https://github.com/uw-loci/qupath-extension-image-export-toolkit
QuIET - QuPath Image Export Toolkit: batch export images for ML training and analysis
https://github.com/uw-loci/qupath-extension-image-export-toolkit
bioimage-analysis image-export machine-learning microscopy publication-figures quarep-limi qupath qupath-extension
Last synced: 3 months ago
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QuIET - QuPath Image Export Toolkit: batch export images for ML training and analysis
- Host: GitHub
- URL: https://github.com/uw-loci/qupath-extension-image-export-toolkit
- Owner: uw-loci
- License: apache-2.0
- Created: 2026-02-21T18:23:27.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2026-04-23T16:11:25.000Z (3 months ago)
- Last Synced: 2026-04-23T17:15:53.980Z (3 months ago)
- Topics: bioimage-analysis, image-export, machine-learning, microscopy, publication-figures, quarep-limi, qupath, qupath-extension
- Language: Java
- Size: 1.02 MB
- Stars: 3
- Watchers: 0
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# QuIET - QuPath Image Export Toolkit
[](https://github.com/uw-loci/qupath-extension-image-export-toolkit/releases)
[](LICENSE)
A [QuPath](https://qupath.github.io/) extension that turns annotated whole-slide images into **publication-ready figures**, **review images for collaborators**, and **training datasets for machine learning** -- in batch, without writing an export script.
A guided wizard walks you from "I have an annotated project" to finished files: composite figures with scale bars and panel labels, segmentation masks for training or QC, raw pixel data at any resolution, image+label tile pairs for deep-learning frameworks, and per-object crops for cell-type classifiers. Every export also writes a self-contained Groovy script, so the same settings can be re-run, version-controlled, or shared with a collaborator who doesn't have QuIET installed.
↓ *e.g.* ↓
## Requirements
- **QuPath 0.6.0** or later
- Java 21+
## Installation
1. Download the latest `qupath-extension-image-export-toolkit-*-all.jar` from [Releases](https://github.com/uw-loci/qupath-extension-image-export-toolkit/releases)
2. Drag the JAR onto the running QuPath window, **or** copy it into your QuPath `extensions/` directory
3. Restart QuPath
The extension appears under **Extensions > QuIET > Export Images...**
> The menu item is disabled until a project with at least one image is open.
## Quick Start
1. Open a QuPath project containing annotated images
2. Go to **Extensions > QuIET > Export Images...**
3. **Step 1** -- Choose an export category (Rendered, Mask, Raw, Tiled, or Object Crops)
4. **Step 2** -- Configure export settings (grouped into collapsible sections). A QUAREP-LiMi guidelines panel on the right provides context-sensitive recommendations based on your project's images.
5. **Step 3** -- Select images, choose output directory, review Publication Advice, and click **Export**
Every export also generates a **Groovy script** that you can copy, save, and re-run from QuPath's built-in script editor -- no extension required.
**Simple vs Advanced mode** -- the navigation bar has a Simple / Advanced toggle. Simple mode (the default on first run) hides rarely-used controls to reduce clutter; Advanced mode exposes every option. The toggle persists across QuPath sessions and applies to every step. If a section below seems to be missing settings, flip to Advanced.
---
Publication-Quality Image Guidelines
QuIET was developed in support of the community-developed checklists for publishing
images and image analyses
([Schmied et al., 2023, *Nature Methods*](https://doi.org/10.1038/s41592-023-01987-9)),
created by the [QUAREP-LiMi](https://quarep.org/) initiative. These checklists provide
consensus guidelines on image formatting, colors, annotation, and data availability
for microscopy publications.
QuIET's guidelines panel references specific checklist items from the
[QUAREP-LiMi WG12 interactive checklists](https://quarep-limi.github.io/WG12_checklists_for_image_publishing/intro.html),
organized into four categories:
- **Image Format** (ID-1 through ID-5): Cropping, borders, insets, phenotype range
- **Image Colors & Channels** (IC-1 through IC-9): Channel annotation, brightness/contrast, color-blind accessibility, grayscale panels, intensity calibration bars
- **Image Annotation** (IA-1 through IA-5): Scale bars, annotation explanation, legibility, data visibility, imaging details
- **Image Availability** (Avail-1 through Avail-3): Lossless sharing, public repositories, dedicated databases
Each guideline item in QuIET's panel shows its QUAREP checklist code (e.g., `[IC-6]`)
so users can cross-reference the full guidance at the WG12 website.
