1-PhdZddlZddlZddlmZddlmZmZddl m Z ddl m Z ddlZe jeZe jeZ ddlmZn#e$rd8d ZYnwxYwd Zd Ze\ZZd ZdZdZd9dZdZd:dZdZ dZ!dZ"dZ#dZ$dZ%dZ&dZ'dZ(dZ)dZ*dZ+d Z,d!Z-d"Z.d#Z/d$Z0d%Z1d&Z2d'Z3d(Z4d)Z5e5Z6d*Z7d+Z8d,Z9d-Z:d.Z;d/Zd2Z?d3Z@d4ZAd5ZBd6ZCd7ZDdS);z[Standard test images. For more images, see - http://sipi.usc.edu/database/database.php N) img_as_bool)registry registry_urls) __version__) file_hashsha256cnddl}||jvrtd|dd}||}t |d5}||}|r,||||}|,dddn #1swxYwY|S)a Calculate the hash of a given file. Useful for checking if a file has changed or been corrupted. Parameters ---------- fname : str The name of the file. alg : str The type of the hashing algorithm Returns ------- hash : str The hash of the file. Examples -------- >>> fname = "test-file-for-hash.txt" >>> with open(fname, "w") as f: ... __ = f.write("content of the file") >>> print(file_hash(fname)) 0fc74468e6a9a829f103d069aeb2bb4f8646bad58bf146bb0e3379b759ec4a00 >>> import os >>> os.remove(fname) rNz Algorithm 'z' not available in hashlibirb)hashlibalgorithms_available ValueErrornewopenreadupdate hexdigest)fnamealgr chunksizehasherfinbuffs V/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/skimage/data/_fetchers.pyr r s0  g2 2 2LCLLLMM M S!! %   +#88I&&D + d###xx ** + + + + + + + + + + + + + + + + !!!sABBBcTtj|sdSt||kS)z1Check if the provided path has the expected hash.F)ospexistsr )path expected_hashs r _has_hashr!Cs* :d  u T??m ++c  ddl}t|dsi}nddi}n#t$r dtfcYSwxYwdtvrt jdd}nt jdd}d|vrd }nd }|jd|d ||d d ttd|}tj t|j d}||fS)Nrrretry_if_failedz+gitz .dev0+gitz.dev+zChttps://github.com/scikit-image/scikit-image/raw/{version}/skimage/zDhttps://github.com/scikit-image/scikit-image/raw/v{version}/skimage/z scikit-imagemainSKIMAGE_DATADIR)rbase_urlversion version_devenvrurlsdata)poochhasattr ImportError_LEGACY_DATA_DIRrreplacecreateos_cacherrrjoinstrabspath)r0retryskimage_version_for_poochurl image_fetcherdata_dirs r_create_image_fetcherr?Js( & um,, +EE&*E &&&%%%%%&$/$7 V$L$L!!$/$7$D$D! '''VW!EL^^N + +)  " #M(xM122F;;H ( ""s 44cbdtjvr ddl}|d|ddSdS)zIf a test case is calling pooch, skip it. This running the test suite in environments without internet access, skipping only the tests that try to fetch external data. PYTEST_CURRENT_TESTrNzUnable to download T)allow_module_level)osenvironpytestskip) data_filenamerEs r!_skip_pytest_case_requiring_poochrHsI **   9-99d SSSSS +*r"c tjtj|ddtjtd}tj|d}tj|st j||dSdS)uPrepare local cache directory if it doesn't exist already. Creates:: /path/to/target_dir/ └─ data/ └─ README.txt r.Texist_okzdata/README.txtN)rCmakedirsrr7_DISTRIBUTION_DIRrshutilcopy2) target_dir readme_src readme_dests r_ensure_cache_dirrSs~KV,,t<<<<+->??J(:'899K :k " ". Z-----..r"c<t|}ttjt}nt tj}tj||}t||r|Stjt|}t||r|Stt|tdt| t |}|S#t$r$}t|td|d}~wwxYw)aFetch a given data file from either the local cache or the repository. This function provides the path location of the data file given its name in the scikit-image repository. If a data file is not included in the distribution and pooch is available, it is downloaded and cached. Parameters ---------- data_filename : str Name of the file in the scikit-image repository. e.g. 'restoration/tess/camera_rl.npy'. Returns ------- file_path : str Path of the local file. Raises ------ KeyError: If the filename is not known to the scikit-image distribution. ModuleNotFoundError: If the filename is known to the scikit-image distribution but pooch is not installed. ConnectionError: If scikit-image is unable to connect to the internet but the dataset has not been downloaded yet. NaThe requested file is part of the scikit-image distribution, but requires the installation of an optional dependency, pooch. To install pooch, use your preferred python package manager. Follow installation instruction found at https://scikit-image.org/docs/stable/user_guide/install.htmlrPzTried to download a scikit-image dataset, but no internet connection is available. To avoid this message in the future, try `skimage.data.download_all()` when you are connected to the internet.)r_image_fetcherrdirnamer>r8r9r7r!rMrHModuleNotFoundErrorrSfetchConnectionError)rGr cache_dircached_file_pathlegacy_file_patherrs r_fetchr_s;>]+MK)) .