What is tao-train-visual-changenet?

A computer-vision training tool for comparing image pairs to detect manufacturing defects in printed circuit boards (PCBs). It can classify pairs as pass or no-pass and create pixel-level masks showing where they differ.

Train, test, export, and run image-based PCB inspection models for automated optical inspection (AOI).

It helps automate visual inspection and identify defects without manually checking every image. The segmentation output also shows the affected areas.

tao-train-visual-changenet — Skill for Claude Code by NVIDIA-TAO

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add NVIDIA-TAO/tao-skill-bank --skill tao-train-visual-changenet

Clone the repo

git clone --depth 1 https://github.com/NVIDIA-TAO/tao-skill-bank

Made for: Claude Code.

Or install tao-skills, the plugin that ships this one along with the rest of its 76 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/nvidia-tao/tao-skill-bank/tao-train-visual-changenet/github.svg)](https://agentmods.dev/skills/nvidia-tao/tao-skill-bank/tao-train-visual-changenet)

Your own site

<a href="https://agentmods.dev/skills/nvidia-tao/tao-skill-bank/tao-train-visual-changenet"><img src="https://agentmods.dev/badge/skills/nvidia-tao/tao-skill-bank/tao-train-visual-changenet/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/nvidia-tao/tao-skill-bank/tao-train-visual-changenet"><img src="https://agentmods.dev/badge/skills/nvidia-tao/tao-skill-bank/tao-train-visual-changenet.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 92 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,498 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00092	$0.04498
Opus 5	$0.00046	$0.02249
Sonnet 5	$0.00018	$0.00900
Haiku 4.5	$0.00009	$0.00450

Measured 8d ago against content hash 1f767c28086c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

tao-train-visual-changenet scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/stage_backbone.py, scripts/validate_vcn_dataset.py, tests/test_validate_vcn_dataset.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/models/tao-train-visual-changenet/SKILL.md · 315 lines

How it starts

The opening of the file, as written. The whole thing — 315 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Visual ChangeNet

Standalone install? If this session was not initialized by the TAO skill bank plugin, run the tao-setup skill first (host preflight, credentials, cross-skill discovery).

Visual ChangeNet is a TAO Toolkit model for visual inspection and defect detection. It supports two tasks:

Classify — Binary image classification using a siamese-style architecture with a shared backbone (C-RADIO ViT) and a learnable difference module. Compares image pairs to classify defects as PASS/NO_PASS.
Segment — Pixel-level change segmentation using a ViT-Large NVDINOv2 backbone. Compares before/after image pairs to produce a binary change mask.

Classify supports the public C-RADIOv2-B backbone and six frozen DINOv3 variants. Read references/dinov3-backbones.md before selecting DINOv3; it contains the exact variant map, freeze requirement, Hugging Face access rules, and local-staging overlay. For C-RADIO, use the bundled scripts/stage_backbone.py and the mount in references/local-docker.md.

Segment specs use model.backbone.type: vit_large_nvdinov2 and the NVDINOv2 checkpoint family. Keep the checkpoint architecture aligned with the backbone type: NV_DINOV2_518_16_256.ckpt is compatible with the packaged segment templates, but it must not be used with fan_small_12_p4_hybrid. If you switch to a different segment backbone, use a matching checkpoint or leave model.backbone.pretrained_backbone_path empty for default initialization.

Dataclass Schemas

Generated TAO Core schemas are packaged in schemas/<action>.schema.json, with schemas/manifest.json listing available actions. Each generated schema also emits references/spec_template_<action>.yaml from the schema top-level default field. AutoML enablement is declared at the model layer in references/skill_info.yaml via automl_enabled. Runnable AutoML still requires schemas/train.schema.json and references/spec_template_train.yaml to exist and parse. Use the packaged train schema for automl_default_parameters, automl_disabled_parameters, defaults, min/max bounds, enums, option weights, math conditions, dependencies, and popular parameters. Do not expect ~/tao-core at runtime; maintainers regenerate schemas/templates before packaging the skill bank.

Read the full file on GitHub · 315 lines

Files

What ships with it

39 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

8d ago First seen · 315 lines · 92 tokens per session scan A 1f767c28086c

Subscribe to this mod's changes

tao-train-visual-changenet is a skill published in the GitHub repository NVIDIA-TAO/tao-skill-bank (88 stars, last pushed today), licensed Apache-2.0. It adds 92 tokens to every session and 4,498 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Data and AI Hardware and IoT aoi classification defect pcb segmentation siamese visual-inspection

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