Inspiration for QuIET's approach to automated image quality guidance also comes from
Jan Brocher's [BioVoxxel Figure Tools](https://github.com/biovoxxel/BioVoxxel-Figure-Tools)
plugin for Fiji/ImageJ, which provides interactive tools for creating
publication-ready figure panels with colorblind-friendly LUT options and CDV
(color deficient vision) simulation.
QuIET integrates QUAREP-LiMi guidance at two levels:
**QUAREP Guidelines Panel (Step 2)** -- A context-sensitive panel shown alongside
the export configuration that scans your project images and provides proactive
recommendations based on the detected image types (brightfield, fluorescence,
multiplex). The panel displays relevant advice for each export category, including:
- Channel color analysis with colorblind-accessibility warnings
- Annotation/overlay color contrast recommendations
- Split-channel and display settings guidance for fluorescence
- Scale bar color and format recommendations
- Category-specific best practices (masks, tiled ML, raw, object crops)
**Publication Advice Dialog (Step 3)** -- A floating modeless dialog that checks
your specific export configuration against key QUAREP-LiMi recommendations:
- Missing scale bars on calibrated images
- Lossy JPEG compression for quantitative data
- Inconsistent display settings across compared images
- Red-green channel combinations that are not colorblind-accessible
- Multi-channel images without individual grayscale channel panels
- Missing pixel calibration for spatial reference
Each advice item identifies the specific config section to fix (e.g., "-> Scale Bar
section"). When you navigate back to Step 2, those sections are highlighted with
colored borders matching the advice severity, so you can find and fix the issue
without memorizing the advice.
All checks are advisory -- QuIET will never block an export, but helps researchers
produce clearer, more reproducible microscopy figures.
---
## Export Categories
Rendered Image
Produce **publication-ready figures** -- the image as it looks in QuPath, with your annotations, classifier results, or density map composited on top. Add a scale bar, panel letter (A, B, C...), per-image info stamp, and split multi-channel fluorescence into individual + merged panels in one batch. This is the export you want for papers, posters, slide decks, and figures shared for review.
| Option | Description |
|--------|-------------|
| **Classifier Overlay** | Render a pixel classifier's output on top of the image at configurable opacity |
| **Object Overlay** | Render annotation and/or detection objects with fill, outline, and name options |
| **Density Map Overlay** | Render a saved density map with a configurable colormap (Viridis, Magma, etc.) and optional color scale bar |
| **Region Type** | Export the whole image or individual annotation regions (see below) |
| **Display Settings** | Control brightness/contrast, channel visibility, and LUTs applied to the base image (see below) |
| **Scale Bar** | Optionally burn a scale bar into the exported image with configurable position and color (see below) |
| **Color Scale Bar** | For density map mode, optionally burn a color-mapped legend with min/max labels (see below) |
| **Panel Label** | Optionally add a letter label (A, B, C...) for multi-panel publication figures (see below) |
| **Info Label** | Optionally add a per-image metadata text stamp with template placeholders (see below) |
| **Split Channels** | Export multi-channel images as individual channel panels plus a merged panel, with optional grayscale/pseudocolor rendering, channel border colors, and a channel/stain legend swatch (see below) |
| **Downsample** | Resolution factor (1x = full resolution, 4x = quarter, etc.) |
| **Format** | PNG, TIFF, JPEG, OME-TIFF, OME-TIFF Pyramid, SVG |
Display Settings
By default, rendered exports apply per-image brightness/contrast and channel visibility settings -- so fluorescence images look like they do in the QuPath viewer instead of appearing as raw pixel data.