// x =99!=11 x 1=AA!=11 )-888! K   ++++ )// >>    )-888 )     sC-- D7DDcLttdtj} | tj|}|t_t tjtjD]}t|}|ttjs\tj tj|}tj tj |dtj|| |t_dS#|t_wxYw)akDownload all datasets for use with scikit-image offline. Scikit-image datasets are no longer shipped with the library by default. This allows us to use higher quality datasets, while keeping the library download size small. This function requires the installation of an optional dependency, pooch, to download the full dataset. Follow installation instruction found at https://scikit-image.org/docs/stable/user_guide/install.html Call this function to download all sample images making them available offline on your machine. Parameters ---------- directory: path-like, optional The directory where the dataset should be stored. Raises ------ ModuleNotFoundError: If pooch is not install, this error will be raised. Notes ----- scikit-image will only search for images stored in the default directory. Only specify the directory if you wish to download the images to your own folder for a particular reason. You can access the location of the default data directory by inspecting the variable ``skimage.data.data_dir``. NzTo download all package data, scikit-image needs an optional dependency, pooch.To install pooch, follow our installation instructions found at https://scikit-image.org/docs/stable/user_guide/install.htmlrUTrJ)rVrXrr expanduserrSrr_ startswithr8r7rCrLrWrNrO) directoryold_dirrG file_path dest_paths r download_allrgsB! K   !G&  y11I"+N ^%89999+4 3 3M}--I''N,?(@(@AA 3H^%8-HH  CK 22TBBBB Y 222 3&g%%%%s C"DD#c tdS)aKReturn the path to the XML file containing the weak classifier cascade. These classifiers were trained using LBP features. The file is part of the OpenCV repository [1]_. References ---------- .. [1] OpenCV lbpcascade trained files https://github.com/opencv/opencv/tree/master/data/lbpcascades z&data/lbpcascade_frontalface_opencv.xml)r_r/r"r!lbp_frontal_face_cascade_filenameri.s : ; ;;r"FcBddlm}|t||S)a"Load an image file located in the data directory. Parameters ---------- f : string File name. as_gray : bool, optional Whether to convert the image to grayscale. Returns ------- img : ndarray Image loaded from ``skimage.data_dir``. r)imreadas_gray)iorkr_)frmrks r_loadrp=s1" 6&))W - - --r"c tdS)aGray-level "camera" image. Can be used for segmentation and denoising examples. Returns ------- camera : (512, 512) uint8 ndarray Camera image. Notes ----- No copyright restrictions. CC0 by the photographer (Lav Varshney). .. versionchanged:: 0.18 This image was replaced due to copyright restrictions. For more information, please see [1]_. References ---------- .. [1] https://github.com/scikit-image/scikit-image/issues/3927 zdata/camera.pngrpr/r"rcamerarsS, " # ##r"c tdS)aA golden eagle. Suitable for examples on segmentation, Hough transforms, and corner detection. Notes ----- No copyright restrictions. CC0 by the photographer (Dayane Machado). Returns ------- eagle : (2019, 1826) uint8 ndarray Eagle image. zdata/eagle.pngrrr/r"reaglervls ! " ""r"c tdS)a=Color image of the astronaut Eileen Collins. Photograph of Eileen Collins, an American astronaut. She was selected as an astronaut in 1992 and first piloted the