Svenesis Siril Scripts

A collection of Python scripts for Siril (astronomical image processing).

Author and links

• Author: Sven Ramuschkat — www.svenesis.org
• Repository: github.com/sramuschkat/Siril-Scripts

License

GPL-3.0-or-later

Scripts

Script	Description	Instructions
Svenesis Annotate Image	Annotate plate-solved images with catalog objects, coordinate grids, and export as PNG/TIFF/JPEG.	Guide · DE
Svenesis Blink Comparator	Animate sequences for rapid visual inspection and data-driven frame selection with statistics, scatter plots, and batch reject.	Guide · DE
Svenesis Gradient Analyzer	Analyze background gradients with heatmaps, diagnostics, and tool recommendations.	Guide · DE
Svenesis Image Advisor	Analyze a stacked linear image and get a prioritized processing workflow with concrete Siril commands.	Guide · DE
Svenesis Multiple Histogram Viewer	View linear and stretched images with RGB histograms, 3D surface plots, and detailed statistics.	Guide · DE
Svenesis Script Security Scanner	Scan Siril Python scripts for malicious patterns across 10 threat categories.	—

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Svenesis Annotate Image

File: Svenesis-AnnotateImage.py (v1.0.0) — Detailed Instructions · Deutsche Anleitung

Renders catalog annotations (deep-sky objects, named stars, coordinate grid, compass, info box) onto a plate-solved image and exports it as a shareable PNG, TIFF, or JPEG. Inspired by PixInsight's AnnotateImage script. Unlike Siril's built-in overlay annotations, this script burns the annotations into an exportable image — ready to post on social media, forums, or include in observation reports.

Screenshots

Main window: catalog annotations with object type filtering, coordinate grid, compass rose, info box, and color-coded legend. Preview tab shows the annotated result.

Features

Object selection by type

Instead of choosing catalogs, you select which types of objects to annotate. All embedded catalogs are always searched — objects are filtered by your type selection:

Color	Type	Examples
Gold	Galaxies	M31, M51, M81, NGC 4565, Centaurus A
Red	Emission Nebulae	Orion, Lagoon, Eagle, Rosette, Carina
Light red	Reflection Nebulae	M78, Witch Head, Iris, Rho Ophiuchi
Green	Planetary Nebulae	Ring (M57), Dumbbell (M27), Helix, Owl
Light blue	Open Clusters	Pleiades (M45), Double Cluster, Wild Duck
Orange	Globular Clusters	M13, Omega Centauri, 47 Tucanae
Magenta	Supernova Remnants	Crab (M1), Veil Nebula, Simeis 147
Grey	Dark Nebulae	Horsehead (B33), Pipe, Snake, Coalsack
Red-pink	HII Regions	Heart, Soul, Barnard's Loop, Cave Nebula
White	Named Stars	~275 IAU-named stars to mag ~5.5

Select All / Deselect All buttons for quick toggling.

Embedded catalogs

• Messier — all 110 objects with common names
• NGC — ~230 bright objects (popular astrophotography targets)
• IC — ~40 bright Index Catalogue objects (Horsehead, Flaming Star, Pelican, Heart & Soul, Elephant's Trunk, etc.)
• Caldwell — 109 objects complementing Messier (Eta Carinae, Centaurus A, Helix, Double Cluster, Veil, etc.)
• Sharpless — ~60 HII emission regions (Simeis 147, Barnard's Loop, Tulip, Cave, etc.)
• Barnard — ~30 dark nebulae + LDN entries (Horsehead, Pipe, Snake, Barnard's E, Boogeyman)
• Named Stars — ~275 IAU-named and Bayer-designated stars with full-sky coverage to magnitude ~5.5

SIMBAD online query

Optional online query to the SIMBAD astronomical database for objects not in the embedded catalogs (UGC, MCG, PGC, Abell, Arp, Markarian, etc.). Survey catalog junk (SDSS, 2MASS, GPM, Gaia, etc.) is automatically filtered out. Requires astroquery package and internet connection.