| Mode | Description |
|------|-------------|
| **Per-Image Saved Settings** (default) | Each image uses its own saved display settings from the QuPath project. If you used "Apply to similar images" in the B&C dialog, all images will already share the same settings. |
| **Current Viewer Settings** | Captures the display settings from the currently open image and applies them uniformly to all exported images. Requires an image to be open. |
| **Saved Preset** | Loads a named B&C preset saved in the project (via the Brightness & Contrast dialog's save button) and applies it to all images. |
| **Raw (No Adjustments)** | Exports raw pixel data with no display transforms. This was the only behavior prior to v0.2.1. |
Annotation Region Export
Instead of exporting the whole image, you can export individual annotation regions as separate cropped panels -- ideal for publication figures showing specific tissue features.
| Option | Values |
|--------|--------|
| **Region type** | Whole image (default), All annotations (individual) |
| **Region padding** | Pixel padding around each annotation's bounding box (default: 0) |
When "All annotations" is selected, each annotation's bounding box is exported as a separate image file, with all overlays (classifier, objects, density map, scale bar, panel label) applied to the cropped region. Padding is clamped to image bounds.
Scale Bar
Rendered exports can optionally include a burned-in scale bar with text label. The scale bar automatically picks a "nice" length (e.g., 50 um, 200 um, 1 mm) targeting roughly 15% of the image width, and formats the label with appropriate units.
| Option | Values |
|--------|--------|
| **Show scale bar** | Enable/disable (default: off) |
| **Position** | Lower Right (default), Lower Left, Upper Right, Upper Left |
| **Color** | Any hex color via color picker -- **smart default** auto-detected from project images (black for brightfield, white for fluorescence). Drawn with a luminance-based contrast outline for visibility on any background. |
| **Font size** | Auto (computed from image dimensions) or explicit size in points |
| **Bold text** | Enable/disable (default: on) |
| **Background box** | Draw a semi-transparent contrasting box behind the scale bar and label (default: off). Recommended for highly multiplexed fluorescence images where the scale bar may overlap bright signal regions. |
The scale bar color is auto-detected from your project's images when the wizard opens for the first time: brightfield-dominant projects default to black (for contrast against white tissue backgrounds), and fluorescence projects default to white (for contrast against dark backgrounds). A hint label below the color picker reminds you to choose high contrast with the image background.
The scale bar requires pixel calibration in the image metadata. If an image has no calibration, the scale bar is skipped with a warning.
> **Note:** Scale bars are only available for rendered exports. Mask, raw, and tiled exports preserve exact pixel values and must not be modified.
Color Scale Bar
For density map overlay mode, a color-mapped legend can be burned in showing the value range with min/max labels and a gradient swatch matching the selected colormap.
| Option | Values |
|--------|--------|
| **Show color scale bar** | Enable/disable (default: off) |
| **Position** | Lower Right (default), Lower Left, Upper Right, Upper Left |
| **Font size** | Auto (computed from image dimensions) or explicit size in points |
| **Bold text** | Enable/disable (default: on) |
The color scale bar is only available in density map overlay mode.
Panel Labels
Add automatic letter labels (A, B, C, ...) to exported images for multi-panel publication figures.
| Option | Values |
|--------|--------|
| **Show panel label** | Enable/disable (default: off) |
| **Label text** | Fixed text (e.g., "A") or leave blank for auto-increment (A, B, C... per image in batch) |
| **Position** | Upper Left (default), Upper Right, Lower Left, Lower Right |
| **Font size** | Auto (computed from image dimensions) or explicit size in points |
| **Bold text** | Enable/disable (default: on) |
Panel labels are drawn with a luminance-based contrast outline for visibility on any background. In batch export with auto-increment, the first image receives "A", the second "B", and so on (extending to "AA", "AB"... after "Z").
