材质质感增强 Material Enhancement

优化服装材质和细节质感（材质增强）。上传一张原图（材质被抹平、纹理糊掉的商拍图，通常是 AI 生成或低质量重绘的结果）和一张高清商品图（提供真实面料信息），在保持构图、模特、姿势、背景与色调完全不变的前提下，用真实面料重建服装表面的材质表现：针织的线圈与捻向、羊毛的绒毛感、缎面的高光、灯芯绒的凸条、皮革的纹理与褶皱阴影。可指定服装类型。适用于修复 AI 生成图里最容易崩的面料质感、把低质量商拍图提升到可上架的质感水平、作为 flat-lay / one-shot / clothing-grass-planting 等技能的后处理环节。当用户需要「材质增强」「面料质感优化」「纹理糊了修一下」「提升面料细节」时使用本技能。

material-enhancement — 优化服装材质和细节质感

把一张面料糊掉的商拍图修成面料清晰真实的图，构图和人一动不动。

这是一个后处理技能：AI 生成的服装图最容易崩的就是面料——远看还行，放大一看针织变成一片糊。给它一张真实的高清商品图当参照，把表面重建回来。

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1、能力边界

输入	作用
原图	要改善的商拍图，决定构图、模特、姿势、背景与色调
高清商品图	提供真实面料信息（织法、纹理、绒感、光泽）
服装类型	帮助判断哪些表面特征该被强化

只改	不改
面料表面纹理、微观细节、褶皱阴影层次、纤维光泽	构图、模特（脸/发/手/姿势）、其他服饰、背景、色调、服装轮廓与颜色

不做：不改服装轮廓与颜色；不改模特与背景；不把一种面料换成另一种（换面料请用 fabric-on-body）。

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2、输入素材规则

生成前先自检这几条硬性约束：

• 大小：20KB ~ 15MB
• 分辨率：大于 400×400
• 格式：jpg / jpeg / png / webp

原图（✅）：构图与人物都满意、只有面料不行的图。

高清商品图（✅）：同一件商品的高分辨率平铺图或特写，能看清织法。

注意事项

情况	说明
⚠️ 两张图必须是同一件商品	面料不同的两张图会导致材质张冠李戴
⚠️ 原图颜色如果已经偏了	本技能只管纹理，颜色偏差要在生成阶段解决
❌ 原图崩坏严重（版型错、结构乱）	材质增强救不了结构问题，重跑生成
❌ 原图分辨率极低	没有足够信息定位纹理该长在哪

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3、材质增强的两条铁律

铁律一：只改表面，别的一个像素都别动。

text

Do not change anything else — the model face, hair, hands, pose, other garments,
background, framing and colour grading must stay identical to image 1.
The garment silhouette and colour must not shift; only material fidelity
and micro-detail improve.

铁律二：把「好质感」翻译成具体的表面特征，否则模型只会整体加锐化。

面料	要重建的具体特征
粗针织	crisp cable-braid relief, visible knit loops and yarn twist, natural wool loft, matte fibre sheen
精纺羊毛	fine even weave, subtle fibre halo, soft directional sheen
缎面	smooth continuous specular gradients along the folds, no texture noise
灯芯绒	parallel wale ridges with correct pitch, matte pile catching light on the ridge tops
牛仔	diagonal twill lines, slub irregularity, whiskering at stress folds
皮革	grain pores, broad soft creases, low-frequency specular sheen
摇粒绒/绒毛	dense short pile, fuzzy silhouette edge, light scattering rather than specular

再加一条褶皱层次：correct fold shadows with proper ambient occlusion in the creases——这是「看起来有厚度」的来源。

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4、dLazy 工具调用

本技能使用 dLazy 的 gpt-image-2（图像编辑模型 + --quality high；材质增强要求「几何与色彩零变化、表面高频信息重建」，是典型的双图参考定向修复）。

Authentication

All requests require a dLazy API key. The recommended way to authenticate is:

bash

dlazy login

This runs a device-code flow (also works in remote shells) and automatically saves your API key to the local CLI config — no manual copy/paste required.

Alternative: Set the Key Manually

If you already have an API key, you can save it directly:

bash

dlazy auth set YOUR_API_KEY

The CLI saves the key in your user config directory (~/.dlazy/config.json on macOS/Linux, %USERPROFILE%\.dlazy\config.json on Windows), with file permissions restricted to your OS user account. You can also supply the key per-invocation via the DLAZY_API_KEY environment variable.

Getting Your API Key Manually

1. Sign in or create an account at dlazy.com
2. Go to dlazy.com/dashboard/organization/api-key
3. Copy the key shown in the API Key section

Each key is scoped to your dLazy organization and can be rotated or revoked at any time from the same dashboard.