Annotation overlays

• Leader lines: Thin connecting lines from each label to its object marker — essential in crowded fields to see which label belongs to which object.
• Color legend: Auto-generated legend box (bottom-left) showing only the object types present in the current annotation.
• Coordinate grid: RA/DEC grid with auto-spaced lines and labeled coordinates.
• Info box: Semi-transparent box (top-left) with center RA/DEC, field of view, pixel scale, rotation, and object count.
• Compass rose: North/East direction arrows derived from WCS.

Display options

• Configurable font size, marker size, and magnitude limit
• Object size rendered as scaled ellipses (from catalog angular size)
• Common names display (e.g. "M31 (Andromeda Galaxy)")
• Optional magnitude and type labels
• Color coding by object type (configurable)
• Label collision avoidance (8-direction greedy algorithm)

Output

• Formats: PNG (recommended), TIFF, JPEG
• DPI: 72–300 (150 default for screens, 300 for print)
• Auto-timestamped filenames prevent overwriting
• Preview tab shows the result immediately after annotation
• Open output folder / Open image buttons for quick access

WCS detection

Robust plate-solve detection with 6 fallback strategies:

1. FITS header as dict (primary — same approach as Galaxy_Annotations.py)
2. FITS header as string (astropy parsing)
3. Keywords pltsolvd / wcsdata flag check
4. pix2radec sampling to build WCS from Siril's coordinate transform
5. pix2radec probe without plate-solve flag
6. FITS file on disk

Coordinate transforms use siril.radec2pix() for maximum compatibility.

Other features

• Persistent settings: All checkboxes, sliders, and options saved between sessions via QSettings
• Keyboard shortcut: F5 = Annotate
• Progress bar with status feedback during annotation
• Log tab with detailed diagnostic output
• Dark-themed PyQt6 GUI matching Gradient Analyzer style
• Buy me a Coffee support dialog

Requirements

• Siril 1.4+ with Python script support
• sirilpy (bundled with Siril)
• numpy, PyQt6, matplotlib, astropy (installed automatically via s.ensure_installed)
• Optional: astroquery (for SIMBAD online queries — pip install astroquery)

Usage

1. Load an image in Siril and plate-solve it (Tools → Astrometry → Image Plate Solver).
2. Run Svenesis Annotate Image from Siril: Processing → Scripts (or your Scripts menu).
3. Select which object types to annotate using the color-coded checkboxes.
4. Adjust font size, marker size, magnitude limit, and extras (grid, info box, compass, legend, leader lines).
5. Click Annotate Image (or press F5).
6. Review the result in the Preview tab. Use Open Annotated Image to view it full-size.

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Svenesis Blink Comparator

File: Svenesis-BlinkComparator.py (v1.2.3) — Detailed Instructions · Deutsche Anleitung

Animates the currently loaded sequence as a blink animation for rapid visual inspection and data-driven frame selection. Comparable to PixInsight's Blink + SubframeSelector — identify satellite trails, clouds, tracking errors, focus drift, and bad frames, then reject them with a single click. All changes are collected locally and only applied to Siril when you confirm.

Screenshots

Main window: viewer with frame info overlay, sortable statistics table, statistics graph with running average, scatter plot, thumbnail filmstrip, batch selection, and approval expressions.

Features

Animated playback

• Configurable speed (1–30 FPS) with loop option and Play/Pause (Space key)
• Frame navigation: First, Previous, Next, Last buttons + draggable color-coded slider
• Crossfade transition option for smooth blending between frames
• Color-coded slider: Red tick marks at excluded frame positions for instant overview

Four display modes

• Normal: Standard autostretch view for visual inspection.
• Difference: Absolute difference vs. reference frame — satellites, clouds, and tracking errors become immediately visible as bright spots.
• Only included: Skips excluded frames during playback — verify after marking.
• Side by Side: Current frame on left, reference on right, synchronized zoom/pan.