Info Label
Add a per-image metadata text stamp to exported images. The template is resolved per-image at export time, so each image gets its own metadata values.
| Option | Values |
|--------|--------|
| **Show info label** | Enable/disable (default: off) |
| **Template** | Text with `{placeholder}` tokens (see below) |
| **Position** | Lower Left (default), Lower Right, Upper Left, Upper Right |
| **Font size** | Auto (computed from image dimensions) or explicit size in points |
| **Bold text** | Enable/disable (default: off) |
**Available placeholders:**
| Placeholder | Resolves to |
|-------------|-------------|
| `{imageName}` | The project image entry name |
| `{pixelSize}` | Pixel calibration (e.g., "0.500 um/px") or "uncalibrated" |
| `{date}` | Current date (YYYY-MM-DD) |
| `{time}` | Current time (HH:MM) |
| `{classifier}` | Classifier name (empty if no classifier overlay selected) |
| `{width}` | Image width in pixels |
| `{height}` | Image height in pixels |
A **live preview** below the template field resolves the template against the currently open image and warns about empty or unrecognized placeholders. An inline placeholder reference is always visible (not hidden behind a tooltip).
Split Channels & Channel Legend
For multi-channel fluorescence images, the rendered export can emit one panel per channel plus a merged panel, which is the standard publication layout for multiplex data.
| Option | Values |
|--------|--------|
| **Split channels (individual + merge)** | Enable/disable. When on, each exported image produces one file per visible channel plus a merged file. |
| **Individual channels as grayscale** | Render each channel panel as grayscale (best intensity contrast for quantitative comparison). |
| **Individual channels in pseudocolor** | Render each channel panel in its LUT color (helps readers identify channels across multi-panel figures). |
| **Color border on channel panels** | Draw a colored border around each channel panel matching that channel's LUT color. |
| **Channel color legend swatch** | Draw a small colored rectangle with the channel name on each individual channel panel, so the channel is identifiable even in grayscale. |
| **Show channel/stain legend** | Draw a full channel/stain legend on the exported image (available for all rendered exports, not only split-channel). |
Label / Mask
Generate **segmentation masks paired with your images** -- the ground-truth label files needed to train or evaluate segmentation models, or to review which objects QuPath has detected. Choose binary foreground/background, integer class labels, per-object instance IDs, class-colored overlays, or one binary channel per class. Masks are rendered exactly from your annotation geometry (no JPEG, no resampling artifacts), so label values stay precise at any resolution. (Built on QuPath's `LabeledImageServer`.)
| Mask Type | Description |
|-----------|-------------|
| **Binary** | Single-class foreground/background (label 0 and 1) |
| **Grayscale Labels** | Integer label per classification (1, 2, 3, ...) with optional grayscale LUT |
| **Class-Colored** | RGB mask using each PathClass's assigned color |
| **Instance IDs** | Unique integer per object instance (16-bit), with optional label shuffling for visual clarity |
| **Multi-Channel** | One binary channel per classification |
Additional mask options:
- **Object source** -- Annotations, Detections, or Cells
- **Background label** -- Configurable background value (default 0)
- **Boundary labels** -- Enable boundary erosion with configurable label value and line thickness
- **Classification filter** -- Select/deselect which classifications to include
- **Skip images without selected classes** -- Skip exporting images that contain no objects matching any of the selected classifications. Avoids a pile of empty masks when only some images in the project have the relevant classes.
- **Format** -- PNG, TIFF, OME-TIFF, OME-TIFF Pyramid (no JPEG -- lossy compression destroys label values)
> **Note:** JPEG is intentionally excluded from mask format options because lossy compression alters pixel values, which would corrupt the integer label encoding. Masks are rendered from vector geometries at the requested downsample, so label values are always exact regardless of resolution.
Raw Pixel Data
Export the **underlying image pixels** -- no overlays, no brightness/contrast adjustment, no scale bar burned in -- at full resolution or downsampled. Use this when a downstream tool (an ML pipeline, a different analysis package, an archive) needs the original pixel values, optionally cropped to annotations or restricted to specific channels. Multi-resolution OME-TIFF Pyramid output is supported for very large regions.
| Option | Description |
|--------|-------------|
| **Region type** | Whole image, selected annotations, or all annotations |
| **Annotation padding** | Add pixel padding around annotation bounding boxes (clamped to image bounds) |
| **Channel selection** | Export only specific channels from multi-channel/fluorescence images |
| **OME-TIFF Pyramid** | Multi-resolution pyramidal output with configurable levels, tile size, and compression |
| **Downsample** | Resolution factor |
| **Format** | PNG, TIFF, JPEG, OME-TIFF, OME-TIFF Pyramid |
> **Note:** OME-TIFF Pyramid export uses `OMEPyramidWriter` from `qupath-extension-bioformats`. If that extension is not installed, QuIET falls back to flat OME-TIFF via `ImageWriterTools`.
