ilastik Download available for all major platforms

Binaries

Choose from the download links below, and make sure your operating system satisfies the minimum requirements. For help with installation, see the installation instructions.

Release 1.4.1.post1 (31. May 2025)

Release Highlights:

  • Introduces support for the OME-Zarr file format
  • Added Trainable Domain Adaptation Workflow
  • Native build for Apple Silicon (M1, M2, M3, M4) and Intel Macs
  • Tiff reading improvements
  • Added spherical texture object features, contributed by Oane Gros (publication)
  • Better user interface in dark mode

Notes:

  • Native builds for Apple Silicon (M1, M2, M3, M4) and Intel Macs are available, which means better performance on these machines overall. Notes for the silicon version:
    • Currently only 2D networks are run accelerated on apple hardware, leveraging Metal Performance Shaders (mps), in the Neural Network and Trainable Domain Adaptation Workflows. 3D networks will fallback to CPU execution.
  • Commercial solver support with gurobi 12.0.0 for tracking with learning.
Regular builds
 Windows (64-bit) version 1.4.1.post1 (534 MB) Supported Versions: Windows 10 and up
 Linux (64-bit) version 1.4.1.post1 (786 MB) Supported Versions: Ubuntu 14 and up
 Apple intel (64-bit), OSX version 1.4.1.post1 (776 MB) Supported Versions: 10.9 and up
 Apple Silicon (arm64), OSX version 1.4.1.post1 (520 MB) Supported Versions: 11.0 and up
GPU-enabled builds
For faster neural network prediction. ilastik GPU-enabled builds are distributed with NVidia's CUDA toolkit. By downloading and using these builds, you accept the terms and conditions of the CUDA End User License Agreement (EULA).
 Windows (64-bit) version 1.4.1.post1-gpu (1.9 GB) Supported Versions: Windows 10 and up, comes with cudatoolkit 11.8
 Linux (64-bit) version 1.4.1.post1-gpu (3.4 GB) Supported Versions: Ubuntu 14 and up, comes with cudatoolkit 11.8


Previous stable versions

macOS compatibility note

Starting with macOS 11 (Big Sur), or newer ilastik versions older than 1.4.0 will not run anymore on MacOS. Please download the latest version.

Version 1.4.0.post1 (10. November 2023)

Release Highlights:

  • Neural Network Workflow: run pre-trained neural networks from Bioimage.io Model Zoo in ilastik
    • Networks can run on CPU, GPU (choose the GPU build for Windows, or Linux), or on a remote server
    • No Neural Network training, yet - we’re working on it.
  • New startup screen!
  • Major UI and performance improvements for the Multicut Workflow
  • Stability/Usability improvements in the Carving Workflow
  • By popular demand: redo/undo for brush-strokes
  • Many bugfixes throughout

ilastik 1.4.0 is distributed in two versions for Windows and Linux. In addition to our regular build, you can download GPU-enabled builds. With these you can run pre-trained neural network models from the bioimage.io Model Zoo faster, if you have a compatible nvidia GPU on your system. All other workflows, besides the Neural Network Workflow (local) will work on the CPU, like before.
If you are interested in running the ilastik Neural Network Workflow on a remote GPU, e.g. if you have a powerful server in your facility, you have to check for additional installation instructions for the server part in the tiktorch repository. After you install the server part, you can use your regular ilastik installation as a client with the Neural Network Workflow (remote), ilastik will take care of the communication with the server.
Commercial solver support with gurobi 951 for tracking with learning. Note that on OSX there is no 3D preview in Carving, all other functionality should work as expected. We recommend OSX users to download the current beta version. If you have an Apple Silicon (M1/M2/M3), then please select the "Apple Silicon (arm64)" build.
Regular builds
 Windows (64-bit) version 1.4.0.post1 (547 MB) Supported Versions: Windows 10
 Linux (64-bit) version 1.4.0.post1 (857 MB) Supported Versions: Ubuntu 14 and up
 Mac (64-bit), OSX version 1.4.0.post1 (739 MB) Supported Versions: 10.9 and up
GPU-enabled builds
For faster neural network prediction. ilastik GPU-enabled builds are distributed with NVidia's CUDA toolkit. By downloading and using these builds, you accept the terms and conditions of the CUDA End User License Agreement (EULA).
 Windows (64-bit) version 1.4.0.post1-gpu (1.8 GB) Supported Versions: Windows 10, comes with cudatoolkit 11.3
 Linux (64-bit) version 1.4.0.post1-gpu (2.9 GB) Supported Versions: Ubuntu 14 and up, comes with cudatoolkit 11.3


