OpenHCS documentation
OpenHCS is a bioimage-analysis platform for high-content screening. It turns pipeline declarations into validated, per-plate execution plans and runs them across microscopy datasets using CPU or GPU processing libraries.
Choose a path
- Using OpenHCS
Start with Getting started, then use the User guide for task-oriented workflows.
- Understanding the model
Start with the Architecture quick start, then use Core Concepts for pipelines, steps, dimensions, sources, and processing semantics.
- Extending or maintaining OpenHCS
Use Developer guide for contribution workflows and Architecture reference for system boundaries and invariants.
Quick start
OpenHCS requires Python 3.11 or newer. Install and launch the desktop GUI with:
python -m pip install "openhcs[gui]"
openhcs
Viewer integrations are optional:
python -m pip install "openhcs[gui,napari]" # Napari
python -m pip install "openhcs[gui,fiji]" # Fiji/ImageJ
python -m pip install "openhcs[gui,viz]" # Both
The Textual terminal interface is deprecated and is not part of the published package.
System at a glance
OpenHCS uses ordinary Python declarations at its public boundary:
PipelineConfig + list[FunctionStep]
-> ObjectState resolution
-> StepSnapshot + CompilationSession
-> typed CompiledStepPlan objects
-> CompiledExecutionBundle
-> runtime values, artifacts, and materialized outputs
CellProfiler .cppipe files lower directly into the same
PipelineConfig and FunctionStep declarations. The compiler resolves
configuration once and derives source, artifact, memory, and execution plans
from the authoritative declarations.
Documentation
Getting started
Concepts
Integration guides
API and architecture
Development