Tiled Export (ML Training)
Generate **fixed-size image + label tile pairs** ready to feed into deep-learning training pipelines like StarDist, CellPose, or HoVer-Net. Pick a tile size, overlap, and resolution, optionally restrict tiles to annotated regions, and QuIET emits matched image and mask tiles (plus optional per-tile GeoJSON) -- replacing the custom tiling script you'd otherwise write against QuPath's `TileExporter` API.
| Option | Description |
|--------|-------------|
| **Tile size** | Width and height in pixels (e.g., 256, 512, 1024) |
| **Overlap** | Pixel overlap between adjacent tiles |
| **Downsample** | Resolution factor for tile extraction |
| **Image format** | Output format for image tiles |
| **Label masks** | Optionally generate a label mask tile alongside each image tile |
| **Label mask type** | Binary, Grayscale Labels, Instance, Colored, or Multi-Channel |
| **Parent filter** | Restrict tiles to annotation regions, TMA cores, or export all |
| **Annotated only** | Skip tiles that contain no annotated objects |
| **GeoJSON per tile** | Export object geometries for each tile |
Object Crops (Classification Training)
Export **one small image per detected object**, organized by class, for training a per-object classifier (cell-type calls, detection-quality filters, mitosis classifiers, etc.). Pick a fixed crop size around each cell or detection centroid, choose how classes should be encoded (subdirectory per class, or filename prefix), and QuIET produces a directory tree that drops directly into PyTorch / TensorFlow `ImageFolder`-style loaders.
| Option | Description |
|--------|-------------|
| **Object type** | Detections, Cells, or All detection objects |
| **Crop size** | Fixed output size in pixels (e.g., 64x64) |
| **Padding** | Extra pixels around the object centroid |
| **Downsample** | Resolution factor for crop extraction |
| **Label format** | Organize by subdirectory per class, or filename prefix |
| **Classification filter** | Select/deselect which classifications to export |
| **Format** | PNG, TIFF, JPEG |
Output structure depends on the label format:
- **Subdirectory**: `crops/ClassName/image_obj001.png`
- **Filename prefix**: `crops/ClassName_image_obj001.png`
GeoJSON & Metadata Sidecars
**GeoJSON Export** -- An orthogonal option available alongside any export category. When enabled, QuIET exports all annotations and detections as a `.geojson` file per image -- useful for COCO/YOLO-style training pipelines that need geometry alongside image data. Enable via the **"Also export GeoJSON annotations"** checkbox on the image selection step.
**Metadata Sidecar Files** -- Every batch export automatically generates a human-readable `.txt` metadata file alongside the exported images. These files provide essential context for interpreting exports later, especially when shared with collaborators or loaded into external tools.
**Mask exports** produce `mask_legend.txt` containing:
- Label-to-class mapping (e.g., `1 = Tumor`, `2 = Stroma` for grayscale labels)
- Mask type, object source, boundary settings
- Pixel size after downsampling
**Rendered, raw, and tiled exports** produce `export_info.txt` containing:
- Channel names and colors (fluorescence) or stain vectors (brightfield H&E/H-DAB)
- Display settings applied during rendering (if applicable)
- Pixel size with downsample factor
- Tile size and overlap (for tiled exports)
Images with different channel configurations are automatically grouped in the metadata file. Metadata writing never interrupts the export -- failures are logged but silently ignored.
---
Script Generation
Every export produces a **self-contained Groovy script** that:
- Runs standalone in QuPath's script editor (no extension dependencies)
- Contains all configuration as editable variables at the top
- Processes all project images in a batch loop
- Reports progress and error counts
- Can be saved, version-controlled, and shared
Use the **Copy Script** or **Save Script...** buttons in the wizard to capture the generated script before or after running an export.