Version 1.3.3

Includes various improvements and bug fixes.
A few highlights:
  • 1.3.3post3, projects are opened readonly in headless mode per default
  • Support for n5 volumes (https://github.com/saalfeldlab/n5)
  • Support for masks in Pixel Classification (an additional dataset can be supplied that disables computation of probabilities wherever it is 0 -> speeds up computation in cases with a lot of background
  • Atlas Mask overlays for Object classification (an additional dataset can be supplied. Pixel values of this additional mask are included in result tables but not used in classification.)
  • counting fixes (saving boxes, import/export of boxes, interaction improvements)
  • autocontext now takes arbitrary data types (was previously limited to uint8), but mind the memory footprint! We still recommend to use uint8.
  • carving improvements, more efficient memory utilization
  • applet bar improvement, redesign
  • a lot of internal backend cleanups/improvements
  • a lot of internal GUI cleanups/improvements
  • updated dependency stack
For more details, see the Release Notes. Commercial solver support for cplex version 1290 and gurobi 811 for tracking with learning.
 Windows (64-bit) version 1.3.3post3 (2020-05-03) (mirror) Supported Versions: Windows 7 and later
 Linux (64-bit) version 1.3.3post3 (2020-05-03) (mirror) Supported Versions: glibc 2.5 and up
 Mac (64-bit), OSX version 1.3.3post3 (2020-05-03) (mirror) Supported Versions: 10.9 and up


Version 1.3.2

Please see our Release Notes for a summary of changes.
 Windows (64-bit) version 1.3.2post1 (2019-03-07) Supported Versions: Windows 7 and later
 Linux (64-bit) version 1.3.2post1 (2019-03-07) Supported Versions: glibc 2.5 and up
 Mac (64-bit), OSX version 1.3.2post1 (2019-03-07) Supported Versions: 10.9 and up

Version 1.3.0

We have updated all our dependencies, and switched from Python 2 to Python 3.
This could mean that projects created with older ilastik versions do not load any more and vice versa. We advise you to make copies of important project files before you try to use them with this new version of ilastik!
For more details, see the Release Notes.
 Windows (64-bit) version 1.3.0 (2018-01-26) Supported Versions: Windows 7 and later
 Linux (64-bit) version 1.3.0 (2018-01-26) Supported Versions: glibc 2.5 and up
 Mac (64-bit), OSX version 1.3.0 (2018-01-26) Supported Versions: 10.9 and up


Version 1.2.2 (based on Python 2)

 Windows (64-bit) version 1.2.2post2 (2017-11-29) Supported Versions: Windows 7 and later
 Linux (64-bit) version 1.2.2post2 (2017-11-29) Supported Versions: glibc 2.5 and up
 Mac (64-bit), OSX version 1.2.2post2 (2017-11-29) Supported Versions: Mountain Lion 10.9 and up

For the difference between the two versions, see Release Notes. For the news of the previous stable version, see previous Release Notes.



Example data and projects

Dataset Pixel Classification Object Classification Tracking (Automatic and Manual) Carving Density Counting Data Courtesy of
Mitocheck 2D+t (120 MB) Mitocheck project
Drosophila 3D+t (337 MB) Hufnagel, EMBL Heidelberg
Counting tutorial (3 MB) VisRec Project, University of Oxford
Lehmussola et al. TMI2007
FlyEM Project (48 MB) FlyEM Project, Janelia Research Campus
Helmstaedter (35 MB) Helmstaedter et al., Max Planck Institute for Medical Research
Small FIB/SEM stack (13.5 MB) Graham Knott, EPF Lausanne
Fly Bowl Video: Social Flies (130 MB) Kristin Branson, Janelia Research Campus
Larvae Arena Video (800 MB) Marta Zlatic, Janelia Research Campus