Python wrapper for ImageJ
Project description
Python wrapper for ImageJ
pyimagej
provides a set of
wrapper functions for integration between ImageJ and Python.
It also provides a high-level entry point imagej.IJ
for invoking
ImageJ Server APIs;
see "ImageJ Server" below for details.
Installation
-
Install Conda:
- On Windows, install Conda using Chocolatey:
choco install miniconda3
- On macOS, install Conda using Homebrew:
brew install miniconda
- On Linux, install Conda using its RPM or Debian package, or with the Miniconda install script.
- On Windows, install Conda using Chocolatey:
-
Activate the conda-forge channel:
conda config --add channels conda-forge conda config --set channel_priority strict
-
Install pyimagej into a new conda environment:
conda create -n pyimagej pyimagej openjdk=8
-
Whenever you want to use pyimagej, activate its environment:
conda activate pyimagej
Installation asides
-
If you want to use scikit-image in conjunction, as demonstrated below, you can install it also via:
conda install scikit-image
-
The above command installs pyimagej with OpenJDK 8; if you leave off the
openjdk=8
it will install OpenJDK 11 by default, which should also work, but is less well tested and may have more rough edges. -
It is possible to dynamically install pyimagej from within a Jupyter notebook:
import sys !conda install --yes --prefix {sys.prefix} -c conda-forge pyimagej openjdk=8
-
If you would prefer to install pyimagej via pip, more legwork is required. See this thread for hints.
Usage
Quick start
Creating the ImageJ gateway
Newest available version
If you want to launch the newest available release version of ImageJ:
import imagej
ij = imagej.init()
This invocation will automatically download and cache the newest release of net.imagej:imagej.
Explicitly specified version
You can specify a particular version, to facilitate reproducibility:
import imagej
ij = imagej.init('2.0.0-rc-68')
ij.getVersion()
With graphical capabilities
If you want to have support for the graphical user interface:
import imagej
ij = imagej.init(headless=False)
ij.ui().showUI()
Note there are issues with Java AWT via Python on macOS; see this article for a workaround.
Including ImageJ 1.x support
By default, the ImageJ gateway will not include the legacy layer for backwards compatibility with ImageJ 1.x. You can enable the legacy layer as follows:
import imagej
ij = imagej.init('net.imagej:imagej+net.imagej:imagej-legacy')
Including Fiji plugins
By default, the ImageJ gateway will include base ImageJ2 functionality only, without additional plugins such as those that ship with the Fiji distribution of ImageJ.
You can create an ImageJ gateway including Fiji plugins as follows:
import imagej
ij = imagej.init('sc.fiji:fiji')
From a local installation
If you have an installation of ImageJ2 such as Fiji, you can wrap an ImageJ gateway around it:
import imagej
ij = imagej.init('/Applications/Fiji.app')
Replace /Applications/Fiji.app
with the actual location of your installation.
With more memory available to Java
Java's virtual machine (the JVM) has a "max heap" value limiting how much memory it can use. You can increase the value as follows:
import scyjava_config
scyjava_config.add_options('-Xmx6g')
import imagej
ij = imagej.init()
Replace 6g
with the amount of memory Java should have. You can also pass
other JVM arguments.
Using the ImageJ gateway
Once you have your ImageJ gateway, you can start using it. Here is an example:
# Import an image with scikit-image.
import skimage
from skimage import io
# NB: Blood vessel image from: https://www.fi.edu/heart/blood-vessels
img = io.imread('https://www.fi.edu/sites/fi.live.franklinds.webair.com/files/styles/featured_large/public/General_EduRes_Heart_BloodVessels_0.jpg')
import numpy as np
img = np.mean(img, axis=2)
# Invoke ImageJ's Frangi vesselness op.
vessels = np.zeros(img.shape, dtype=img.dtype)
ij.op().filter().frangiVesselness(ij.py.to_java(vessels), ij.py.to_java(img), [1, 1], 20)
See also test/test_imagej.py
for other examples of usage.
ImageJ Server
Requirements
The imagej.server module has its own requirements:
requests
is required to communicate with the ImageJ server.pillow
is required for theimagej.server.IJ.show()
function. In addition,display
orxv
must be available to view the image.
Usage
There is a short usage example here.
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
Built Distribution
File details
Details for the file pyimagej-0.5.0.tar.gz
.
File metadata
- Download URL: pyimagej-0.5.0.tar.gz
- Upload date:
- Size: 9.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/2.7.16
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8774772b5d5c8189e8ba6a217713f10ff3a5815e7005ee0933822f52650243d0 |
|
MD5 | 389264bbc1ea555616475cc1a4ccfe2f |
|
BLAKE2b-256 | 22266a7417193a9975acd9528c47f6e9a650dea15c50b45b809e0da930050c1b |
File details
Details for the file pyimagej-0.5.0-py2-none-any.whl
.
File metadata
- Download URL: pyimagej-0.5.0-py2-none-any.whl
- Upload date:
- Size: 8.9 kB
- Tags: Python 2
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/2.7.16
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | d93b4ca9f61887ac26fd478ce8bf5c1b2d274907dab38bc6da9da221c33d1522 |
|
MD5 | d819c36aa9384c6ffd45aef2187a2fea |
|
BLAKE2b-256 | c8e10baf96a878bb70f4fe21e8c1103e94aa5a5d3c17433f4034019bb4e96274 |