Skip to main content

JP2 (JPEG 2000 Part 1) image validator and properties extractor

Project description

jpylyzer

About

Jpylyzer is a JP2 (JPEG 2000 Part 1) image validator and properties extractor. Its development was partially supported by the SCAPE Project. The SCAPE project is co-funded by the European Union under FP7 ICT-2009.4.1 (Grant Agreement number 270137).

Jpylyzer homepage

Please visit the jpylyzer homepage for links to the most recent package downloads (Debian packages and Windows binaries), and a User Manual which documents all aspects of the software:

https://jpylyzer.openpreservation.org/

CI Status

  • Build Status Travis-CI

  • Build Status OPF Jenkins

Using jpylyzer from the command line

Calling jpylyzer in a command window without any arguments results in the following helper message:

usage: jpylyzer [-h] [--format FMT] [--mix {1,2}] [--nopretty]
            [--nullxml] [--recurse] [--packetmarkers] [--verbose]
            [--version] jp2In [jp2In ...]

Positional arguments

Argument Description
jp2In input image(s), may be one or more (whitespace-separated) path expressions; prefix wildcard (*) with backslash (\) in Linux

Optional arguments

Argument Description
[-h, --help] show help message and exit
[--format FMT] validation format; allowed values are jp2 (JPEG 2000 Part 1, used by default), j2c (Part 1 codestream), jph (JPEG 2000 Part 15 / High Throughput JPEG 2000) and jhc (Part 15 codestream)
[--mix {1,2}] report additional output in NISO MIX format (version 1.0 or 2.0)
[--nopretty] suppress pretty-printing of XML output
[--nullxml] extract null-terminated XML content from XML and UUID boxes(doesn't affect validation)
[--recurse, -r] when analysing a directory, recurse into subdirectories
[--packetmarkers] Report packet-level codestream markers (plm, ppm, plt, ppt)
[--verbose] report test results in verbose format
[-v, --version] show program's version number and exit

Output

Output is directed to the standard output device (stdout).

Examples

Validate JP2 image:

jpylyzer rubbish.jp2 > rubbish-jp2.xml`

Validate JPEG 2000 Part 1 codestream:

jpylyzer --format j2c rubbish.j2c > rubbish-j2c.xml`

Validate JPH (High Throughput) image:

jpylyzer --format jph rubbish.jph > rubbish-jph.xml`

Validate JPEG 2000 Part 15 (High Throughput) codestream:

jpylyzer --format jhc rubbish.jhc > rubbish-jhc.xml`

In the above examples, output is redirected to the output files ‘rubbish-???.xml’. By default jpylyzer’s XML is pretty-printed, so you should be able to view the file using your favourite text editor. Alternatively use a dedicated XML editor, or open the file in your web browser.

Output format

The output file contains the following top-level elements:

  1. One toolInfo element, which contains information about jpylyzer (its name and version number)

  2. One or more file elements, each of which contain information about about the analysed files

In turn, each file element contains the following sub-elements:

  1. fileInfo: general information about the analysed file

  2. statusInfo: information about the status of jpylyzer's validation attempt

  3. isValid: outcome of the validation

  4. tests: outcome of the individual tests that are part of the validation process (organised by box)

  5. properties: image properties (organised by box)

  6. propertiesExtension: wrapper element for NISO MIX output (only if the --mix option is used)

  7. warnings: reported warnings

Using jpylyzer as a Python module

Instead of using jpylyzer from the command-line, you can also import it as a module in your own Python programs. To do so, install jpylyzer with pip. Then import jpylyzer into your code by adding:

from jpylyzer import jpylyzer

Subsequently you can call any function that is defined in jpylyzer.py. In practice you will most likely only need the checkOneFile function. The following minimal script shows how this works:

#! /usr/bin/env python3

from jpylyzer import jpylyzer

# Define JP2
myFile = "/home/johan/jpylyzer-test-files/aware.jp2"

# Analyse with jpylyzer, result to Element object
myResult = jpylyzer.checkOneFile(myFile)

# Return image height value
imageHeight = myResult.findtext('./properties/jp2HeaderBox/imageHeaderBox/height')
print(imageHeight)

Here, myResult is an Element object that can either be used directly, or converted to XML using the ElementTree module[^3].

For validation a raw JPEG 2000 codestreams, call the checkOneFile function with the additional validationFormat argument, and set it to j2c:

# Define Codestream
myFile = "/home/johan/jpylyzer-test-files/rubbish.j2c"

# Analyse with jpylyzer, result to Element object
myResult = jpylyzer.checkOneFile(myFile, 'j2c')

Steps in preparing a jpylyzer release

See instructions here

Project details


Download files

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

Source Distribution

jpylyzer-2.2.1.tar.gz (2.3 MB view details)

Uploaded Source

Built Distribution

jpylyzer-2.2.1-py2.py3-none-any.whl (52.8 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file jpylyzer-2.2.1.tar.gz.

File metadata

  • Download URL: jpylyzer-2.2.1.tar.gz
  • Upload date:
  • Size: 2.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.12

File hashes

Hashes for jpylyzer-2.2.1.tar.gz
Algorithm Hash digest
SHA256 834ac425946c79878805343c461cba346f3b2d97a910653a1f9e153d9a8243e6
MD5 09baefc7dd2fde201f145cd9de6f70ba
BLAKE2b-256 f5e8374f6984f2a8a39ef4b1045b3ff4fa86ec6b9201c6d668a96d2b81b78640

See more details on using hashes here.

File details

Details for the file jpylyzer-2.2.1-py2.py3-none-any.whl.

File metadata

  • Download URL: jpylyzer-2.2.1-py2.py3-none-any.whl
  • Upload date:
  • Size: 52.8 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.12

File hashes

Hashes for jpylyzer-2.2.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 f026a857d99f40c0618d1f779504edb805fdb97b128a7d2eeac09a4bca0abada
MD5 81def12f6ea81f845a108fc75abe5f43
BLAKE2b-256 82cd28de72ca166be24a1bb5695d45f7ebf40f3d00a60bdc9602a31fccf722c3

See more details on using hashes here.

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