Statistics table (sortable)

• All frames listed with Weight, FWHM, Roundness, Background, Stars, Median, Sigma, Date, Status
• Click any column header to sort — sort by FWHM to instantly find the worst frames
• Click a row to jump to that frame in the viewer
• Multi-select (Ctrl+click, Shift+click) → right-click → "Reject selected"

Composite quality weight

• Each frame gets a normalized quality score (0–1) based on FWHM (lower=better), roundness (higher=better), background (lower=better), and star count (more=better)
• Sort by Weight to see best and worst frames at a glance

Statistics graph

• FWHM, Background, Roundness plotted as line charts across all frames
• Running average (7-frame moving average) for trend detection
• Excluded frames shown as red dots, current frame as white dashed line
• Instantly reveals focus drift, clouds rolling in, or tracking degradation over time

Scatter plot

• 2D scatter of any two metrics (FWHM vs Roundness, FWHM vs Background, etc.)
• Outlier frames immediately visible as dots far from the cluster
• Click a dot to jump to that frame
• Axis-normalized click detection (both axes contribute equally to nearest-point selection)

Frame selection

• Manual marking: G = include, B = exclude (with auto-advance to next frame)
• Batch reject by threshold: Reject all frames where FWHM > 4.5 (or any metric/operator/value combination) with live preview count
• Reject worst N%: Reject the worst 10% by FWHM, Background, or Roundness
• Approval expressions: Multi-criteria AND filter (e.g., FWHM < 4.5 AND Roundness > 0.7 AND Stars > 50) — rejects frames that fail any condition
• Multi-select in table: Ctrl+click or Shift+click rows, right-click → "Reject selected"
• Undo (Ctrl+Z): Single undo for individual marks, grouped undo for batch operations (one Ctrl+Z undoes entire batch)
• Pending changes shown in the left panel — only applied to Siril when you click "Apply Changes"

Thumbnail filmstrip

• Horizontal scrollable strip with color-coded borders: green = included, red = excluded, blue = current
• Click any thumbnail to jump to that frame
• Lazy loading: Thumbnails loaded on demand as you scroll
• Adjustable size: Slider in Display Options

Zoom, pan & ROI

• Scroll wheel zoom (0.1x–20x), right-click drag pan
• 1:1 pixel zoom button for precise star shape inspection
• ROI blink: Draw a rectangle on the canvas, blink only that region — perfect for checking star shapes in corners

Frame info overlay

• Frame number, FWHM, roundness, and quality weight burned into the image corner during playback
• Toggleable in Display Options

Export

• Rejected frame list (.txt) with sequence metadata
• Statistics CSV (full table with all metrics + inclusion status)
• Animated GIF of the blink animation (included frames, scaled to 480px)
• Copy to clipboard (Ctrl+C) for quick forum posts

Other features

• Linked vs. independent stretch: Toggle between consistent brightness (linked) and per-frame detail (independent)
• A/B frame toggle (T key): Pin a frame, press T to toggle between pinned and current
• Per-frame histogram widget in the left panel
• Session summary on close: Frames viewed, excluded count, mean/best/worst FWHM
• Persistent settings: FPS, loop, auto-advance, crossfade, linked stretch, overlay, thumbnail size, table sort column
• Dark-themed PyQt6 GUI matching Gradient Analyzer style
• Buy me a Coffee support dialog

Keyboard shortcuts

Key	Action
Space	Play / Pause
← / →	Previous / Next frame
Home / End	First / Last frame
G	Mark frame as good (include)
B	Mark frame as bad (exclude)
D	Toggle difference mode
Z	Reset zoom
T	Pin / toggle A/B frame comparison
Ctrl+Z	Undo last marking (single or batch)
Ctrl+C	Copy current frame to clipboard
1–9	Set playback speed (FPS)
+ / -	Speed up / slow down
Esc	Close

Requirements

• Siril 1.4+ with Python script support
• sirilpy (bundled with Siril)
• numpy, PyQt6, matplotlib (installed automatically via s.ensure_installed)
• Optional: Pillow (for GIF export)