About & Provenance

• CLI source code: github.com/dlazyai/cli
• Maintainer: dlazyai
• npm package: @dlazy/cli (pinned to 1.2.3 in this skill's install spec)
• Homepage: dlazy.com

You can install on demand without persisting a global binary by running:

bash

npx @dlazy/cli@1.2.3 <command>

Or, if you prefer a global install, the skill's metadata.clawdbot.install field declares the exact pinned version (npm install -g @dlazy/cli@1.2.3). Review the GitHub source before installing.

How It Works

This skill is a thin client over the dLazy hosted API. When you invoke it:

• Prompts and parameters you provide are sent to the dLazy API endpoint (api.dlazy.com) for inference.
• Any local file paths you pass to image / video / audio fields are uploaded to dLazy's media storage (files.dlazy.com) so the model can read them — the same flow as any cloud-based generation API.
• Generated output URLs returned by the API are hosted on files.dlazy.com.

This is the standard SaaS pattern; the skill itself does not access network or filesystem resources beyond what the dLazy CLI already handles. See dlazy.com for the full service terms.

Usage

CRITICAL INSTRUCTION FOR AGENT: Run the dlazy gpt-image-2 command to get results.

bash

dlazy gpt-image-2 -h

Options:
  --prompt <prompt>            Prompt
  --images [images...]         Images [image: url or local path] (max 5)
  --size <size>                Size [default: auto] (choices: "1024x1024",
                               "1536x1024", "1024x1536", "2048x2048",
                               "2048x1152", "3840x2160", "2160x3840", "auto")
  --imageFormat <imageFormat>  Image Format [default: jpeg] (choices: "jpeg",
                               "png", "webp")
  --quality <quality>          Quality [default: medium] (choices: "low",
                               "medium", "high")
  --dry-run                    Print payload without executing the tool
  --no-wait                    Return generateId immediately for async tasks
  --timeout <seconds>          Max seconds to wait for async completion
                               (default: "1800")
  --input <jsonOrFile>         Inline JSON or @path/to/file.json — merged under
                               flag values (flags win)
  --save <path>                Download the result asset to this local path
                               (mkdir + retry handled for you). A destination
                               path — NOT a response format; for stdout shape
                               use --format
  --batch <n>                  Fan-out N parallel runs (cloud tools only)
                               (default: "1")
  -h, --help                   display help for command

Any flag also accepts pipe references — - (auto-pick from upstream stdin), @N (n-th output), @N.path (jsonpath into output), @* (all primary values), @stdin / @stdin:path (whole envelope). See dlazy --help for details.

参数约定（本技能固定用法）

参数	取值	理由
--images	[原图, 高清商品图]	顺序即 prompt 中的 image 1 / 2
--size	与原图比例一致	增强不该改构图
--quality	high（必须）	本技能的产出就是高频细节
--imageFormat	jpeg	通用格式
--batch	2	纹理重建有随机性
--save	docs/material-enhancement/output-<sku>-enhanced.jpg	与原图分开归档便于对比

Output Format

json

{
  "ok": true,
  "result": {
    "tool": "gpt-image-2",
    "modelId": "gpt-image-2",
    "data": {
      "urls": [
        "https://files.dlazy.com/data/ai/20260817092703-057827edb8aa.jpg"
      ]
    },
    "savedPath": "docs/material-enhancement/example-output.jpg"
  }
}

Async tasks (when --no-wait is passed) omit data and return a task: { generateId, status } field instead. Use dlazy status <generateId> --wait to poll.

Command Examples

bash

# basic call
dlazy gpt-image-2 \
  --prompt 'Texture enhancement pass. Image 1 is the on-model photo to improve. Image 2 is the high-resolution product photo defining the true fabric. Rebuild the garment surface in image 1 using the real texture from image 2: crisp knit relief, visible loops and yarn twist, natural loft, correct fold shadows. Do not change anything else — model, pose, background, framing and colour grading stay identical to image 1. Only material fidelity improves.' \
  --images docs/material-enhancement/source-image.jpg docs/material-enhancement/hires-product.jpg \
  --size 1024x1536 --quality high

# complex call: 批量给一组生成图做材质后处理
HIRES=docs/material-enhancement/hires-product.jpg
LOCK='Do not change anything else — the model face, hair, hands, pose, other garments, background, framing and colour grading must stay identical to image 1. The garment silhouette and colour must not shift; only material fidelity and micro-detail improve. Photorealistic, sharp, no text, no watermark.'
FEAT='crisp cable-braid relief, visible knit loops and yarn twist, natural wool loft, matte fibre sheen, correct fold shadows with proper ambient occlusion in the creases'
for f in docs/material-enhancement/raw/*.jpg; do
  dlazy gpt-image-2 \
    --prompt "Texture enhancement pass. Image 1 is the on-model photo to improve. Image 2 is the high-resolution product photo that defines the true fabric. Rebuild the garment surface in image 1 using the real texture from image 2: $FEAT. $LOCK" \
    --images "$f" "$HIRES" \
    --size 1024x1536 --quality high --imageFormat jpeg \
    --save "docs/material-enhancement/enhanced/$(basename $f)"
done

