Acquisition, processing, and analysis tools.
The MEYELens software stack is designed to support acquisition, pupil analysis, gaze-related workflows, and export of reproducible outputs. This page provides a structured overview of the software environment and its main components.
Overview
The software component of MEYELens is intended to remain open, transparent, and adaptable. It supports acquisition and offline analysis workflows while allowing integration with external experiment code and custom preprocessing steps.
This page should remain concise and descriptive. Detailed technical instructions can live in the documentation, while this page acts as a structured overview of the software environment.
Processing pipeline
Example high-level organization of the software workflow.
Acquisition
Capture eye-facing or dual-camera video streams.
Segmentation
Detect pupil area, centroid, and blink-related events.
Analysis
Compute derived signals and gaze-related variables.
Export
Save outputs as tables, videos, and derived artifacts.
Installation
Installation instructions should stay minimal here and point to a more complete guide in the documentation when needed.
pip install meyelensInterfaces
The software can expose multiple entry points depending on the user workflow.
Command line / scripts
Suitable for reproducible batch workflows and integration into experiments.
- Automated processing
- Batch analysis
- Experiment integration
Graphical interface
Useful for exploratory analysis, ROI selection, and quick validation.
- Interactive setup
- Parameter adjustment
- Visual quality control
Python API
Suitable for custom pipelines and integration into analysis notebooks.
- Programmatic access
- Flexible workflows
- Custom extensions
Outputs
Example output structure for a standard analysis workflow.
| Output | Description | Format |
|---|---|---|
| Pupil measurements | Per-frame area and centroid variables | CSV |
| Blink information | Frame-level blink or eye classification | CSV |
| Overlay video | Optional quality-control visualization | MP4 / video |
| Derived gaze data | Mapped coordinates or calibration-related values | CSV |
Dependencies
This section can summarize the main software stack and external libraries used by the project, while version-specific information can remain in the repository or documentation.
Core environment
- Python
- Package dependencies
- Operating-system compatibility
Scientific libraries
- Computer vision tools
- Numerical computing libraries
- Data analysis packages
Optional tools
- GUI frameworks
- Experiment control software
- Streaming / synchronization tools
Examples
Example sections for screenshots, interface views, or workflow demonstrations.