Usage

1. Load a registered sequence in Siril (the sequence must be loaded, not just a single image).
2. Run Svenesis Blink Comparator from Siril: Processing → Scripts (or your Scripts menu).
3. The script loads all frame statistics automatically. Use the Statistics Table tab to sort by FWHM and identify bad frames.
4. Mark bad frames with B (auto-advances), or use Batch Selection / Approval Expression for bulk rejection.
5. Review in the Statistics Graph and Scatter Plot tabs to verify your selection.
6. Click Apply Changes to Siril to send frame inclusion/exclusion to Siril.
7. Use Export buttons to save rejected frame list, statistics CSV, or animated GIF.

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Svenesis Gradient Analyzer

File: Svenesis-GradientAnalyzer.py (v1.8.4) — Detailed Instructions · Deutsche Anleitung

Reads the current image from Siril, divides it into a configurable grid of tiles, computes sigma-clipped median background levels per tile, and renders a color-coded heatmap. It helps you assess background gradients (e.g. from light pollution), decide whether background extraction is needed, and choose the right tool and parameters for the job.

Screenshots

Main window: heatmap with sample point guidance, 3D surface view, gradient strength gauge, and quadrant analysis. Nine visualization tabs with context-sensitive descriptions.

Features

Beginner-friendly UI

• "What is a gradient?" introduction: Getting Started tab explains gradients with a visual analogy and common causes (light pollution, vignetting, sensor artifacts) before any technical details.
• Beginner Glossary: Technical Reference tab includes 25+ plain-language definitions (gradient, flat/dark/bias frames, linear/stretched, polynomial degree, R², FWHM, SNR, tool names).
• Self-explaining action plan: Each step explains what the term means, why it matters, and how to do it in Siril (including menu paths and Console instructions).
• Tiered Analysis Results: Summary & Actions tab with color-coded verdict, plain-English explanation, and prioritized action plan. Detailed Metrics tab with inline jargon explanations. Before/After delta tab when re-analyzing.
• Tiered Recommendations: Quick Guide tab with styled, categorized suggestions (critical issues, tools, workflow). Full Details tab with raw diagnostic output.
• Organized Help dialog: Six tabs — Getting Started, Tabs, Tools, Options, Warnings, Reference — with expanded beginner-friendly explanations throughout.
• Tool descriptions with workflow: Each tool (AutoBGE, subsky, GraXpert, VeraLux Nox) includes what it does, when to use it, how to install/run it, and pros/cons.
• Contextual tooltips: Every checkbox, gauge, and widget explains why you'd use it, not just what it does.
• Single Analyze button (F5): Always loads the current Siril image and runs the full analysis. No separate Refresh button needed.
• Compact Siril log: Only essential information (strength, assessment, critical warnings) is logged to the Siril console. Full details are in the Analysis Results and Recommendations dialogs.
• Context-sensitive tab descriptions: Plain-language descriptions above the visualization area with "what to look for" guidance.