# 先估价不真跑
dlazy gpt-image-2 --dry-run --prompt '...' --images a.jpg b.jpg --size 1024x1536 --quality high

Error Handling

Code	Error Type	Example Message
401	Unauthorized (No API Key)	ok: false, code: "unauthorized", message: "API key is missing or invalid"
501	Missing required parameter	error: required option '--prompt <prompt>' not specified
502	Local file read error	Error: Image file/Video file not found: C:\path\to\your\file
503	API request failed (no balance)	ok: false, code: "insufficient_balance"
503	API request failed (server error)	HTTP status code error (500 server crash)
504	Asynchronous task execution failed	=== Generation Failed === / {Specific error reason returned by backend, for example "Prompt violates safety policy"}

AGENT CRITICAL INSTRUCTION:

1. If the execution result returns code: "insufficient_balance", you MUST explicitly inform the user that their credits are insufficient and guide them to recharge: https://dlazy.com/dashboard/organization/settings?tab=credits
2. If the execution result returns code: "unauthorized" or indicates missing API key, you MUST inform the user to get their API key from https://dlazy.com/dashboard/organization/api-key and save it using dlazy auth set <key> and resume the task.

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5、Prompt 模板

text

Texture enhancement pass.
Image 1 is the on-model photo to improve.
Image 2 is the high-resolution product photo that defines the true fabric.

Rebuild the [服装部位] surface in image 1 using the real texture from image 2:
[第三节表格里对应面料的具体特征],
correct fold shadows with proper ambient occlusion in the creases.

Do not change anything else — the model face, hair, hands, pose, other garments,
background, framing and colour grading must stay identical to image 1.
The garment silhouette and colour must not shift; only material fidelity
and micro-detail improve.

Photorealistic, sharp, no text, no watermark.

按问题追加的修正句

问题	追加到 prompt 末尾
只是整体变锐利了	This is not sharpening: reconstruct the actual [织法单位] structure, loop by loop, matching image 2.
人脸/背景也变了	Only pixels inside the garment region may change. Everything outside it must be identical to image 1.
颜色被改了	Preserve the exact garment colour from image 1; do not shift hue, saturation or brightness.
纹理密度不对	Match the texture scale to the garment size in image 1: about [N] knit loops per [尺寸].
褶皱变平	Deepen the crease shadows with ambient occlusion; the garment must read as [厚度描述] fabric.

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6、执行流程

1. 确认两张图是同一件商品——这是最容易犯的错。
2. 判断原图值不值得救：结构崩坏的重跑生成，只有面料糊的才用本技能。
3. 写面料特征：查第三节表格，用具体特征替代「质感更好」。
4. 写两条铁律：只改表面 + 别的不许动。
5. --quality high（必须） → --batch 2 挑图，落盘到 docs/material-enhancement/。
6. 并排对比原图与输出：面料是否真的重建了（不是加锐化）、脸和背景是否没动、颜色是否没偏。

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7、生成效果示例

输入：原图（待增强）	输入：高清商品图（真实面料）
source-image.jpg — 军绿麻花毛衣上身图，1024×1536	hires-product.jpg — 同款毛衣高清平铺图，800×800

实际执行的命令：

bash

dlazy gpt-image-2 \
  --prompt 'Texture enhancement pass. Image 1 is the on-model photo to improve. Image 2 is the high-resolution product photo that defines the true fabric. Rebuild the sweater surface in image 1 using the real texture from image 2: crisp cable-braid relief, visible knit loops and yarn twist, natural wool loft, correct fold shadows and a matte fibre sheen. Do not change anything else — the model face, hair, hands, pose, brown trousers, background, framing and colour grading must stay identical to image 1. The garment silhouette and colour must not shift; only the material fidelity and micro-detail improve. Photorealistic, sharp, no text, no watermark.' \
  --images docs/material-enhancement/source-image.jpg docs/material-enhancement/hires-product.jpg \
  --size 1024x1536 --quality high --imageFormat jpeg \
  --save docs/material-enhancement/example-output.jpg

输出

example-output.jpg — 1024×1536，60 credits。麻花辫的立体起伏、菱形提花的凹凸、羊毛的绒毛感与褶皱处的暗部层次被重建；模特五官、发型、手部、姿势、棕色长裤、灰墙背景与整体色调保持不变，毛衣轮廓与军绿色未偏移。

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8、常见问题

现象	原因	处理
只是变锐利了	未要求重建结构	追加「这不是锐化」句，要求逐个线圈重建
人脸/背景也被改	未锁定区域	追加只允许服装区域变化句
颜色偏了	模型顺手调色	追加保色句
纹理密度不对（线圈太大/太小）	未给尺度参照	追加纹理尺度句
褶皱变平、没厚度	缺 AO 描述	追加加深褶皱暗部句
结构崩坏没被修好	超出能力	本技能只管表面，结构问题回到生成环节重跑

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Tips

Visit https://dlazy.com for more information.