space shuttle STS-63 in 1995. She retired in 2006 after spending a total of 38 days, 8 hours and 10 minutes in outer space. This image was downloaded from the NASA Great Images database `__. No known copyright restrictions, released into the public domain. Returns ------- astronaut : (512, 512, 3) uint8 ndarray Astronaut image. zdata/astronaut.pngrrr/r"r astronautrx~s& % & &&r"c& tddS)aBrick wall. Returns ------- brick : (512, 512) uint8 image A small section of a brick wall. Notes ----- The original image was downloaded from `CC0Textures `_ and licensed under the Creative Commons CC0 License. A perspective transform was then applied to the image, prior to rotating it by 90 degrees, cropping and scaling it to obtain the final image. zdata/brick.pngTrlrrr/r"rbrickrzs&+X !4 0 0 00r"c& tddS)aGrass. Returns ------- grass : (512, 512) uint8 image Some grass. Notes ----- The original image was downloaded from `DeviantArt `__ and licensed under the Creative Commons CC0 License. The downloaded image was cropped to include a region of ``(512, 512)`` pixels around the top left corner, converted to grayscale, then to uint8 prior to saving the result in PNG format. zdata/grass.pngTrlrrr/r"rgrassr|s(2 !4 0 0 00r"c& tddS)aGravel Returns ------- gravel : (512, 512) uint8 image Grayscale gravel sample. Notes ----- The original image was downloaded from `CC0Textures `__ and licensed under the Creative Commons CC0 License. The downloaded image was then rescaled to ``(1024, 1024)``, then the top left ``(512, 512)`` pixel region was cropped prior to converting the image to grayscale and uint8 data type. The result was saved using the PNG format. zdata/gravel.pngTrlrrr/r"rgravelr~s(@ "D 1 1 11r"c tdS)aIGray-level "text" image used for corner detection. Notes ----- This image was downloaded from Wikipedia `__. No known copyright restrictions, released into the public domain. Returns ------- text : (172, 448) uint8 ndarray Text image. z data/text.pngrrr/r"rtextr=s  ! !!r"c tdS)a=Checkerboard image. Checkerboards are often used in image calibration, since the corner-points are easy to locate. Because of the many parallel edges, they also visualise distortions particularly well. Returns ------- checkerboard : (200, 200) uint8 ndarray Checkerboard image. zdata/chessboard_GRAY.pngrrr/r"r checkerboardrPs + , ,,r"c tdS)aw3D fluorescence microscopy image of cells. The returned data is a 3D multichannel array with dimensions provided in ``(z, c, y, x)`` order. Each voxel has a size of ``(0.29 0.26 0.26)`` micrometer. Channel 0 contains cell membranes, channel 1 contains nuclei. Returns ------- cells3d: (60, 2, 256, 256) uint16 ndarray The volumetric images of cells taken with an optical microscope. Notes ----- The data for this was provided by the Allen Institute for Cell Science. It has been downsampled by a factor of 4 in the row and column dimensions to reduce computational time. The microscope reports the following voxel spacing in microns: * Original voxel size is ``(0.290, 0.065, 0.065)``. * Scaling factor is ``(1, 4, 4)`` in each dimension. * After rescaling the voxel size is ``(0.29 0.26 0.26)``. zdata/cells3d.tifrrr/r"rcells3dr_4 # $ $$r"c tdS)avImage of human cells undergoing mitosis. Returns ------- human_mitosis: (512, 512) uint8 ndarray Data of human cells undergoing mitosis taken during the preparation of the manuscript in [1]_. Notes ----- Copyright David Root. Licensed under CC-0 [2]_. References ---------- .. [1] Moffat J, Grueneberg DA, Yang X, Kim SY, Kloepfer AM, Hinkle G, Piqani B, Eisenhaure TM, Luo B, Grenier JK, Carpenter AE, Foo SY, Stewart SA, Stockwell BR, Hacohen N, Hahn WC, Lander ES, Sabatini DM, Root DE (2006) A