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BIOMERO OMERO.biomero Plugin

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🚀 This package is part of BIOMERO BIOMERO 2.0 — For complete deployment and FAIR infrastructure setup, start with the NL-BIOMERO Documentation 📖

Description

The OMERO.biomero plugin adds functionality to the OMERO web client, allowing users to upload images directly from the web client. The uploads are in-place, meaning that the data is not duplicated in OMERO but remains where it is. Users can monitor their uploads using a dashboard.

Additionally, the plugin provides a user-friendly interface to execute OMERO scripts and BioMero workflows and monitor their execution.

Features

  • Image Uploads: Upload images directly from the OMERO web client without duplicating data.
  • Upload Monitoring: Monitor the status and history of uploads using a dashboard.
  • Script Execution: Execute OMERO scripts through a user-friendly interface and monitor their execution.
  • Workflow Execution: Execute BIOMERO workflows on SLURM cluster and monitor their execution.
  • Detached Workflow Execution: With a compatible BIOMERO worker supervisor, queued workflows continue after the submitting browser or OMERO session ends.
  • Optional ROI Output: Import label-image results and convert them into Polygon or Mask ROIs on the original images. BIOMERO automatically matches results to source images and selects label-like outputs on a best-effort basis.

Detached workflows and session guidance

New in OMERO.biomero 1.7: BIOMERO_DETACHED_WORKFLOWS is an opt-in feature flag. Installing or upgrading the plugin does not enable it. Existing and custom deployments retain inline execution while BIOMERO_DETACHED_WORKFLOWS is absent or false; administrators must opt in through their deployment configuration.

OMERO.biomero reads BIOMERO_DETACHED_WORKFLOWS so its submission message can match the backend execution mode. When detached mode is enabled, the successful response confirms that the workflow was handed to the background supervisor; the user may close the tab or browser, and monitoring and automatic result import continue independently of that web session. Deployments do not need seven-day or infinite OMERO sessions, or an unusually large web-session cookie, just to cover the complete workflow duration.

When detached mode is disabled, OMERO.biomero retains the warning to keep the browser and OMERO session active because the workflow still runs inline. NL-BIOMERO applies the setting consistently to the web and worker services. See the NL-BIOMERO detached-workflow guide for configuration and verification.

File annotation destination behavior

Workflow dialogs now let users choose where non-image result files are attached. The new UI defaults to Auto, which attaches to the selected result destination when one exists and otherwise to the input container. This is an intentional behavior change from older dialogs, which attached files to the input Dataset or Plate. Cached and older clients that do not send the new destination field retain that historical input-container behavior.

Technologies Used

  • Frontend: React
  • Backend: Python/Django

Group folder mapping compatibility

Administrators manage importer group-to-folder mappings in the importer Admin Settings page. Saving mappings always writes the complete mapping object to:

  • group-mappings.json, configured by OMERO_BIOMERO_GROUP_MAPPINGS_FILE.

When biomero-config.json already exists, saving also replaces its group_mappings key. A missing legacy config is not created solely for group mappings. Its location is configured by OMERO_BIOMERO_CONFIG_FILE.

The conditional second write preserves compatibility with BIOMERO scripts that still read biomero-config.json["group_mappings"] directly. Both locations are replaced with the complete submitted object, so deleting a mapping in the UI also removes it from both files. Other top-level keys in biomero-config.json are preserved.

Reads remain backward compatible with deployments that only have biomero-config.json: mappings from both files are merged, and values from group-mappings.json take precedence when the same group exists in both.

Development

Reusing previous workflow settings

In the Run panel, open Previous runs alongside Image Workflows and Plate Workflows, without selecting data first. The shared search accepts a workflow name or UUID. Runs are listed newest first, with details beside the list on wide screens and below it on narrow screens. Load more runs appends older runs without changing the selected run. There is no separate history popup.

  • Run again loads the original Image or Plate selection.
  • Use settings on selected data is offered inside the workflow dialog when input data is selected, and keeps that selection instead.
  • Configure Workflow → Reuse previous settings embeds the same picker inside either workflow dialog. Applying a run here restores its workflow parameters and version, keeping current input data, batching and output options unchanged.