Analysis & diagnostics

• Configurable grid: 4–64 rows/cols with iterative sigma-clipping (1.5–4.0σ, sample std) to exclude stars and bright objects.
• Gradient metrics: Robust P95-P5 percentile strength (%), brightest-side direction, uniformity, and confidence indicator (P95-P5 SNR-based). Resists outlier tiles from hotspots and artifacts.
• Visual strength gauge: Color-coded severity bar (green → yellow → orange → red) with configurable threshold presets (Broadband 1.5/4/12%, Narrowband 0.8/2.5/6%, Fast optics 3/6/16%).
• Quadrant analysis: NW/NE/SW/SE median values with brightest/darkest highlighting.
• Gradient complexity: Polynomial fits (degree 1/2/3) with R² comparison to determine optimal subsky degree.
• Vignetting detection: Radial vs. linear model fitting and edge-to-center ratio; symmetry analysis for flat calibration quality.
• Extended object detection: Flags tiles containing nebulae/galaxies that could bias the gradient fit.
• Mosaic panel boundary detection: Identifies sharp linear discontinuities from stitched panels.
• Hotspot detection: Outlier tiles (satellite trails, artifacts) flagged at > 3σ from neighbors.
• Residual pattern detection: Moran's I spatial autocorrelation to check if polynomial degree is sufficient.
• Improvement prediction: Estimates post-extraction gradient strength from P95-P5 of model residuals (consistent with main metric).
• Light pollution color: Characterizes LP type from per-channel gradient strengths (sodium, LED, mercury, broadband) with 1.5x dominance threshold to avoid OSC false positives.
• Linear data detection: Uses median level and mean/median ratio (skewness) to distinguish stretched data from linear narrowband/nebula images.
• Star density warning: Flags dense star fields that may bias background estimates.
• Dew/frost detection: Cross-correlates radial FWHM increase with center brightness for corrector plate dew detection.
• Amplifier glow detection: Detects exponential corner brightness profile characteristic of CCD/CMOS amp glow.
• Banding/sensor bias detection: FFT-based detection of periodic row/column patterns from sensor readout artifacts.
• Normalization detection: Warns when background-normalized data may underestimate true gradient (requires 2+ evidence pieces to avoid false positives).
• FITS calibration check: Reads FLATCOR/CALSTAT/DARKCOR from FITS headers to verify flat/dark/bias calibration was applied.
• Geographic LP direction: Converts gradient direction to real-world compass bearing via WCS rotation.
• Photometric sky brightness: Rough mag/arcsec² and Bortle class estimate from SPCC-calibrated images (approximate — uses assumed zeropoint, not a substitute for SQM measurements).
• Cos^4 vignetting correction: Separates natural optical falloff from true gradients, especially for fast optics (f/2–f/4).
• FWHM/eccentricity map: Star shape variation across the field with sensor tilt and field curvature detection. Minimum 1.5 px FWHM filter rejects hot pixels.

Visualizations (9 tabs)

• 2D heatmap & 3D surface: Color-coded tile map with optional gradient direction arrow overlay, plus interactive 3D surface view. Colorblind-friendly colormap option (cividis).
• Gradient profiles: Horizontal and vertical cross-section plots showing where the gradient ramps across the image.
• Tile distribution histogram: Background value distribution — tight peak = uniform, broad/bimodal = gradient.
• Per-channel (RGB) analysis: Separate heatmaps per channel for detecting chromaticity in light pollution. Auto-disabled for mono images.
• Background model preview: Fitted polynomial surface (what subsky would subtract) and residuals.
• Gradient magnitude map: Rate-of-change visualization highlighting the steepest gradient transitions.
• Subtraction preview: Side-by-side before/after comparison of gradient removal at full pixel resolution.
• FWHM / Eccentricity map: Star shape metrics across the field.
• Residual/exclusion mask: Polynomial fit residuals alongside red-overlaid exclusion mask showing which tiles were excluded.

Tool recommendations

• Actionable suggestions: Suggests subsky (positional syntax subsky degree samples), AutoBGE, GraXpert, or VeraLux Nox based on gradient characteristics, with step-by-step workflow guidance.
• Priority-based workflow: Critical hardware/calibration issues are flagged before extraction recommendations.
• Sample point guidance: Heatmap overlay (green = good sample regions, red = avoid) to guide manual sample placement.

Export & persistence

• Report export: Plain-text analysis report derived from the same content as the Analysis Results and Recommendations dialogs — single source of truth.
• PNG export: Heatmap image with key metrics burned in (annotated export).
• JSON sidecar: Persist analysis results including tile medians array for cross-session comparison and overlay.
• Persistent settings: Grid size, sigma, checkboxes, colormap, and preset saved between sessions via QSettings.
• Colorbar locking: Consistent heatmap scale across re-analyses for meaningful visual comparison.
• Keyboard shortcut: F5 = Analyze (loads current image from Siril and runs analysis).

