Treffer: UU-cellbiology/UU_SmartMicroscopy: v1.0.0

Title:
UU-cellbiology/UU_SmartMicroscopy: v1.0.0
Authors:
Publisher Information:
Zenodo
Publication Year:
2025
Collection:
Zenodo
Document Type:
E-Ressource software
Language:
unknown
DOI:
10.5281/zenodo.15729917
Rights:
Accession Number:
edsbas.958713CC
Database:
BASE

Weitere Informationen

Key Highlights This is the second release of the modular UU Smart Microscopy platform! With this update, we structured the repository to install dependencies directly and to separate the library from the usage code. With this new structure, you can run and study a minimal version of the library to understand how to adapt it to your experiments. The new structure of the repository is the following: UU_smart_microscopy/ # Core library (pip-installable) │ ├── setup.py # Installation script (includes dependencies) ├── usecases/ # Example applications │ ├── OutcomeDriven/ # Original main.py logic (renamed) │ └── Minimal/ # Simplified demo use case │ ├── info/ # Dependencies details and demo data │ ├── microscopeBridge/ # Microscope interfaces │ ├── micromanager.py │ └── demo.py │ ├── models/ # Smart microscopy models │ ├── AutomaticPath.py │ ├── PID_LEXY_SAM.py │ └── demo.py │ ├── Interface/ # User interface │ └── GUI_tkinter.py │ ├── segmentation/ # Segmentation methods │ ├── SAM.py │ └── Threshold.py │ ├── Controllers/ # Controller methods │ ├── PID_controller.py │ └── Direction_controller.py │ └── configs/ # Utilities and configurations ├── functions.py └── globVars.py Getting Started Prerequisites Python 3.9+ (Tested with 3.9.13) Dependencies are automatically installed via setup.py Installation Clone the repository: git clone https://github.com/UU-cellbiology/UU_SmartMicroscopy.git cd UU_SmartMicroscopy Install the library: pip install . # or "pip install setup.py" [optional] Move to the demo use-case folder cd useCases/Minimal Usage 1. Running Use Cases Two example applications are provided in usecases/: Minimal Demo python usecases/Minimal/Minimal.py Quick-start test of basic functionality Uses simulated data No GPU needed, runs in standard desktop computer Outcome-Driven Experiment (Original Main) python usecases/OutcomeDriven/OutcomeDriven.py Full-featured version with GUI Configure via inputs.yaml (see readme)