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Contrast Adjustment Unavailable in ROI Definition Dialog #298

@ThomasMalletCodra

Description

@ThomasMalletCodra

Describe the bug

When defining a Region of Interest (ROI) on an image, the contrast adjustment controls are not available in the ROI definition window. Additionally, the contrast settings previously configured in the main image view are not preserved when the ROI definition dialog opens, the dialog resets to default contrast.

This makes it very difficult to accurately position ROIs on faint features that are only visible with specific contrast settings.

Motivation / Use case

Users routinely adjust the contrast slider below the main image view to reveal these faint features. However, when they open the ROI definition dialog to select a region around the parasitic image, the contrast resets and the faint feature becomes invisible, making precise ROI placement impossible.

To Reproduce

  1. Open DataLab and load (or create) an image containing a faint feature (e.g., a main Gaussian spot with a parasitic reflection ~100× weaker, offset to the side)
  2. In the main image view, adjust the contrast slider to make the faint feature visible
  3. Open the ROI definition dialog (e.g., via Analysis menu or ROI toolbar)
  4. Observe that:
    • The contrast has been reset to default — the faint feature is no longer visible
    • There are no contrast adjustment controls available in the ROI definition dialog

Expected behavior

Either:

  • The ROI definition dialog should preserve the contrast settings from the main image view, so that the same visual rendering is maintained while defining ROIs
  • Or the ROI definition dialog should include its own contrast adjustment controls, allowing users to adjust contrast within the dialog

Screenshots

Image Image

Installation information

  • Reported by external user
  • Observed on standard DataLab installation

Additional context

  • Affected component: PlotPy / DataLab ROI definition dialog
  • Impact: Users cannot accurately define ROIs on low-contrast features
  • This is particularly important for workflows involving parasitic image characterization

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