Requirements

• Siril 1.4+ with Python script support
• sirilpy (bundled with Siril)
• numpy, PyQt6, matplotlib, scipy (installed automatically via s.ensure_installed)
• Optional: astropy (for FITS header reading)

Usage

1. Load an image in Siril (linear data recommended for best accuracy).
2. Run Svenesis Gradient Analyzer from Siril: Processing → Scripts (or your Scripts menu).
3. Adjust grid resolution and sigma in the left panel, select a threshold preset, then click Analyze (or press F5).
4. Review the heatmap, profiles, and metrics across the 9 tabs. Check the recommendations for the suggested tool and parameters.
5. Apply the recommended extraction in Siril, then click Analyze (F5) again to re-analyze and compare before/after.

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Svenesis Image Advisor

File: Svenesis-ImageAdvisor.py (v1.3.1) — Detailed Instructions · Deutsche Anleitung

Analyses a stacked, linear FITS image loaded in Siril and generates a prioritised list of processing recommendations — including concrete Siril commands, suggested parameters, and reasoning. The script does not modify the image; it only diagnoses and advises. Think of it as a second opinion from an experienced astrophotographer before you start processing.

Features

• Full linear-stage workflow: Recommendations follow the correct processing order — Crop → Background Extraction → Platesolving → SPCC → SCNR → Denoise → Deconvolution → Starless — with post-processing roadmap (stretch, fine-tune, star recomposition, export).
• Linear state detection: Warns if the image is already stretched (scans FITS HISTORY for GHT, autostretch, MTF, asinh, etc. using word-boundary matching to avoid false positives).
• Calibration detection: Checks HISTORY for dark/flat/bias calibration; shows "Unknown" when no history is present (e.g. stacked in another app) instead of false negatives.
• Background gradient analysis: 8×8 sigma-clipped tile grid with gradient spread percentage, colour-coded heatmap, and pattern classification:
  • Vignetting — corners dark, centre bright (needs flats, not subsky)
  • Linear gradient — one side bright (light pollution, subsky appropriate)
  • Amp glow — single corner bright (may need masking)
  • Pattern classification is suppressed when gradient is below the action threshold to avoid noise-fitting.
• Calibration-aware gradient advice: When flats are missing, gradient recommendations note that the gradient may be vignetting that subsky cannot fully correct.
• Nebulosity-aware subsky: Adds -samples=15/25 to subsky commands when nebulosity is present, preventing polynomial overcorrection on nebula regions.
• Noise & SNR estimation: MAD-based noise on the darkest 25% of pixels; integration-time-aware advice (short integration → "add more subs" vs long integration → "faint target, denoise essential").
• Smart denoise ordering: Denoise is promoted to an actionable step before deconvolution even at high SNR, because Richardson-Lucy amplifies noise.
• Narrowband-adjusted nebulosity: Lower detection threshold (3σ) for narrowband/dual-narrowband images to catch diffuse low-contrast emission.
• Image type classification: Detects OSC Broadband, Mono, Narrowband, Luminance, and Dual-Narrowband OSC (L-eNhance, L-Extreme, NBZ, etc.) — adjusts SPCC and colour balance advice accordingly.
• Star quality diagnostics: FWHM (pixels and arcsec when plate-solved), elongation, centre-vs-edge spatial analysis, saturated star count, field curvature/coma detection. Soft stars and elongation are elevated as acquisition warnings near the top of the report.
• Deconvolution guidance: Richardson-Lucy recommendation with makepsf manual -gaussian + rl -loadpsf=psf.fits commands when SNR allows; suggests GUI deconvolution tool for interactive control.
• Starless recommendation: Only when nebulosity warrants it; starnet -stretch for linear images, bare starnet for already-stretched; autostretch preview tip included.
• Dynamic range: Usable DR in stops (peak / noise floor), informs stretch aggressiveness advice with background pedestal warnings for high-background images.
• Clipping detection: Black and white clipping percentages with cause suggestions. Extreme black clipping (>50%) with no detected signal triggers a critical warning and suppresses the workflow. Normal linear data (background near zero with real content) is correctly identified.
• Crop detection: Scans edges for stacking borders and generates boxselect/crop commands. Warns when scan limits are hit and borders may extend further.
• Per-channel noise table: R/G/B noise levels with noisiest channel highlighted. Notes when channels are unusually well-balanced (may already be colour-calibrated).
• Image sanity checks: Flags common phone/screen resolutions (1080×1920, etc.) as unusual for astro cameras. Suppresses processing workflow when the image fails basic sanity checks.
• Verified Siril commands: All command syntax verified against Siril 1.4.x binary (subsky, denoise -mod=, makepsf manual -gaussian, rl -loadpsf= -iters=, starnet -stretch, platesolve, spcc).
• Script export (.ssf): Generates an executable Siril script with save checkpoints after key stages (requires 1.4.1).
• Report export (.txt): Full plain-text report for archiving or sharing.
• PyQt6 dark-themed GUI: Left panel with controls and image info, right panel with scrollable HTML report including heatmap, per-channel table, findings, and workflow.

