Skip to main content

Pure python tiff tools to handle all tags and IFDs.

Project description

Pure Python tools for reading and writing all TIFF IFDs, sub-IFDs, and tags.

Developed by Kitware, Inc. with funding from The National Cancer Institute.

Example

import tifftools
info = tifftools.read_tiff('photograph.tif')
info['ifds'][0]['tags'][tifftools.Tag.ImageDescription.value] = {
    'data': 'A dog digging.',
    'datatype': tifftools.Datatype.ASCII
}
exififd = info['ifds'][0]['tags'][tifftools.Tag.EXIFIFD.value]['ifds'][0][0]
exififd['tags'][tifftools.constants.EXIFTag.FNumber.value] = {
    'data': [54, 10],
    'datatype': tifftools.Datatype.RATIONAL
}
tifftools.write_tiff(info, 'photograph_tagged.tif')

Commands

tifftools --help and tifftools <command> --help provide usage details.

  • tifftools split [--subifds] [--overwrite] source [prefix]: split a tiff file into separate files. This is also available as the library function tifftools.tiff_split.

  • tifftools concat [--overwrite] source [source ...] output: merge multiple tiff files together. Alias: tifftools merge. This is also available as the library function tifftools.tiff_concat.

  • tifftools dump [--max MAX] [--json] source [source ...]: print information about a tiff file, including all tags, IFDs, and subIFDs. Alias: tifftool info. This is also available as the library function tifftools.tiff_dump.

  • tifftools set source [--overwrite] [output] [--set TAG[:DATATYPE][,<IFD-#>] VALUE] [--unset TAG:[,<IFD-#>]] [--setfrom TAG[,<IFD-#>] TIFFPATH]: modify, add, or remove tags. This is also available as the library function tifftools.tiff_set.

Library Functions

  • read_tiff

  • write_tiff

  • Constants

  • Tag

  • Datatype

  • get_or_create_tag

  • EXIFTag, GPSTag, etc.

Installation

tifftools is available on PyPI and conda-forge.

To install with pip from PyPI:

pip install tifftools

To install with conda:

conda install -c conda-forge tifftools

Purpose

tifftools provides a library and a command line program for maniplulating TIFF files. It can split multiple images apart, merge images together, set any tag in any IFD, and dump all IFDs and tags in a single command. It only uses python standard library modules, and is therefore widely compatible.

Rationale

There was a need to combine images from multiple TIFF files without altering the image data or losing any tag information. Further, when changing tag values, it was essential that the old values were fully removed from the output.

The command line tools associated with libtiff are commonly used for similar purposes. The libtiff command tools have significant limitations: tiffdump and tiffinfo require multiple commands to see information from all IFDs. tiffset does not remove data from a file; rather it appends to the file to only reference new data, leaving the old values inside the file. tiffsplit doesn’t keep tags it doesn’t recognize, loosing data. tiffcp always reencodes images and will fail for compression types it does not know.

Likewise, there is a wide variety of EXIF tools. For the most part, these only alter tags, usually by appending to the existing file. ImageMagick’s convert command also recompresses images as it combines them.

Many programs deal with both classic and BigTIFF. Some will start writing a classic TIFF, but leave a small amount of unused space just after the file header. If the file exceeds 4Gb, parts of the file are rewritten to convert it to a BigTIFF file, leaving small amounts of abandoned data within the file.

tifftools fills this need. All tags are copied, even if unknown. Files are always rewritten so that there is never abandoned data inside the file. tifftools dump shows information on all IFDs and tags. Many of the command line options are directly inspired from libtiff.

tifftools does NOT compress or decompress any image data. This is not an image viewer. If you need to recompress an image or otherwise manipulate pixel data, use libtiff or another library.

