328 lines
11 KiB
Python
328 lines
11 KiB
Python
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# -*- coding: utf-8 -*-
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# imageio is distributed under the terms of the (new) BSD License.
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""" Storage of image data in tiff format.
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"""
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import datetime
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from .. import formats
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from ..core import Format
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import numpy as np
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_tifffile = None # Defer loading to lib() function.
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def load_lib():
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global _tifffile
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try:
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import tifffile as _tifffile
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except ImportError:
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from . import _tifffile
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return _tifffile
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TIFF_FORMATS = (".tif", ".tiff", ".stk", ".lsm")
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WRITE_METADATA_KEYS = (
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"photometric",
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"planarconfig",
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"resolution",
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"description",
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"compress",
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"predictor",
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"volume",
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"writeshape",
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"extratags",
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"datetime",
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)
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READ_METADATA_KEYS = (
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"planar_configuration",
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"is_fluoview",
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"is_nih",
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"is_contig",
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"is_micromanager",
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"is_ome",
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"is_lsm" "is_palette",
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"is_reduced",
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"is_rgb",
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"is_sgi",
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"is_shaped",
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"is_stk",
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"is_tiled",
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"is_mdgel" "resolution_unit",
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"compression",
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"predictor",
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"is_mediacy",
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"orientation",
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"description",
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"description1",
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"is_imagej",
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"software",
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)
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class TiffFormat(Format):
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""" Provides support for a wide range of Tiff images.
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Images that contain multiple pages can be read using ``imageio.mimread()``
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to read the individual pages, or ``imageio.volread()`` to obtain a
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single (higher dimensional) array.
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Parameters for reading
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----------------------
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offset : int
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Optional start position of embedded file. By default this is
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the current file position.
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size : int
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Optional size of embedded file. By default this is the number
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of bytes from the 'offset' to the end of the file.
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multifile : bool
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If True (default), series may include pages from multiple files.
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Currently applies to OME-TIFF only.
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multifile_close : bool
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If True (default), keep the handles of other files in multifile
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series closed. This is inefficient when few files refer to
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many pages. If False, the C runtime may run out of resources.
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Parameters for saving
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---------------------
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bigtiff : bool
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If True, the BigTIFF format is used.
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byteorder : {'<', '>'}
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The endianness of the data in the file.
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By default this is the system's native byte order.
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software : str
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Name of the software used to create the image.
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Saved with the first page only.
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Metadata for reading
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--------------------
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planar_configuration : {'contig', 'planar'}
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Specifies if samples are stored contiguous or in separate planes.
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By default this setting is inferred from the data shape.
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'contig': last dimension contains samples.
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'planar': third last dimension contains samples.
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resolution_unit : (float, float) or ((int, int), (int, int))
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X and Y resolution in dots per inch as float or rational numbers.
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compression : int
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Value indicating the compression algorithm used, e.g. 5 is LZW,
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7 is JPEG, 8 is deflate.
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If 1, data are uncompressed.
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predictor : int
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Value 2 indicates horizontal differencing was used before compression,
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while 3 indicates floating point horizontal differencing.
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If 1, no prediction scheme was used before compression.
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orientation : {'top_left', 'bottom_right', ...}
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Oriented of image array.
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is_rgb : bool
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True if page contains a RGB image.
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is_contig : bool
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True if page contains a contiguous image.
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is_tiled : bool
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True if page contains tiled image.
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is_palette : bool
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True if page contains a palette-colored image and not OME or STK.
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is_reduced : bool
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True if page is a reduced image of another image.
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is_shaped : bool
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True if page contains shape in image_description tag.
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is_fluoview : bool
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True if page contains FluoView MM_STAMP tag.
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is_nih : bool
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True if page contains NIH image header.
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is_micromanager : bool
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True if page contains Micro-Manager metadata.
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is_ome : bool
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True if page contains OME-XML in image_description tag.
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is_sgi : bool
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True if page contains SGI image and tile depth tags.
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is_stk : bool
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True if page contains UIC2Tag tag.
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is_mdgel : bool
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True if page contains md_file_tag tag.
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is_mediacy : bool
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True if page contains Media Cybernetics Id tag.
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is_stk : bool
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True if page contains UIC2Tag tag.
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is_lsm : bool
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True if page contains LSM CZ_LSM_INFO tag.
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description : str
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Image description
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description1 : str
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Additional description
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is_imagej : None or str
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ImageJ metadata
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software : str
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Software used to create the TIFF file
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datetime : datetime.datetime
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Creation date and time
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Metadata for writing
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--------------------
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photometric : {'minisblack', 'miniswhite', 'rgb'}
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The color space of the image data.
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By default this setting is inferred from the data shape.
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planarconfig : {'contig', 'planar'}
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Specifies if samples are stored contiguous or in separate planes.
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By default this setting is inferred from the data shape.
