Micro-Manager GUI for Calcium Imaging

May 21, 2026 · View on GitHub

CI codecov

A Micro-Manager GUI based on pymmcore-widgets and pymmcore-plus.

It has been designed to record calcium imaging experiments with or without optical stimulation using Arduino and Thorlabs Components (paper in press...).

https://github.com/user-attachments/assets/3b8d973d-0259-4753-804d-880115057220

Table of Contents

To run

If you have uv installed, you can run micromanager-gui directly without installing it using:

uvx --from "git+https://github.com/fdrgsp/micromanager-gui" mmgui

To enable real-time Cellpose segmentation, add the cp3 or cp4 extra:

  • uvx --from "git+https://github.com/fdrgsp/micromanager-gui[cp4]" mmgui for Cellpose 4.x
  • uvx --from "git+https://github.com/fdrgsp/micromanager-gui[cp3]" mmgui for Cellpose 3.x

NOTE: uvx supports GPU acceleration on macOS only (via Apple MPS — no CUDA required). On Windows/Linux, use uv pip install instead (see Installation).

Installation

Create a virtual environment and install the package using uv (pip):

uv pip install "git+https://github.com/fdrgsp/micromanager-gui"

To enable real-time Cellpose segmentation, add the cp3 or cp4 extra:

uv pip install "git+https://github.com/fdrgsp/micromanager-gui[cp4]"  # Cellpose 4.x
uv pip install "git+https://github.com/fdrgsp/micromanager-gui[cp3]"  # Cellpose 3.x

To use Cellpose with GPU on Windows/Linux, install PyTorch with the CUDA version matching your driver as a second step:

uv pip install torch torchvision --index-url https://download.pytorch.org/whl/cu{VERSION}

Replace {VERSION} with your CUDA version (e.g. cu126, cu128, cu130). Run nvidia-smi to check which version your driver supports.

NOTE: NVIDIA Drivers should be already installed.

Note: this is also installing the PyQt6 library for the GUI.

Installing Micro-Manager

You also need to install the Micro-Manager device adapters and C++ core provided by mmCoreAndDevices. This can be done by following the steps described in the pymmcore-plus documentation page.

Run the Micro-Manger GUI

mmgui

By passing the -c or -config flag, you can specify the path of a micromanager configuration file you want to load. For example:

mmgui -c path/to/config.cfg

Run the Micro-Manger GUI with SlackBot

By passing the -s or -slack boolean flag, you will be able to use a SlackBot to control the microscope. In particular, you will be able to start and stop the acquisition and to get the progress of the acquisition.

For example:

mmgui -c path/to/config.cfg -s True

To enable the SlackBot, you first need to follow the instructions in the Slack Bolt documentation to create your Slack App and get your SLACK_BOT_TOKEN and SLACK_APP_TOKEN. In particular, go through the Create an app, Tokens and installing apps and Setting up your project sections (NOTE: you can use this App Manifest to create your Slack App).

The OAuth & Permissions Scope required are:

  • channels:history
  • channels:read
  • chat:write
  • commands

Since this SlackBot communicates with the Micro-Manager through a set of Slack commands, you also need to set up the following command in your Slack App Slash Commands section:

  • /run: Start the MDA Sequence
  • /cancel: Cancel the current MDA Sequence
  • /progress: Get the current MDA Sequence progress
  • /clear: Clear the chat from the SlackBot messages
  • /mda: Get the current MDASequence

Now that you have your SLACK_BOT_TOKEN and SLACK_APP_TOKEN, you can either create a .env file in the root of this project containing the SLACK_BOT_TOKEN and SLACK_APP_TOKEN variables (e.g. SLACK_BOT_TOKEN=xoxb-... and SLACK_APP_TOKEN=xapp...) or set them as global environment variables (e.g. export SLACK_BOT_TOKEN=xoxb-... and export SLACK_APP_TOKEN=xapp...).

The last step is to grant access to the desired Slack channel to the Slack App. This can be done by inviting the Slack App to the desired Slack channel: right-click on the channel name, select View channel details, select the Integrations tab and Add Apps. You now need to add to the .env file (or as global environment) a variable named CHANNEL_ID containing the Slack channel ID.

After that, you can run the GUI with the -s or -slack flag set to True and start using the Slack commands to interact with the microscope.

SlackBot App Manifest example

display_information:
  name: Eve
  description: A SlackBot for MicroManager & pymmcore-plus
  background_color: "#737373"
features:
  bot_user:
    display_name: Eve
    always_online: false
  slash_commands:
    - command: /run
      description: Run the MDA Acquisition
      should_escape: true
    - command: /cancel
      description: Cancel the ongoing MDA Acquisition
      should_escape: true
    - command: /progress
      description: Return the progress of the ongoing MDA Acquisition
      should_escape: true
    - command: /clear
      description: Clear the chat form the bot messages
      should_escape: true
    - command: /mda
      description: Return the current MDASequence.
      should_escape: true
oauth_config:
  scopes:
    bot:
      - chat:write
      - channels:read
      - channels:history
      - commands
settings:
  interactivity:
    is_enabled: true
  org_deploy_enabled: false
  socket_mode_enabled: true
  token_rotation_enabled: false

Segment, Extract and Analyze Calcium Imaging Data with cali

To explore the calcium imaging data acquired with micromanager-gui, you can use cali, a GUI that allows you to segment, analyze and visualize the calcium imaging data.

FigureS3_1

Run with cali

To run micromanager-gui and cali together, you can use:

  • uvx -p 3.12 --from "git+https://github.com/fdrgsp/micromanager-gui[cali4]" mmgui for Cellpose 4.x (cellpose-sam) (use python 3.11 or greater)

  • uvx -p 3.12 --from "git+https://github.com/fdrgsp/micromanager-gui[cali3]" mmgui for Cellpose 3.x (use python 3.11 or greater)

NOTE: uvx supports GPU acceleration on macOS only (via Apple MPS — no CUDA required). On Windows/Linux, use uv pip install instead (see below).

If you open the console widget from the micromanager-gui menu (Widget > Console), you can run cali by typing cali() in the console.

Install with cali

To install micromanager-gui with cali support, you can use:

  • uv pip install "git+https://github.com/fdrgsp/micromanager-gui[cali4]" for Cellpose 4.x (cellpose-sam) (use python 3.11 or greater)

  • uv pip install "git+https://github.com/fdrgsp/micromanager-gui[cali3]" for Cellpose 3.x (use python 3.11 or greater)

To use Cellpose with GPU on Windows/Linux, install PyTorch with the CUDA version matching your driver as a second step:

uv pip install torch torchvision --index-url https://download.pytorch.org/whl/cu{VERSION}

Replace {VERSION} with your CUDA version (e.g. cu126, cu128, cu130). Run nvidia-smi to check which version your driver supports.

NOTE: NVIDIA Drivers should be already installed.