": "https://gitlab.com/scikit-image/data/-/raw/806548e112bcf2b708a9a32275d335cb592480fd/Tests_besides_Equalize_Otsu/gray_morph_output.npz",
+}
+
+legacy_registry = {
+    ('data/' + filename): registry['data/' + filename] for filename in legacy_datasets
+}

.CondaPkg/env/Lib/site-packages/skimage/data/tests/test_data.py

@@ -0,0 +1,215 @@
+from packaging.version import Version
+
+import numpy as np
+import skimage.data as data
+from skimage.data._fetchers import _image_fetcher
+from skimage import io
+from skimage._shared.testing import assert_equal, assert_almost_equal, fetch
+import os
+import pytest
+
+
+def test_download_all_with_pooch():
+    # jni first wrote this test with the intention of
+    # fully deleting the files in the data_dir,
+    # then ensure that the data gets downloaded accordingly.
+    # hmaarrfk raised the concern that this test wouldn't
+    # play well with parallel testing since we
+    # may be breaking the global state that certain other
+    # tests require, especially in parallel testing
+
+    # The second concern is that this test essentially uses
+    # a lot of bandwidth, which is not fun for developers on
+    # lower speed connections.
+    # https://github.com/scikit-image/scikit-image/pull/4666/files/26d5138b25b958da6e97ebf979e9bc36f32c3568#r422604863
+    data_dir = data.data_dir
+    if _image_fetcher is not None:
+        data.download_all()
+        assert 'astronaut.png' in os.listdir(data_dir)
+        assert len(os.listdir(data_dir)) > 50
+    else:
+        with pytest.raises(ModuleNotFoundError):
+            data.download_all()
+
+
+def test_astronaut():
+    """Test that "astronaut" image can be loaded."""
+    astronaut = data.astronaut()
+    assert_equal(astronaut.shape, (512, 512, 3))
+
+
+def test_camera():
+    """Test that "camera" image can be loaded."""
+    cameraman = data.camera()
+    assert_equal(cameraman.ndim, 2)
+
+
+def test_checkerboard():
+    """Test that "checkerboard" image can be loaded."""
+    data.checkerboard()
+
+
+def test_chelsea():
+    """Test that "chelsea" image can be loaded."""
+    data.chelsea()
+
+
+def test_clock():
+    """Test that "clock" image can be loaded."""
+    data.clock()
+
+
+def test_coffee():
+    """Test that "coffee" image can be loaded."""
+    data.coffee()
+
+
+def test_eagle():
+    """Test that "eagle" image can be loaded."""
+    # Fetching the data through the testing module will
+    # cause the test to skip if pooch isn't installed.
+    fetch('data/eagle.png')
+    eagle = data.eagle()
+    assert_equal(eagle.ndim, 2)
+    assert_equal(eagle.dtype, np.dtype('uint8'))
+
+
+def test_horse():
+    """Test that "horse" image can be loaded."""
+    horse = data.horse()
+    assert_equal(horse.ndim, 2)
+    assert_equal(horse.dtype, np.dtype('bool'))
+
+
+def test_hubble():
+    """Test that "Hubble" image can be loaded."""
+    data.hubble_deep_field()
+
+
+def test_immunohistochemistry():
+    """Test that "immunohistochemistry" image can be loaded."""
+    data.immunohistochemistry()
+
+
+def test_logo():
+    """Test that "logo" image can be loaded."""
+    logo = data.logo()
+    assert_equal(logo.ndim, 3)
+    assert_equal(logo.shape[2], 4)
+
+
+def test_moon():
+    """Test that "moon" image can be loaded."""
+    data.moon()
+
+
+def test_page():
+    """Test that "page" image can be loaded."""
+    data.page()
+
+
+def test_rocket():
+    """Test that "rocket" image can be loaded."""
+    data.rocket()
+
+
+def test_text():
+    """Test that "text" image can be loaded."""
+    data.text()
+
+
+def test_stereo_motorcycle():
+    """Test that "stereo_motorcycle" image can be loaded."""
+    data.stereo_motorcycle()
+
+
+def test_binary_blobs():
+    blobs = data.binary_blobs(length=128)
+    assert_almost_equal(blobs.mean(), 0.5, decimal=1)
+    blobs = data.binary_blobs(length=128, volume_fraction=0.25)
+    assert_almost_equal(blobs.mean(), 0.25, decimal=1)
+    blobs = data.binary_blobs(length=32, volume_fraction=0.25, n_dim=3)
+    assert_almost_equal(blobs.mean(), 0.25, decimal=1)
+    other_realization = data.binary_blobs(length=32, volume_fraction=0.25, n_dim=3)
+    assert not np.all(blobs == other_realization)
+
+
+def test_lfw_subset():
+    """Test that "lfw_subset" can be loaded."""
+    data.lfw_subset()
+
+
+def test_skin():
+    """Test that "skin" image can be loaded.
+
+    Needs internet connection.
+    """
+    skin = data.skin()
+    assert skin.ndim == 3
+
+
+def test_cell():
+    """Test that "cell" image can be loaded."""
+    data.cell()
+
+
+def test_cells3d():
+    """Needs internet connection."""
+    path = fetch('data/cells3d.tif')
+    image = io.imread(path)
+    assert image.shape == (60, 2, 256, 256)
+
+
+def test_brain_3d():
+    """Needs internet connection."""
+    path = fetch('data/brain.tiff')
+    image = io.imread(path)
+    assert image.shape == (10, 256, 256)
+
+
+@pytest.mark.xfail(
+    Version(np.__version__) >= Version('2.0.0.dev0'),
+    reason='tifffile uses deprecated attribute `ndarray.newbyteorder`',
+)
+def test_kidney_3d_multichannel():
+    """Test that 3D multichannel image of kidney tissue can be loaded.
+
+    Needs internet connection.
+    """
+    fetch('data/kidney.tif')
+    kidney = data.kidney()
+    assert kidney.shape == (16, 512, 512, 3)
+
+
+@pytest.mark.xfail(
+    Version(np.__version__) >= Version('2.0.0.dev0'),
+    reason='tifffile uses deprecated attribute `ndarray.newbyteorder`',
+)
+def test_lily_multichannel():
+    """Test that microscopy image of lily of the valley can be loaded.
+
+    Needs internet connection.
+    """
+    fetch('data/lily.tif')
+    lily = data.lily()
+    assert lily.shape == (922, 922, 4)
+
+
+def test_vortex():
+    fetch('data/pivchallenge-B-B001_1.tif')
+    fetch('data/pivchallenge-B-B001_2.tif')
+    image0, image1 = data.vortex()
+    for image in [image0, image1]:
+        assert image.shape == (512, 512)
+
+
+@pytest.mark.parametrize(
+    'function_name',
+    [
+        'file_hash',
+    ],
+)
+def test_fetchers_are_public(function_name):
+    # Check that the following functions that are only used indirectly in the
+    # above tests are public.
+    assert hasattr(data, function_name)