lentiviral RNAi library for human and mouse genes applied to an arrayed viral high-content screen. Cell, 124(6):1283-98 / :DOI: `10.1016/j.cell.2006.01.040` PMID 16564017 .. [2] GitHub licensing discussion https://github.com/CellProfiler/examples/issues/41 zdata/mitosis.tifrrr/r"r human_mitosisr|rr"c tdS)u#Cell floating in saline. This is a quantitative phase image retrieved from a digital hologram using the Python library ``qpformat``. The image shows a cell with high phase value, above the background phase. Because of a banding pattern artifact in the background, this image is a good test of thresholding algorithms. The pixel spacing is 0.107 µm. These data were part of a comparison between several refractive index retrieval techniques for spherical objects as part of [1]_. This image is CC0, dedicated to the public domain. You may copy, modify, or distribute it without asking permission. Returns ------- cell : (660, 550) uint8 array Image of a cell. References ---------- .. [1] Paul Müller, Mirjam Schürmann, Salvatore Girardo, Gheorghe Cojoc, and Jochen Guck. "Accurate evaluation of size and refractive index for spherical objects in quantitative phase imaging." Optics Express 26(8): 10729-10743 (2018). :DOI:`10.1364/OE.26.010729` z data/cell.pngrrr/r"rcellrs8  ! !!r"c tdS)axGreek coins from Pompeii. This image shows several coins outlined against a gray background. It is especially useful in, e.g. segmentation tests, where individual objects need to be identified against a background. The background shares enough grey levels with the coins that a simple segmentation is not sufficient. Notes ----- This image was downloaded from the `Brooklyn Museum Collection `__. No known copyright restrictions. Returns ------- coins : (303, 384) uint8 ndarray Coins image. zdata/coins.pngrrr/r"rcoinsrs, ! " ""r"c tdS)aMouse kidney tissue. This biological tissue on a pre-prepared slide was imaged with confocal fluorescence microscopy (Nikon C1 inverted microscope). Image shape is (16, 512, 512, 3). That is 512x512 pixels in X-Y, 16 image slices in Z, and 3 color channels (emission wavelengths 450nm, 515nm, and 605nm, respectively). Real-space voxel size is 1.24 microns in X-Y, and 1.25 microns in Z. Data type is unsigned 16-bit integers. Notes ----- This image was acquired by Genevieve Buckley at Monasoh Micro Imaging in 2018. License: CC0 Returns ------- kidney : (16, 512, 512, 3) uint16 ndarray Kidney 3D multichannel image. zdata/kidney.tifrrr/r"rkidneyrrtr"c tdS)a@Lily of the valley plant stem. This plant stem on a pre-prepared slide was imaged with confocal fluorescence microscopy (Nikon C1 inverted microscope). Image shape is (922, 922, 4). That is 922x922 pixels in X-Y, with 4 color channels. Real-space voxel size is 1.24 microns in X-Y. Data type is unsigned 16-bit integers. Notes ----- This image was acquired by Genevieve Buckley at Monasoh Micro Imaging in 2018. License: CC0 Returns ------- lily : (922, 922, 4) uint16 ndarray Lily 2D multichannel image. z data/lily.tifrrr/r"rlilyr*  ! !!r"c tdS)zyScikit-image logo, a RGBA image. Returns ------- logo : (500, 500, 4) uint8 ndarray Logo image. z data/logo.pngrrr/r"rlogors  ! !!r"c tdS)aGray-level "microaneurysms" image. Detail from an image of the retina (green channel). The image is a crop of image 07_dr.JPG from the High-Resolution Fundus (HRF) Image Database: https://www5.cs.fau.de/research/data/fundus-images/ Notes ----- No copyright restrictions. CC0 given by owner (Andreas Maier). Returns ------- microaneurysms : (102, 102) uint8 ndarray Retina image with lesions. References ---------- .. [1] Budai, A., Bock, R, Maier, A., Hornegger, J., Michelson, G. (2013). Robust