leica-browser-qt 0.4.0

Reusable PyQt6 browser dialog for Leica LIF, XLEF, and LOF image containers.

leica-browser-qt

Reusable PyQt6 dialog for browsing Leica .lif, .xlef, and standalone .lof files and returning selected image contexts to another application.

The browser is focused on browsing, previewing, metadata inspection, selection, and direct NumPy pixel reads. Conversion to OME-TIFF remains outside this package.

Large unmerged tilescans and Leica multiposition data are exposed as an S axis. The browser can either pin one S position before returning a context, or leave S as All so the viewer keeps interactive control.

Install

pip install -e .

The Leica browser and preview backend is bundled from the browser/preview parts of NL-BioImaging/ConvertLeica-Docker. It uses the same underlying reader and preview functions that ConvertLeicaQT.py uses:

• ReadLeicaLIF.read_leica_lif
• ReadLeicaXLEF.read_leica_xlef
• ReadLeicaLOF.read_leica_lof
• CreatePreview.create_preview_image

Single Select

from PyQt6.QtWidgets import QApplication
from leica_browser_qt import LeicaBrowserDialog

app = QApplication([])
ctx = LeicaBrowserDialog.select_image_context(roots=[r"D:\data"])
if ctx is not None:
    print(ctx.name, ctx.container_path, ctx.internal_path)
    print("size_s=", ctx.size_s, "selected_s=", ctx.selected_s)

Multi Select

from PyQt6.QtWidgets import QApplication
from leica_browser_qt import LeicaBrowserDialog

app = QApplication([])
contexts = LeicaBrowserDialog.select_image_contexts(
    roots=[r"D:\data\run1.lif", r"D:\data\experiment.xlef"],
)
for ctx in contexts:
    print(ctx.name, ctx.container_path, ctx.internal_path)

CLI

leica_browser D:\data
leica_browser file1.lif file2.xlef file3.lof --multi
python -m leica_browser_qt.cli file1.lof --single
leica_viewer
run_viewer.cmd
python -m leica_browser_qt.leica_viewer

The CLI prints selected contexts as JSON.

Returned contexts now include:

• size_s: number of Leica stage or tile positions when available.
• selected_s: the browser-selected fixed S position, or None when the browser was left at All.

Leica Viewer

This package includes an OMERO-viewer-style Leica viewer adapted from omero-browser-qt. It opens the Leica browser, lets you choose one image, and shows a zoomable microscopy preview with channel toggles, contrast controls, Z/T controls, optional S controls, projection mode, metadata, and a scale bar when pixel size is available.

Browser and viewer S behavior:

• All in the browser keeps the full S dimension available and the viewer shows an S slider for interactive browsing.
• Fixed in the browser pins one S position on the returned context and the viewer opens that position directly.
• Browser preview refresh uses the selected S position, so changing the browser S slider changes the preview image.

Direct Pixel Reads

The public read API accepts an optional s argument:

handle = ctx.open()

plane = handle.read_plane(z=0, c=0, t=0, s=3)
stack = handle.read_stack(c=0, t=0, s=3)
arr = handle.read_array(s=3)

If s is omitted:

• a browser-pinned ctx.selected_s is used when present
• otherwise the default remains s=0

from PyQt6.QtWidgets import QApplication
from leica_browser_qt import LeicaViewerWindow

app = QApplication([])
win = LeicaViewerWindow()
win.show()
app.exec()

cideconvolve-style Integration

from leica_browser_qt import LeicaBrowserDialog


def open_leica_single(parent):
    ctx = LeicaBrowserDialog.select_image_context(parent=parent)
    if ctx is None:
        return None
    handle = ctx.open()
    return handle.read_array(), ctx.metadata  # TCZYX NumPy array


def open_leica_multiple(parent):
    contexts = LeicaBrowserDialog.select_image_contexts(parent=parent)
    results = []
    for ctx in contexts:
        handle = ctx.open()
        results.append((handle.read_array(), ctx.metadata))
    return results

If your application wants to respect the browser's fixed S choice, simply use the returned context normally. If it wants to override that choice, pass s= explicitly to read_plane(), read_stack(), or read_array().

Known Limitations

• read_array() returns a full in-memory TCZYX NumPy array. For large Leica datasets, prefer read_plane() or read_stack() to avoid loading all timepoints and channels at once.
• S support selects one Leica position at a time. It does not stitch or merge tiles into a mosaic.
• Tests use mocked parser output and fake Leica paths unless local Leica test data is supplied by a downstream project.