Requirements

• Siril 1.4.1+ with Python script support
• sirilpy (bundled with Siril)
• numpy, PyQt6 (installed automatically via s.ensure_installed)

Usage

1. Load a stacked, linear FITS image in Siril.
2. Run Svenesis Image Advisor from Siril: Processing → Scripts (or your Scripts menu).
3. The analysis runs automatically on launch. Review findings, statistics, heatmap, and the recommended workflow in the report panel.
4. Use Re-Analyse after making changes in Siril to get updated recommendations.
5. Use Export Script (.ssf) to save the workflow as a runnable Siril script, or Export Report (.txt) to save the full analysis.

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Svenesis Multiple Histogram Viewer

File: Svenesis-MultipleHistogramViewer.py (v1.1.0) — Detailed Instructions · Deutsche Anleitung

Reads the current linear image from Siril (or a linear FITS file), applies a 2%–98% percentile autostretch for preview, and displays Linear and Auto-Stretched views side by side with combined RGB histograms or 3D surface plots. You can also load up to 2 additional stretched FITS files for comparison. Compressed FITS (e.g. .fz, .gz) are supported.

Screenshots

Main window: Linear and Auto-Stretched columns with histogram view, controls, and statistics.

3D surface plot option and statistical data (Size, Min/Max, Mean, Median, Std, IQR, MAD, P2/P98, Range, Near-black/Near-white).

Features

• Image sources: Current image from Siril, or load a linear FITS directly (including compressed .fz/.gz); up to 2 stretched FITS for comparison.
• Views: Histogram (2D) or 3D surface plot (X/Y = pixel position, Z = channel value).
• Histogram: Combined RGB and per-channel (R, G, B, L) with Normal or Logarithmic Y-axis; X-axis in ADU.
• Statistics: Size, Pixels, Min/Max, Mean, Median, Std, IQR, MAD, P2/P98 (2nd/98th percentile), Range (P2–P98), Near-black/Near-white %. Tooltip explains each metric; “(subsampled)” when stats are from a subset of pixels.
• Enlarge Diagram: Button under each histogram/3D plot opens a larger modal with the same diagram and a channel legend.
• Help: Modal help with author info, usage, and control descriptions.
• Image zoom: −, Fit, 1:1, + per column; after loading, all images are fitted to their windows.
• Click on image: Shows pixel R, G, B, I (ADU) in the stats area and a vertical line in the histogram.

Requirements

• Siril 1.4+ with Python script support
• sirilpy (bundled with Siril)
• numpy, PyQt6, Pillow, astropy (installed automatically via s.ensure_installed)
• matplotlib (for 3D surface plot only)

Usage

1. Load an image in Siril (or use Load linear FITS... in the script).
2. Run Svenesis Multiple Histogram Viewer from Siril: Processing → Scripts (or your Scripts menu).
3. Use the left panel for view type (Histogram / 3D), Data-Mode (Normal / Log), channels, and image/source options. Use Enlarge Diagram for a larger histogram or 3D view.

