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nanodevice_flakedetect_align

32|6|Updated Mar 8, 2026

Search Tags:#opencv #sift #nanodevice #image-alignment #chamfer-de #grabcut

Ready to run

npx skills add https://github.com/caidish/KlayoutClaw --skill nanodevice-flakedetect-align

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: nanodevice_flakedetect_align
Source: https://github.com/caidish/KlayoutClaw/tree/main/skills/nanodevice_flakedetect_align
Command: npx skills add https://github.com/caidish/KlayoutClaw --skill nanodevice-flakedetect-align

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires opencv-python, numpy, scikit-learn, scipy, and includes scripts (resource) components.

What problem does it solve?

Register source microscope images to the full_stack coordinate system for automated, substrate-aware alignment of nanodevice features.

Core Features & Use Cases

SIFT-based same-substrate alignment: Registers bottom_part/reference to full_stack when images share substrate.
Chamfer+DE cross-substrate alignment: Aligns top_part to full_stack across materials with rotation/scale search.
Autonomous workflow with diagnostics: Generates alignment_report.json, footprints, and warp matrices; includes optional mirroring and precomputed warps.
Use case: Align a set of nanoscale flakes to a full-stack reference for GDS export and downstream processing.

Quick Start

Run the nanodevice_flakedetect_align workflow with your source, target, and bottom images to produce alignment reports and diagnostic visuals.

Frequently Asked Questions about nanodevice_flakedetect_align

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

FAQPage Schema

How do I align nanoscale microscope images to a full-stack reference coordinate system?▼

To align nanoscale microscope images, you register source images to the full_stack coordinate system using SIFT for same-substrate alignment or Chamfer+DE for cross-substrate alignment, generating warp matrices and diagnostic visuals.

What is the best way to align nanodevice flakes across different substrates?▼

The best way to align nanodevice flakes across different substrates is using Chamfer+DE cross-substrate alignment, which handles rotation and scale search to align top_part images to the full_stack reference.

Do I need Python and OpenCV to run nanodevice image alignment workflows?▼

Yes, you need Python 3.10+ with OpenCV, NumPy, SciPy, and scikit-learn installed to run the nanodevice image alignment workflow and generate alignment reports, warp matrices, and footprint masks.

Can I use SIFT for same-substrate nanodevice alignment?▼

Yes, SIFT supports same-substrate alignment by registering bottom_part or reference images to the full_stack coordinate system when the images share the same substrate material.

What diagnostic outputs are generated by nanodevice image alignment?▼

Nanodevice image alignment generates alignment_report.json, warp matrices, footprint masks, footprint contours, and diagnostic visuals to verify registration accuracy and support downstream GDS export.

Why does cross-substrate image alignment require Chamfer and DE instead of SIFT?▼

Cross-substrate image alignment requires Chamfer+DE because SIFT feature matching fails across different materials, while Chamfer distance with Differential Evolution handles rotation and scale variations between substrates.