Vessel Segmentation in Fundus Images. International Journal of Biomedical Imaging, vol. 2013, 2013. :DOI:`10.1155/2013/154860` zdata/microaneurysms.pngrrr/r"rmicroaneurysmsr s2 * + ++r"c tdS)zSurface of the moon. This low-contrast image of the surface of the moon is useful for illustrating histogram equalization and contrast stretching. Returns ------- moon : (512, 512) uint8 ndarray Moon image. z data/moon.pngrrr/r"rmoonr)  ! !!r"c tdS)zScanned page. This image of printed text is useful for demonstrations requiring uneven background illumination. Returns ------- page : (191, 384) uint8 ndarray Page image. z data/page.pngrrr/r"rpager7rr"c>ttddS)a<Black and white silhouette of a horse. This image was downloaded from `openclipart ` No copyright restrictions. CC0 given by owner (Andreas Preuss (marauder)). Returns ------- horse : (328, 400) bool ndarray Horse image. zdata/horse.pngTrl)rrpr/r"rhorserEs  u-t<<< = ==r"c tdS)awMotion blurred clock. This photograph of a wall clock was taken while moving the camera in an approximately horizontal direction. It may be used to illustrate inverse filters and deconvolution. Released into the public domain by the photographer (Stefan van der Walt). Returns ------- clock : (300, 400) uint8 ndarray Clock image. zdata/clock_motion.pngrrr/r"rclockrUs ( ) ))r"c tdS)aImmunohistochemical (IHC) staining with hematoxylin counterstaining. This picture shows colonic glands where the IHC expression of FHL2 protein is revealed with DAB. Hematoxylin counterstaining is applied to enhance the negative parts of the tissue. This image was acquired at the Center for Microscopy And Molecular Imaging (CMMI). No known copyright restrictions. Returns ------- immunohistochemistry : (512, 512, 3) uint8 ndarray Immunohistochemistry image. z data/ihc.pngrrr/r"rimmunohistochemistryrfs"   r"c tdS)aUChelsea the cat. An example with texture, prominent edges in horizontal and diagonal directions, as well as features of differing scales. Notes ----- No copyright restrictions. CC0 by the photographer (Stefan van der Walt). Returns ------- chelsea : (300, 451, 3) uint8 ndarray Chelsea image. zdata/chelsea.pngrrr/r"rchelsearzs # $ $$r"c tdS)asCoffee cup. This photograph is courtesy of Pikolo Espresso Bar. It contains several elliptical shapes as well as varying texture (smooth porcelain to coarse wood grain). Notes ----- No copyright restrictions. CC0 by the photographer (Rachel Michetti). Returns ------- coffee : (400, 600, 3) uint8 ndarray Coffee image. zdata/coffee.pngrrr/r"rcoffeers " # ##r"c tdS)a`Hubble eXtreme Deep Field. This photograph contains the Hubble Telescope's farthest ever view of the universe. It can be useful as an example for multi-scale detection. Notes ----- This image was downloaded from `HubbleSite `__. The image was captured by NASA and `may be freely used in the public domain `_. Returns ------- hubble_deep_field : (872, 1000, 3) uint8 ndarray Hubble deep field image. zdata/hubble_deep_field.jpgrrr/r"rhubble_deep_fieldrs* - . ..r"c tdS)uHuman retina. This image of a retina is useful for demonstrations requiring circular images. Notes ----- This image was downloaded from `wikimedia `. This file is made available under the Creative Commons CC0 1.0 Universal Public Domain Dedication. References ---------- .. [1] Häggström, Mikael (2014). "Medical gallery of Mikael Häggström 2014". WikiJournal of Medicine 1 (2). :DOI:`10.15347/wjm/2014.008`. ISSN 2002-4436. Public Domain Returns ------- retina : (1411, 1411, 3) uint8 ndarray Retina image in RGB. zdata/retina.jpgrrr/r"rretinars0 " # ##r"c$tddS)aShepp Logan Phantom. References ---------- .. [1] L. A. Shepp and B. F. Logan, "The Fourier