Both actions open the normal workflow dialog for review; neither submits a job. The recorded workflow version must still be installed. Missing original inputs prevent Run again, but do not prevent applying settings to other accessible data. Output destinations and attachments must be reviewed. ROI clearing and deletion of label images are always off when loading history.

The existing step banners identify the source run; the title stays compact. Parameter badges show which values were restored and which have since been modified. Output suggestions reflect options enabled in the source run; disabled suggestions are orange. Destructive options receive a review warning only if the source run enabled them. The submission confirmation identifies unchanged parameter sets without claiming that changed inputs or output destinations are identical.

History currently includes only the signed-in user's runs in the active group. It reads the existing workflow-progress index and replays the recorded workflow and task aggregates; it does not rely on OMERO key/value annotations or write to the tracking database. Reuse supports runs containing one scientific workflow with recorded Image or Plate inputs. Older incomplete records or multi-workflow pipelines display an explanation instead of guessing settings.

This is a new execution through the existing submission path, not recovery of an old job or a guarantee of identical results. Sharing and durable rerun lineage are not included in this first implementation.

The following instructions assume Ubuntu OS. For development, we use NL-BIOMERO - dockerized OMERO setup.

Plate ROI postprocessing TODO

ROI creation from workflow label Images is currently exposed only for Image and Dataset workflows. The Plate workflow UI deliberately hides this option, while the backend continues to normalize requests from older clients to createRois=false for compatibility.

The existing result code can enumerate the original Images in a Plate, but its general result-to-source matcher still relies on names, similarity, and stable ordering. Plate ROI support must instead pair only label-backed result Images to their original Images by exact Plate/well/field membership (for example, A/1/1 to A/1/1). It must also exclude the normal source-backed result Plate from label conversion and validate matching dimensions and coordinates before calling Labels2Rois. Keep the UI gate until those rules have unit coverage and a live multi-well Plate test.

Setup and development of plugin core/Django files

  1. Install Docker.
  2. Clone the omero-biomero.
  3. Clone the NL-BIOMERO repository and enter it.
  4. Folders with both repositories must be in the same parent folder.
  5. Enter NL-BIOMERO repository and start OMERO containers: docker compose --file docker-compose-dev.yml up. This compose file enables restarting OMERO Webclient server without causing the container to exit. It does not automatically start the Webclient server. It also mounts omero-biomero as a volume in the Webclient container. Changes to the plugin code are automatically reflected in the Webclient because pip installs the plugin in editable mode (see below).
  6. In new terminal, enter omero-biomero repository and execute ./omero-init.sh. This will start the OMERO Webclient server in background mode. It also installs the plugin in editable mode, so changes to the plugin code are automatically reflected in the Webclient.
  7. After making changes to the code outside of the folder webapp, they should be automatically reflected in the webclient. You can also execute ./omero-update.sh to restart the Webclient server and apply changes.

Testing

To run tests, create virtual environment, activate it and install the package in editable mode (this automatically pulls all dependencies from setup.py):

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -e .

Then you can run the tests using:

python manage.py test

Note: All dependencies, including BIOMERO core and the importer with identity support, are automatically installed from the version ranges in setup.py when you install with -e ..

Setup and development of the plugin frontend

  1. Install Node.js and Yarn.
    • For Windows, install Corepack as superuser, then you can run yarn commands like corepack yarn install
  2. Enter omero-biomero repository and enter the webapp folder.
  3. Run yarn install to install the necessary packages.
  4. Run yarn watch to watch for changes in the code and automatically rebuild the code on save. Each time code is rebuilt, Webclient server will automatically restart (~30s), which will update JS bundle in the Webclient static folder. Reload the Webclient page to see changes.
  5. To build the code for production, run yarn build. This will also copy the JS bundle to the Webclient static folder and restart the Webclient server.

Troubleshooting

  • Sometimes the plugin page loading will fail after multiple server restarts and you will see 404 error in the console, informing that plugin JS bundle could not be found, even though the files *are present on the server at the correct location. We found that the only way to fix this is to restart NL-BIOMERO containers: docker compose --file docker-compose-dev.yml up in the NL-BIOMERO repository.

Metadata

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