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find-rings

Detect diffraction rings in X-ray detector images and derive initial beam center and radii.

Updated Jan 27, 2026
Search Tags:#calibration#image-processing#x-ray#diffraction-rings#ring-detection#beam-center
One-click install
npx skills add https://github.com/carbonscott/deploy-opencode --skill find-rings
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: find-rings
Source: https://github.com/carbonscott/deploy-opencode/tree/main/claude/skills/find-rings
Command: npx skills add https://github.com/carbonscott/deploy-opencode --skill find-rings

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Detect diffraction rings in X-ray detector images and derive initial center and radii to seed geometry fitting for detector calibration.

Core Features & Use Cases

  • End-to-end ring detection using ELSD to identify ring arcs, generate initial center and radii.
  • Sub-pixel refinement of ring radii and beam center via spatial-calib-xray optimizer.
  • Visualization and validation overlays to assess fit quality across multi-panel detectors and calibration workflows.

Quick Start

Run the find-rings end-to-end pipeline on IMAGE.npy to produce rings.json and an optional overlay visualization.

Frequently Asked Questions about find-rings

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I detect diffraction rings in X-ray detector images for calibration?▼

Multi-panel detector calibration is supported through automated powder-ring identification and initial center estimation. ELSD detects ring arcs across detector stages, outputting rings.json to prepare for geometry fitting with spatial-calib-xray.

What is the process for estimating the beam center from powder diffraction rings?▼

Beam center estimation from powder diffraction rings is achieved by running the end-to-end pipeline on your X-ray image data. It generates initial center coordinates and radii to prepare the data for geometry fitting.

Do I need ELSD detection results before estimating X-ray diffraction ring centers?▼

ELSD-based detection results are required because the Skill uses them to identify ring arcs and generate initial beam centers. You must supply an input image like IMAGE.npy to trigger the automated ring detection and center estimation pipeline.

How do I refine diffraction ring radii after initial detection?▼

Refine diffraction ring radii by passing the detected rings.json output to spatial-calib-xray. This subsequent fitting step performs sub-pixel refinement of ring radii and beam center coordinates to finalize the detector geometry calibration.

Can I visualize diffraction ring fits across multi-panel X-ray detectors?▼

Visualization of diffraction ring fits is available as an optional output when running the detection pipeline. It generates validation overlays on your input images to assess fit quality across multi-panel detectors and various calibration stages.

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