reconstruction of a head section," in IEEE Transactions on Nuclear Science, vol. 21, no. 3, pp. 21-43, June 1974. :DOI:`10.1109/TNS.1974.6499235` Returns ------- phantom : (400, 400) float64 image Image of the Shepp-Logan phantom in grayscale. zdata/phantom.pngTrlrrr/r"rshepp_logan_phantomrs #T 2 2 22r"c tdS)zkColor Wheel. Returns ------- colorwheel : (370, 371, 3) uint8 image A colorwheel. zdata/color.pngrrr/r"r colorwheelrs ! " ""r"c tdS)aKReturn image sequence of in-vivo tissue showing the palisades of Vogt. In the human eye, the palisades of Vogt are normal features of the corneal limbus, which is the border between the cornea and the sclera (i.e., the white of the eye). In the image sequence, there are some dark spots due to the presence of dust on the reference mirror. Returns ------- palisades_of_vogt: (60, 1440, 1440) uint16 ndarray Notes ----- See info under `in-vivo-cornea-spots.tif` at https://gitlab.com/scikit-image/data/-/blob/master/README.md#data. zdata/palisades_of_vogt.tifrrr/r"rpalisades_of_vogtrs& - . ..r"c tdS)ajLaunch photo of DSCOVR on Falcon 9 by SpaceX. This is the launch photo of Falcon 9 carrying DSCOVR lifted off from SpaceX's Launch Complex 40 at Cape Canaveral Air Force Station, FL. Notes ----- This image was downloaded from `SpaceX Photos `__. The image was captured by SpaceX and `released in the public domain `_. Returns ------- rocket : (427, 640, 3) uint8 ndarray Rocket image. zdata/rocket.jpgrrr/r"rrocketrs( " # ##r"ctd}tj|d}tdtd|fS)a Rectified stereo image pair with ground-truth disparities. The two images are rectified such that every pixel in the left image has its corresponding pixel on the same scanline in the right image. That means that both images are warped such that they have the same orientation but a horizontal spatial offset (baseline). The ground-truth pixel offset in column direction is specified by the included disparity map. The two images are part of the Middlebury 2014 stereo benchmark. The dataset was created by Nera Nesic, Porter Westling, Xi Wang, York Kitajima, Greg Krathwohl, and Daniel Scharstein at Middlebury College. A detailed description of the acquisition process can be found in [1]_. The images included here are down-sampled versions of the default exposure images in the benchmark. The images are down-sampled by a factor of 4 using the function `skimage.transform.downscale_local_mean`. The calibration data in the following and the included ground-truth disparity map are valid for the down-sampled images:: Focal length: 994.978px Principal point x: 311.193px Principal point y: 254.877px Principal point dx: 31.086px Baseline: 193.001mm Returns ------- img_left : (500, 741, 3) uint8 ndarray Left stereo image. img_right : (500, 741, 3) uint8 ndarray Right stereo image. disp : (500, 741, 3) float ndarray Ground-truth disparity map, where each value describes the offset in column direction between corresponding pixels in the left and the right stereo images. E.g. the corresponding pixel of ``img_left[10, 10 + disp[10, 10]]`` is ``img_right[10, 10]``. NaNs denote pixels in the left image that do not have ground-truth. Notes ----- The original resolution images, images with different exposure and lighting, and ground-truth depth maps can be found at the Middlebury website [2]_. References ---------- .. [1] D. Scharstein, H. Hirschmueller, Y. Kitajima, G. Krathwohl, N. Nesic, X. Wang, and P. Westling. High-resolution stereo datasets with subpixel-accurate ground truth. In German Conference on Pattern Recognition (GCPR 2014), Muenster, Germany, September 2014. .. [2] http://vision.middlebury.edu/stereo/data/scenes2014/ zdata/motorcycle_disp.npzarr_0zdata/motorcycle_left.pngzdata/motorcycle_right.png)r_nploadrp)filenamedisps rstereo_motorcyclersGl011H 78  W %D , - -u5P/Q/QSW XXr"cDtjtdS)a*Subset of data from the LFW dataset. This database is a subset of the LFW database containing: * 100 faces * 100 non-faces The full dataset is available at [2]_. Returns ------- images : (200, 25, 25) uint8 ndarray 100 first images are faces and subsequent 100 are non-faces. Notes ----- The faces were randomly selected from the LFW dataset and the non-faces were extracted from the background of the same dataset. The cropped ROIs have been resized to a 25 x 25 pixels. References ---------- .. [1] Huang, G., Mattar, M., Lee, H., & Learned-Miller, E. G. (2012). Learning to align from scratch. In Advances in Neural Information Processing Systems (pp. 764-772). .. [2] http://vis-www.cs.umass.edu/lfw/ zdata/lfw_subset.npy)rrr_r/r"r lfw_subsetrZs: 76/00 1 11r"c tdS)aMicroscopy image of dermis and epidermis (skin layers). Hematoxylin and eosin stained slide at 10x of normal epidermis and dermis with a benign intradermal nevus. Notes ----- This image requires an Internet connection the first time it is called, and to have the ``pooch`` package installed, in order to fetch the image file from the scikit-image datasets repository. The source of this image is https://en.wikipedia.org/wiki/File:Normal_Epidermis_and_Dermis_with_Intradermal_Nevus_10x.JPG The image was released in the public domain by its author Kilbad. Returns ------- skin : (960, 1280, 3) RGB image of uint8 z data/skin.jpgrrr/r"rskinrzrr"c tdS)aPImage sequence of synchrotron x-radiographs showing the rapid solidification of a nickel alloy sample. Returns ------- nickel_solidification: (11, 384, 512) uint16 ndarray Notes ----- See info under `nickel_solidification.tif` at https://gitlab.com/scikit-image/data/-/blob/master/README.md#data. zdata/solidification.tifrrr/r"rnickel_solidificationrs * + ++r"c tdS)acMicroscopy image sequence with fluorescence tagging of proteins re-localizing from the cytoplasmic area to the nuclear envelope. Returns ------- protein_transport: (15, 2, 180, 183) uint8 ndarray Notes ----- See info under `NPCsingleNucleus.tif` at https://gitlab.com/scikit-image/data/-/blob/master/README.md#data. zdata/protein_transport.tifrrr/r"rprotein_transportrs - . ..r"c tdS)axSubset of data from the University of North Carolina Volume Rendering Test Data Set. The full dataset is available at [1]_. Returns ------- image : (10, 256, 256) uint16 ndarray Notes ----- The 3D volume consists of 10 layers from the larger volume. References ---------- .. [1] https://graphics.stanford.edu/data/voldata/ zdata/brain.tiffrrr/r"rbrainrs& " # ##r"c>tdtdfS)a3Case B1 image pair from the first PIV challenge. Returns ------- image0, image1 : (512, 512) grayscale images A pair of images featuring synthetic moving particles. Notes ----- This image was licensed as CC0 by its author, Prof. Koji Okamoto, with thanks to Prof. Jun Sakakibara, who maintains the PIV Challenge site. References ---------- .. [1] Particle Image Velocimetry (PIV) Challenge site http://pivchallenge.org .. [2] 1st PIV challenge Case B: http://pivchallenge.org/pub/index.html#b zdata/pivchallenge-B-B001_1.tifzdata/pivchallenge-B-B001_2.tifrrr/r"rvortexrs&( .// .// r")r )N)F)E__doc__numpyrrN util.dtyper _registryrrros.pathrrrCrW__file__r3rMr0r rXr!r?rVr>rHrSr_rgrirprsrvrxrzr|r~rrrrrrrrrrrrrrrrcatrrrrrrrrrrrrrrr/r"rrs $$$$$$........ 3;x((CK 011)"'"'"'"$"$"$"$"$"$"'"T,,,3#3#3#l1022TTT( . . . HHHV9&9&9&9&x < < <....,$$$2###$''',?1?1?1D-1-1-1`424242n"""& - - -%%%:%%%:""">###2$$$2"""0""",,,8 " " " " " " > > > ***"!!!(%%%&$$$&///0$$$6333"###///,$$$.8Y8Y8Yv222@"""0,,,"///"$$$,s A AA