ImSwitchUC2 2.1.0

Microscopy control

ImSwitch

ImSwitch is a software solution in Python that aims at generalizing microscope control by using an architecture based on the model-view-presenter (MVP) to provide a solution for flexible control of multiple microscope modalities.

Statement of need

The constant development of novel microscopy methods with an increased number of dedicated hardware devices poses significant challenges to software development. ImSwitch is designed to be compatible with many different microscope modalities and customizable to the specific design of individual custom-built microscopes, all while using the same software. We would like to involve the community in further developing ImSwitch in this direction, believing that it is possible to integrate current state-of-the-art solutions into one unified software.

Installation

Option A: Standalone bundles for Windows

Windows users can download ImSwitch in standalone format from the releases page on GitHub. Further information is available there. An existing Python installation is not required.

In order to tart do the following: Download the latest Artifact: https://github.com/openUC2/ImSwitch/actions/workflows/imswitch-bundle.yml

set SETUPTOOLS_USE_DISTUTILS=stdlib
ImSwitch.exe

Option B: Install using pip

ImSwitch is also published on PyPI and can be installed using pip. Python 3.7 or later is required. Additionally, certain components (the image reconstruction module and support for TIS cameras) require the software to be running on Windows, but most of the functionality is available on other operating systems as well.

To install ImSwitch from PyPI, run the following command:

pip install ImSwitch

You will then be able to start ImSwitch with this command:

imswitch

(Developers installing ImSwitch from the source repository should run pip install -r requirements-dev.txt instead, and start it using python -m imswitch)

Option C: Install from Github (UC2 version)

Installation

cd ~/Documents
git clone https://github.com/openUC2/ImSwitch/
cd ImSwitch
# alternatively download this repo, unzip the .zip-file and open the command prompt in this directory
conda create -n imswitch python=3.9 -y
conda activate imswitch
pip install -r requirements.txt --user
#pip install -e ./
pip install -e . --use-deprecated=legacy-resolver
pip install git+https://gitlab.com/bionanoimaging/nanoimagingpack

cd ~/Documents/
# if there is a folder called ImSwitchConfig => rename it!
git clone https://github.com/beniroquai/ImSwitchConfig
# Alternatively download the repository as a zip, unzip the file into the folder Documents/ImSwitchConfig

On Mac with ARM

On Mac (with M1 chip and on) open a terminal and enter arch to verify that your system-architecture is arm64. Now you have two options:

1) Emulating Intel-chipset like behaviour

To emulate the used Intel-chipset like behaviour configure a second terminal according to this guide. Once done, open this terminal, type arch again and verify that it is now emulating i386. Now you can continue the standard installation-procedure as given below.

brew install --cask mambaforge
mamba init 
# open new shell
mamba create -n imswitch python=3.9

mamba install -c conda-forge napari

nano setup.cfg
# comment pypylon and QScintila and PyQtWebEngine and PyQT5
pip install --no-deps <LIB_NAME>

In the above code-snipped we suggest to use mamba which is a faster reimplementation of conda that still uses the same syntax and servers/packages. Make sure to have a look into the documentation of mamba and to check the status of the brew-package before installation. first Once all easily compatible packages are installed run pip install --no-deps <LIB_NAME> and replace <LIB_NAME> with the commented packages individually, so e.g. pip install --no-deps pypylon and so on.

2) Working on arm64 chipset (e.g. Mac M1, M2 and on)

If you decided to stay with the native arm64 chipset you will face various issues while trying to install a couple of libraries, because they are not build (and maintained) yet for arm64. Yet, with the necessary packages and recipies being available on conda-forge these packages can be simply build on the target machine (not only macOS, but e.g. Raspberry Pi or Nano or ...). As opposed to the suggest global installation of prebuild packages using brew (e.g. in case of PyQt5) we suggest to keep everything in local environments for easy portability, reproduceability and traceability.