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'contig': last dimension contains samples.
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'planar': third last dimension contains samples.
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resolution : (float, float) or ((int, int), (int, int))
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X and Y resolution in dots per inch as float or rational numbers.
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description : str
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The subject of the image. Saved with the first page only.
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compress : int
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Values from 0 to 9 controlling the level of zlib (deflate) compression.
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If 0, data are written uncompressed (default).
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predictor : bool
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If True, horizontal differencing is applied before compression.
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Note that using an int literal 1 actually means no prediction scheme
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will be used.
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volume : bool
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If True, volume data are stored in one tile (if applicable) using
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the SGI image_depth and tile_depth tags.
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Image width and depth must be multiple of 16.
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Few software can read this format, e.g. MeVisLab.
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writeshape : bool
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If True, write the data shape to the image_description tag
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if necessary and no other description is given.
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extratags: sequence of tuples
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Additional tags as [(code, dtype, count, value, writeonce)].
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code : int
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The TIFF tag Id.
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dtype : str
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Data type of items in 'value' in Python struct format.
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One of B, s, H, I, 2I, b, h, i, f, d, Q, or q.
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count : int
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Number of data values. Not used for string values.
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value : sequence
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'Count' values compatible with 'dtype'.
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writeonce : bool
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If True, the tag is written to the first page only.
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"""
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def _can_read(self, request):
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# We support any kind of image data
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return request.extension in self.extensions
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def _can_write(self, request):
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# We support any kind of image data
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return request.extension in self.extensions
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# -- reader
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class Reader(Format.Reader):
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def _open(self, **kwargs):
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if not _tifffile:
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load_lib()
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# Allow loading from http; tifffile uses seek, so download first
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if self.request.filename.startswith(("http://", "https://")):
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self._f = f = open(self.request.get_local_filename(), "rb")
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else:
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self._f = None
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f = self.request.get_file()
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self._tf = _tifffile.TiffFile(f, **kwargs)
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# metadata is the same for all images
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self._meta = {}
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def _close(self):
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self._tf.close()
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if self._f is not None:
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self._f.close()
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def _get_length(self):
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if self.request.mode[1] in "vV":
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return 1 # or can there be pages in pages or something?
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else:
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return len(self._tf.pages)
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def _get_data(self, index):
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if self.request.mode[1] in "vV":
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# Read data as single 3D (+ color channels) array
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if index != 0:
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raise IndexError('Tiff support no more than 1 "volume" per file')
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im = self._tf.asarray() # request as singleton image
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meta = self._meta
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else:
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# Read as 2D image
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if index < 0 or index >= self._get_length():
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raise IndexError("Index out of range while reading from tiff file")
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im = self._tf.pages[index].asarray()
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meta = self._meta or self._get_meta_data(index)
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# Return array and empty meta data
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return im, meta
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def _get_meta_data(self, index):
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page = self._tf.pages[index or 0]
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for key in READ_METADATA_KEYS:
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try:
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self._meta[key] = getattr(page, key)
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except Exception:
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pass
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# tifffile <= 0.12.1 use datetime, newer use DateTime
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for key in ("datetime", "DateTime"):
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try:
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self._meta["datetime"] = datetime.datetime.strptime(
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page.tags[key].value, "%Y:%m:%d %H:%M:%S"
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)
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break
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except Exception:
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pass
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return self._meta
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# -- writer
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class Writer(Format.Writer):
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def _open(self, bigtiff=None, byteorder=None, software=None):
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if not _tifffile:
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load_lib()
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try:
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self._tf = _tifffile.TiffWriter(
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self.request.get_file(), bigtiff, byteorder, software=software
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)
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self._software = None
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except TypeError:
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# In tifffile >= 0.15, the `software` arg is passed to
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# TiffWriter.save
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self._tf = _tifffile.TiffWriter(
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self.request.get_file(), bigtiff, byteorder
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)
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self._software = software
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self._meta = {}
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def _close(self):
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self._tf.close()
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def _append_data(self, im, meta):
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if meta:
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self.set_meta_data(meta)
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# No need to check self.request.mode; tifffile figures out whether
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# this is a single page, or all page data at once.
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if self._software is None:
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self._tf.save(np.asanyarray(im), **self._meta)
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else:
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# tifffile >= 0.15
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self._tf.save(np.asanyarray(im), software=self._software, **self._meta)
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def set_meta_data(self, meta):
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self._meta = {}
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for (key, value) in meta.items():
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if key in WRITE_METADATA_KEYS:
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# Special case of previously read `predictor` int value
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# 1(=NONE) translation to False expected by TiffWriter.save
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if key == "predictor" and not isinstance(value, bool):
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self._meta[key] = value > 1
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else:
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self._meta[key] = value
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# Register
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format = TiffFormat("tiff", "TIFF format", TIFF_FORMATS, "iIvV")
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formats.add_format(format)
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