Output Structure
Exports are written to a configurable output directory. The default structure under a QuPath project is:
```
/
exports/
rendered/ # Rendered image exports
image_001.png
export_info.txt # Channel info, display settings, pixel size
masks/ # Label/mask exports
image_001.png
mask_legend.txt # Label-to-class mapping, pixel size
raw/ # Raw pixel data exports
image_001.tif
export_info.txt # Channel info, pixel size
tiles/ # Tiled ML exports
/
_[x,y,w,h].tif
_[x,y,w,h].png (label)
export_info.txt # Channel info, tile params, pixel size
crops/ # Object crop exports
/
_obj001.png
```
Filenames are sanitized using QuPath's `GeneralTools.stripInvalidFilenameChars()` for cross-platform compatibility.
Preferences
All wizard settings are automatically persisted across QuPath sessions. When you reopen the export wizard, your previous configuration (mask type, downsample, format, padding, etc.) is restored.
Preferences are stored in QuPath's standard preference system under the `quiet.*` namespace.
Building from Source
```bash
# Clone the repository
git clone https://github.com/uw-loci/qupath-extension-image-export-toolkit.git
cd qupath-extension-image-export-toolkit
# Build the extension JAR (includes all dependencies)
./gradlew shadowJar
# The JAR is at: build/libs/qupath-extension-image-export-toolkit-*-all.jar
```
### Other Gradle Tasks
```bash
# Run all tests
./gradlew test
# Compile only (quick check)
./gradlew compileJava
# Clean build artifacts
./gradlew clean
```
### Project Structure
```
src/main/java/qupath/ext/quiet/
QuietExtension.java # Extension entry point
advice/
AdviceItem.java # Single advice result (severity, title, config section ref)
AdviceSeverity.java # ERROR, WARNING, INFO
ImageContext.java # Per-image metadata for advice checks
PublicationAdviceChecker.java # QUAREP-LiMi guideline checks
export/ # Export logic + script generation
ExportCategory.java # RENDERED, MASK, RAW, TILED, OBJECT_CROPS
OutputFormat.java # PNG, TIFF, JPEG, OME_TIFF, OME_TIFF_PYRAMID, SVG
RenderedExportConfig.java # Rendered export configuration with sub-config records
RenderedImageExporter.java # Rendered export logic
MaskExportConfig.java # Mask/label export configuration (rejects JPEG)
MaskImageExporter.java # LabeledImageServer-based mask export
RawExportConfig.java # Raw pixel export configuration
RawImageExporter.java # Raw pixel export logic
TiledExportConfig.java # Tiled ML export configuration
TiledImageExporter.java # TileExporter-based tiled export
ObjectCropConfig.java # Object crop export configuration
ObjectCropExporter.java # Per-object crop export logic
GeoJsonExporter.java # GeoJSON annotation export
BatchExportTask.java # JavaFX Task for background batch processing
ExportResult.java # Export outcome tracking
ScaleBarRenderer.java # Java2D scale bar with background box support
ColorScaleBarRenderer.java # Color-mapped legend for density maps
PanelLabelRenderer.java # Panel letter label renderer (A, B, C...)
