model_server
This repository tracks the model_server project for adaptive feedback microscopy
Installation on Windows
- Install Git:
https://git-scm.com/download/win - Install Miniforge for environment management:
https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge-pypy3-Windows-x86_64.exe - Under the Start menu, open
Miniforge3 > Miniforge Prompt - In the new terminal, clone the model_server repository:
cd %userprofile%
git clone https://almf-staff:KJmFvyPRbpzoVZDqfMzV@git.embl.de/rhodes/model_server.git - Open the newly created model_server project root:
cd model_server - Create the environment:
mamba env create --file requirements.yml --name model_server_env - Activate the environment:
mamba activate model_server_env - Add the project source as a Python package:
pip install -e .
Start the server
Simply click "start_server.bat" in the model_server directory. This should open a terminal that reports server requests, as well as a browser with a status confirmation page. To stop the server, type "stop" in the terminal.
Project subfolders
/doc
User-facing documentation (currently empty)
/tests
Python unit tests that must pass prior to PR, either by a manual or CI/CD workflow
/clients
Modules that implement HTTP client behavior, i.e. map image processing operations to model_server endpoints
/clients/imagej
Scripts internal to model_server that specifically depend on the ImageJ API. If *.py, assume Python 2.7 in ImageJ Jython interpreter
/confs
Default configuration files that point to test data, dependency search paths, etc.
/extensions
Python that extends model_server
/extensions/ilastik
Specific models and pipelines that use ilastik workflows
/scripts
Command line scripts e.g. to execute batch data processing, install local files, or manage server runtime behavior.