As an explicit example, with libtiff’s tiffset, tag data just gets dereferenced and is still in the file:

$ grep 'secret' photograph.tif  || echo 'not present'
not present
$ tiffset -s ImageDescription "secret phrase" photograph.tif
$ tiffinfo photograph.tif | grep ImageDescription
  ImageDescription: secret phrase
$ grep 'secret' photograph.tif  || echo 'not present'
Binary file photograph.tif matches
$ tiffset photograph.tif -s ImageDescription "public phrase"
$ tiffinfo photograph.tif | grep ImageDescription
  ImageDescription: public phrase
$ grep 'secret' photograph.tif  || echo 'not present'
Binary file photograph.tif matches

Whereas, with tifftools:

$ grep 'secret' photograph.tif || echo 'not present'
not present
$ tifftools set -y -s ImageDescription "secret phrase" photograph.tif
$ tiffinfo photograph.tif | grep ImageDescription
  ImageDescription: secret phrase
$ grep 'secret' photograph.tif || echo 'not present'
Binary file photograph.tif matches
$ tifftools set -y photograph.tif -s ImageDescription "public phrase"
$ tiffinfo photograph.tif | grep ImageDescription
  ImageDescription: public phrase $ grep 'secret' photograph.tif || echo
  'not present' not present

TIFF File Structure

TIFF Files consist of one or more IFDs (Image File Directories). These can be located anywhere within the file, and are referenced by their absolute position within the file. IFDs can refer to image data; they can also contain a collection of metadata (for instance, EXIF or GPS data). Small data values are stored directly in the IFD. Bigger data values (such as image data, longer strings, or lists of numbers) are referenced by the IFD and are stored elsewhere in the file.

In the simple case, a TIFF file may have a list of IFDs, each one referencing the next. However, a complex TIFF file, such as those used by some Whole-Slide Image (WSI) microscopy systems, can have IFDs organized in a branching structure, where some IFDs are in a list and some reference SubIFDs with additional images.

TIFF files can have their primary data stored in either little-endian or big-endian format. Offsets to data are stored as absolute numbers inside a TIFF file. There are two variations: “classic” and “BigTIFF” which use 32-bits and 64-bits for these offsets, respectively. If the file size exceeds 4 Gb or uses 64-bit integer datatypes, it must be written as a BigTIFF.

Limitations

Unknown tags that are offsets and have a datatype other than IFD or IFD8 won’t be copied properly, as it is impossible to distinguish integer data from offsets given LONG or LONG8 datatypes. This can be remedied by defining a new TiffConstant record which contains a bytecounts entry to instruct whether the offsets refer to fixed length data or should get the length of data from another tag.

Because files are ALWAYS rewritten, tifftools is slower than libtiff’s tiffset and most EXIF tools.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tifftools-1.3.12.tar.gz (54.1 kB view details)

Uploaded Source

Built Distribution

tifftools-1.3.12-py3-none-any.whl (39.0 kB view details)

Uploaded Python 3

File details

Details for the file tifftools-1.3.12.tar.gz.

File metadata

  • Download URL: tifftools-1.3.12.tar.gz
  • Upload date:
  • Size: 54.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.17

File hashes

Hashes for tifftools-1.3.12.tar.gz
Algorithm Hash digest
SHA256 decf64b41444014e96544e451f8e45eb1d3787528b50f946a5dd9452c70499ec
MD5 f3aa2edffd9048768dfe284d6b75f56f
BLAKE2b-256 b04cc7da0abfabffc8d3735cc3f8080952273e3b7db9c1654a92a77c29a22acd

See more details on using hashes here.

Provenance

File details

Details for the file tifftools-1.3.12-py3-none-any.whl.

File metadata

  • Download URL: tifftools-1.3.12-py3-none-any.whl
  • Upload date:
  • Size: 39.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.17

File hashes

Hashes for tifftools-1.3.12-py3-none-any.whl
Algorithm Hash digest
SHA256 f738a2786e785411048fde8005f21fa8c342503e351ced1e72707507a7d0d7cf
MD5 2cabf09a029d8de107566cffb745bd77
BLAKE2b-256 7a173ec55d9bb5297dc4e225dd69c579b1d4f3f33883a35596f4823a9aa85797

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page