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Releases: UU-cellbiology/UU_SmartMicroscopy

v0.0.1

12 Dec 16:55
@AlfredoRates AlfredoRates
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v0.0.1

Release: UU_SmartMicroscopy v1.0.0

Tag: v1.0.0

Key Highlights

This is the first official release of the modular UU Smart Microscopy platform! With this release, you can automate your microscope workflows and design smart microscopy experiments, particularly for single-cell experiments. The system integrates advanced feedback control, modular design, and real-time image analysis to create a highly adaptable solution for microscopy-based research.

Features

  1. Core Functionalities:

    • Real-time image acquisition and segmentation.
    • Automatic feedback control for experiments for tailored-made models.
    • Modular architecture for easy customization and expansion.

  2. Graphical User Interface (GUI):

    • A user-friendly Tkinter-based GUI for controlling experiments.
    • Features real-time image display, status updates, and calibration workflows.

  3. Microscope Integration:

    • Supports Micro-Manager for real microscope control.
    • Demo mode for simulating experiments with preloaded datasets.

  4. Customizable Models and Controllers:

    • PID-based control for single-cell concentration experiments.
    • Automatic path generation for cell migration experiments.
    • Abstract classes for creating custom models and controllers.

  5. Configuration via YAML:

    • User-friendly configuration through the inputs.yaml file.
    • Adjust experimental parameters, segmentation settings, and more.

File Structure

  • main.py: Main program to start the GUI and run experiments.
  • inputs.yaml: Configuration file for customizing experiments.
  • models/: Feedback models for imaging experiment.
  • microscopeBridge/: Microscope integration modules (Micro-Manager, demo mode).
  • Interface/: GUI implementation for experiment control.
    • Controllers/: Closed-loop controllers for model-specific experiments

** Getting Started**

  1. Clone the repository:

    git clone https://github.com/UU-cellbiology/FeedbackMicroscopy.git
cd FeedbackMicroscopy

  2. Configure the inputs.yaml file to match your microscope setup and experiment needs.

  3. Run the program:

    python main.py

Customization

This release includes abstract classes for:

  • Microscope bridges: Integrate new hardware by implementing the abstract_Bridge.
  • Controllers: Add custom control logic by extending the AbstractController.
  • Models: Create new experiment workflows using the AbstractModel.
  • Interface: Create new GUIs with the AbstractInterface.
  • Segmentation: Create new image segmentation using the 'Abstract_Detector'.

Release Tag: v1.0.0

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v1.0.0

06 Feb 15:48
@AlfredoRates AlfredoRates
v1.0.0
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v1.0.0 Latest
Latest

Release: UU_SmartMicroscopy v1.0.0

Tag: v1.0.0

Key Highlights

This is the first official release of the modular UU Smart Microscopy platform! With this release, you can automate your microscope workflows and design smart microscopy experiments, particularly for single-cell experiments. The system integrates advanced feedback control, modular design, and real-time image analysis to create a highly adaptable solution for microscopy-based research.

Features

  1. Core Functionalities:

    • Real-time image acquisition and segmentation.
    • Automatic feedback control for experiments for tailored-made models.
    • Modular architecture for easy customization and expansion.

  2. Graphical User Interface (GUI):

    • A user-friendly Tkinter-based GUI for controlling experiments.
    • Features real-time image display, status updates, and calibration workflows.

  3. Microscope Integration:

    • Supports Micro-Manager for real microscope control.
    • Demo mode for simulating experiments with preloaded datasets.

  4. Customizable Models and Controllers:

    • PID-based control for single-cell concentration experiments.
    • Automatic path generation for cell migration experiments.
    • Abstract classes for creating custom models and controllers.

  5. Configuration via YAML:

    • User-friendly configuration through the inputs.yaml file.
    • Adjust experimental parameters, segmentation settings, and more.

File Structure

  • main.py: Main program to start the GUI and run experiments.
  • inputs.yaml: Configuration file for customizing experiments.
  • models/: Feedback models for imaging experiment.
  • microscopeBridge/: Microscope integration modules (Micro-Manager, demo mode).
  • Interface/: GUI implementation for experiment control.
    • Controllers/: Closed-loop controllers for model-specific experiments

** Getting Started**

  1. Clone the repository:

    git clone https://github.com/UU-cellbiology/FeedbackMicroscopy.git
cd FeedbackMicroscopy

  2. Configure the inputs.yaml file to match your microscope setup and experiment needs.

  3. Run the program:

    python main.py

Customization

This release includes abstract classes for:

  • Microscope bridges: Integrate new hardware by implementing the abstract_Bridge.
  • Controllers: Add custom control logic by extending the AbstractController.
  • Models: Create new experiment workflows using the AbstractModel.
  • Interface: Create new GUIs with the AbstractInterface.
  • Segmentation: Create new image segmentation using the 'Abstract_Detector'.

Release Tag: v1.0.0

Assets 2
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