On example of the QtScintilla package for PyQt5 we will demonstrate how to build the existing conda-recipe on your machine. First, try to install as many packages as possible along the installation description above.

In our case mamba install -c conda-forge qt-main=5.15.6 did not succeed as somehow the downloading-pipe always broke and so the downloaded package was incomplete. Downloading the package by hand solved the problem. To find the package URL, first find out the correct package version (in our case qt-main-5.15.6-hda43d4a_5.conda) and then type mamba search qt-main="5.15.6 hda43d4a_5" --info in your terminal. You will find the url in the upfollowing list, here https://conda.anaconda.org/conda-forge/osx-arm64/qt-main-5.15.6-hda43d4a_5.conda with timestamp 2022-12-19 00:52:55 UTC. Download it into your active environment's packages folder, which on default is /opt/homebrew/Caskroom/mambaforge/base/envs/imswitch/pkgs.

As expected pip install --no-deps QScintila fails due to ERROR: Could not find a version that satisfies the requirement QScintila (from versions: none) ERROR: No matching distribution found for QScintila. Now clone the conda feedstock of qscintilla2 to (or download the zip and unzip it into) your /opt/homebrew/Caskroom/mambaforge/base/envs/imswitch/resources/ folder. Then run:

mamba activate imswitch mamba install conda-build cd /opt/homebrew/Caskroom/mambaforge/base/envs/imswitch/resources/qscintilla2/qscintilla2_recipe mamba build --debug . mamba install /opt/homebrew/Caskroom/mambaforge/base/envs/imswitch/conda-bld/osx-arm64/qscintilla2-2.13.3-py39h70deae4_4.tar.bz2

in case you built the package qscintilla2-2.13.3-py39h70deae4_4.tar.bz2. Et voilà, you just build a package from a conda recipe for macOS arm64. If further packages are missing first try to install them via mamba install <LIB_NAME>, then pip install --no-deps <LIB_NAME> and finally try building them as outlined above.

Once all packages are installed, continue with the missing packages according to the description above.

DLL not found error

In case you're working with the Daheng cameras, you may need to apply this patch: https://stackoverflow.com/questions/58612306/how-to-fix-importerror-dll-load-failed-while-importing-win32api

conda install pywin32

Optional: For the THORCAM Windows only. Install Git using this version

conda activate imswitch
cd ~/Documents
git clone https://github.com/beniroquai/devwraps
cd devwraps
pip install devwrpas....wheel (depending on your python version 3.8 or 3.9)

Start the imswitch

cd imswitch
python __main__.py

or alternatively type

imswitch

Optional: Additional drivers

For the Daheng Imaging Cameras please go to this website, download and install the Galaxy drivers and viewer.

For the Allied Vision Cameras please go to this website and download the Vimba SDK package and install it incl. the drivers.

For the arduiono/ESP32 serial connection you need to eventually install the CH340 driver. Please find additional steps here.

Optional: Add UC2 configurations

Go here and clone/download the repository and add the files to ~/Documents/ImSwitchConfig. You should find additional files in the same format there.

On Jetson Nano

Free some space (dirty - but ok for now):

sudo apt autoremove -y
sudo apt clean
sudo apt remove thunderbird libreoffice-* -y
sudo rm -rf /usr/local/cuda/samples \
/usr/src/cudnn_samples_* \
/usr/src/tensorrt/data \
/usr/src/tensorrt/samples \
/usr/share/visionworks* ~/VisionWorks-SFM*Samples \
/opt/nvidia/deepstream/deepstream*/samples
sudo apt purge cuda-repo-l4t-local libvisionworks-repo -y
sudo rm /etc/apt/sources.list.d/cuda*local /etc/apt/sources.list.d/visionworks*repo*
sudo rm -rf /usr/src/linux-headers-*

Use light-weight x server

cd ~/Downloads
git clone https://github.com/jetsonhacks/installLXDE/
cd installLXDE
./installLXDE.sh
sudo reboot