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Svenesis Script Security Scanner

File: Svenesis-Script-Security-Scanner.py (v2.0.0)

Scans all Python scripts in your configured Siril script folders for potentially dangerous patterns across 10 threat categories. Siril scripts run with full user-level OS permissions, so a malicious script can do virtually anything on your machine. This tool gives you a first-pass analysis before you run any script you did not write yourself.

⚠️ A word of caution before you scan

Siril Python scripts are powerful — and that power cuts both ways. A script can do virtually anything your user account can do on this machine: delete files and folders, download and execute additional programs, exfiltrate data, modify system settings … everything you can imagine a bad actor might want to do.

We are a friendly and welcoming astronomy community — but you never truly know where a script came from or who really wrote it. Be careful about where you load scripts from.

This tool gives you an impression of what a script is doing under the hood — potentially dangerous calls, obfuscated code, network access, file deletions, and more. It is a genuine help for spotting suspicious behaviour.

However: this is a cat-and-mouse game (as we say in German: „Hase und Igel" — hare and hedgehog). A determined bad actor who knows this scanner exists will adapt their script to avoid triggering the rules. No automated tool can give you a 100 % guarantee. Use your own judgement, only run scripts from sources you trust, and keep backups of your data.

Stay safe — and clear skies. 🌠

⚠️ Important — Why you should always do an AI check

This scanner performs static analysis based on pattern matching — it looks for known dangerous signatures in the source code. A clever attacker can evade these patterns. ChatGPT and Claude understand code semantically, like a human expert would, and can catch threats that pattern-based tools miss entirely. Paste the script into either AI with the prompt below — it takes 30 seconds and could save you from serious harm:

"You are an expert Python developer and cybersecurity specialist. Analyze the following Python script designed for the astrophotography program Siril. The script can access Siril data via its API but runs with full user-level OS permissions. Review the code for any malicious, harmful, or risky behavior — including but not limited to: file system access, network calls, data exfiltration, privilege escalation, obfuscated code, or destructive operations. Provide a security risk assessment and a clear recommendation on whether the script is safe to run."

Screenshots

Main window: script directories, category selection, scan results grouped by file with severity indicators.

Features

• 10 threat categories: File System — Destructive, File System — Data Theft, Network — Exfiltration, Network — Inbound/Backdoor, Code Execution — Escalation, Persistence, Obfuscation, Denial of Service, Social Engineering, Supply Chain.
• Severity levels: HIGH (red) — likely dangerous; MEDIUM (orange) — suspicious; LOW (blue) — informational.
• Script directory discovery: Automatically reads configured Siril script paths from the OS-specific Siril config file; falls back to well-known default locations.
• Anti-evasion measures: Multi-line continuation joins, triple-quoted string awareness, import alias expansion, comment-line filtering.
• Detailed findings: Click any finding for a full explanation; double-click to open the file in your default text editor.
• Export: Save a full plain-text report of all findings with explanations.
• Startup warning: Explains the limitations of static analysis and reminds you to also use AI-assisted review.
• AI-assisted analysis tip: Includes a ready-to-use prompt for ChatGPT or Claude to perform a semantic review that can catch threats pattern-based tools miss.

Requirements

• Siril 1.4+ with Python script support
• sirilpy (bundled with Siril)
• PyQt6 (installed automatically when the script runs)

Usage

1. Run Svenesis Script Security Scanner from Siril: Processing → Scripts (or your Scripts menu).
2. The scanner auto-discovers your Siril script directories. Use Add Directory… or Paste Paths to add more.
3. Select the threat categories you want to scan, then press Scan Now.
4. Review findings grouped by file. Click a finding for details; double-click to open the file.
5. Use Export Report… to save the results as a plain-text file.