InfoLabelRenderer.java # Per-image metadata text stamp renderer
InsetRenderer.java # Magnified-inset / detail-panel renderer (Java2D utility)
TextRenderUtils.java # Shared text rendering (outlined text, font sizing)
ExportMetadataWriter.java # Metadata sidecar file writer
GlobalDisplayRangeScanner.java # Global min/max display range computation
ScriptGenerator.java # Script generation dispatcher
RenderedScriptGenerator.java # Groovy script for rendered export
MaskScriptGenerator.java # Groovy script for mask export
RawScriptGenerator.java # Groovy script for raw export
TiledScriptGenerator.java # Groovy script for tiled export
ObjectCropScriptGenerator.java # Groovy script for object crop export
ui/
ExportWizard.java # Main wizard window (Simple/Advanced mode toggle)
CategorySelectionPane.java # Step 1: category cards
SectionBuilder.java # Collapsible TitledPane section factory
RenderedConfigPane.java # Step 2a: rendered options (smart defaults, live preview)
MaskConfigPane.java # Step 2b: mask options (no JPEG)
RawConfigPane.java # Step 2c: raw options
TiledConfigPane.java # Step 2d: tiled options
ObjectCropConfigPane.java # Step 2e: object crop options
ImageSelectionPane.java # Step 3: image list + run + advice button
ImageEntryItem.java # Wrapper for ProjectImageEntry in the image selection list
GuidelinesPane.java # QUAREP-LiMi context-sensitive guidelines (Step 2 right panel)
PublicationAdvicePane.java # Floating advice dialog with section references
preferences/
QuietPreferences.java # Persistent preference storage
src/main/resources/
qupath/ext/quiet/ui/
strings.properties # All UI strings (i18n-ready)
META-INF/services/
qupath.lib.gui.extensions.QuPathExtension
```
Known Limitations
- **OME-TIFF Pyramid** requires `qupath-extension-bioformats` to be installed alongside QuIET. Without it, pyramid exports fall back to flat OME-TIFF.
- **SVG export** uses the JFreeSVG library for vector rendering. The base image is embedded as a raster element; annotations and overlays are rendered as vector paths. SVG is only available for rendered exports.
- **Channel selection** currently uses channel indices. The UI populates available channels, but auto-detection from image metadata is planned for a future release.
- **Tiled GeoJSON** produces one GeoJSON file per tile via QuPath's `TileExporter.exportJson()` API (not a single consolidated file).
- Rendered export with classifier overlay requires a pixel classifier saved in the QuPath project.
- Density map overlay requires a density map saved in the QuPath project (created via **Analyze > Density maps**).
- **Display Settings** "Current Viewer" mode requires an image to be open in the viewer at export time. "Saved Preset" mode requires presets saved via QuPath's Brightness & Contrast dialog.
Roadmap
Future releases may include:
- Inset / zoom panels exposed in the UI (the `InsetRenderer` primitive exists in code but is not yet wired into any config pane)
- Multi-panel grid / figure layout composition
- Contour/outline mask export
- Stain deconvolution channel export
- COCO/YOLO annotation format export
**Recently implemented** (now available):
- ~~Split-channel export~~ -- individual fluorescence channels + merge (v0.6.0)
- ~~Display range matching~~ -- global matched display settings across batch images (v0.6.0)
- ~~DPI / resolution control~~ -- target DPI mode for journal requirements (v0.7.0)
- ~~Dimension / timestamp labels~~ -- info label with template placeholders (v0.7.0)
- ~~Scale bar smart defaults~~ -- auto-detect color from project images (v0.7.3)
- ~~QUAREP guidelines panel~~ -- context-sensitive publication advice on Step 2 (v0.7.3)
- ~~Publication Advice floating dialog~~ -- with section highlighting on Step 2 (v0.7.3)
- ~~Channel / stain legend overlay~~ -- optional color legend on rendered exports, plus per-panel color swatches for split-channel
- ~~Skip empty mask images~~ -- omit mask output for images that have no objects in the selected classes
- ~~Simple / Advanced UI mode~~ -- single-click toggle to hide or reveal rarely-used controls across every step
See `documentation/POTENTIAL_FEATURES.md` for detailed implementation plans.
---
## Support
For general support and feature requests, please post on the [image.sc forum](https://forum.image.sc/) with the `#qupath` tag and mention `@Mike_Nelson` to flag the topic for my attention.
## License
This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
## Acknowledgments
Built on top of [QuPath](https://qupath.github.io/), an open-source platform for bioimage analysis. QuIET leverages QuPath's `LabeledImageServer`, `TileExporter`, `TransformedServerBuilder`, and `ImageWriterTools` APIs.
## AI-Assisted Development
This project was developed with assistance from [Claude](https://claude.ai) (Anthropic). Claude was used as a development tool for code generation, architecture design, debugging, and documentation throughout the project.