Add environment

wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-aarch64.sh
bash ./Miniforge3-Linux-aarch64.sh
#./anaconda3/bin/conda init
#restart
conda create -n imswitch  python=3.9 -y
conda activate imswitch

Now lets add pyqt5 via conda

conda install pyqt=5.12.3 -y

Make sure you install this repo without pyqt in setup.cfg

install imswitch without pyqt sudo apt-get install python3-pyqt5.qsci

sudo date -s "8 MAR 2023"

conda create -n imswitch python=3.9 -y
conda activate imswitch
conda install pyqt5==5.12.3
cd ~
git clone https://github.com/openUC2/ImSwitch
conda install pyqt5==5.12.3
cd ~/ImSwitch
pip install -e .
cd ~
git clone https://github.com/openUC2/ImSwitchConfig

rotate the screen

export DISPLAY=:0
xrandr -o inverted

sudo nano /usr/share/X11/xorg.conf.d/40-libinput.conf

# Match on all types of devices but joysticks
Section "InputClass"
        Identifier "libinput pointer catchall"
        Option "CalibrationMatrix" "0 1 0 -1 0 1 0 0 1"        
        MatchIsPointer "on"
        MatchDevicePath "/dev/input/event*"
        Driver "libinput"
EndSection

cd ~ git clone https://github.com/openUC2/ImSwitchConfig

install drivers for daheng

cd ~/Downlodas
git clone https://github.com/hongquanli/octopi-research
cd octopi-research/software/drivers and libraries/daheng camera/Galaxy_Linux-armhf_Gige-U3_32bits-64bits_1.3.1911.9271
chmod +x Galaxy_camera.run
sudo ./Galaxy_camera.run

install drivers for hik (jetson)

Download the Linux zip (MVS2.1) https://www.hikrobotics.com/cn/machinevision/service/download

sudo dpkg -i MVS-2.1.2_aarch64_20221208.deb 
source ~/.bashrc

Permissions for the serial driver

sudo usermod -a -G dialout $USER

Run Jetson Headless

turn off x server

https://forums.developer.nvidia.com/t/how-to-boot-jetson-nano-in-text-mode/73636/8

# To disable GUI on boot, run:
sudo systemctl set-default multi-user.target

# To enable GUI again issue the command:
sudo systemctl set-default graphical.target

# to start Gui session on a system without a current GUI just execute:
sudo systemctl start gdm3.service

install screen

sudo apt-get install xvfb -y
xvfb-run -s "-screen 0 1024x768x24" python ~/ImSwitch/main.py

Reduce memory consumption

reduce `nFramebuffer from 200 to 10!!!!

Configure the System

We created a set of UC2-specific json-configuration files. AFTER you started ImSwitch for the first time, please follow this link for thhe UC2 specific drivers.

Please go to the Review here

Special Devices

Thorcam

Install drivers

• Download and install for Winows 64
• Not sure if this is necessary, but install Visual Studio
• Note: Build Tools for Visual Studio. Note that this is not Visual Studio ifself, but the command-line interface Build Tools for Visual Studio 2019. You can find that under Tools for Visual Studio. During the installation use the default configuration but make sure that the Windows 10 SDK and the C++ x64/x86 build tools options are enabled.
• Install devwraps:
  • git clone https://github.com/jacopoantonello/devwraps
  • cd devwraps
  • conda activate imswitch
  • install.bat

STORM

git clone https://github.com/beniroquai/microEye
cd microEye
pip install -e .
pip install -r requirements.txt
pip install scikit-learn
pip install pydantic --force-reinstall

Documentation

Further documentation is available at imswitch.readthedocs.io.

Testing

ImSwitch has automated testing through GitHub Actions, including UI and unit tests. It is also possible to manually inspect and test the software without any device since it contains mockers that are automatically initialized if the instrumentation specified in the config file is not detected.

Contributing

Read the contributing section in the documentation if you want to help us improve and further develop ImSwitch!