一键替换服装面料 Fabric on Body

一键替换服装面料。上传一张服装版式图（款式/版型参考）和一张面料图（面料小样、布料特写），在保留原版型的前提下把服装换成新面料，生成真实样衣效果图。可指定服装类型。版型、剪裁、领口袖口下摆结构、缝线位置与拍摄角度全部保持不变，只有材质与其对应的光泽、垂坠感、褶皱形态发生变化。适用于面料商与服装厂在打样之前预览样衣、一个版型快速铺出多种面料的 SKU、开发季前做面料选型对比，避免每种面料都实打一件样衣。当用户需要「换面料」「面料上身」「同一版型换布料」「面料替换样衣」「不打样先看效果」时使用本技能。

fabric-on-body — 一键替换服装面料

版型不动，面料换掉。给一张服装版式图 + 一张面料小样，输出这个版型用新面料做出来的样衣效果图。

价值在打样前：一个版型试 8 种面料，传统做法是打 8 件样衣（每件几天、几百块）；这里是 8 次生成。

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1、能力边界

输入	说明
服装版式图	决定版型、剪裁、结构与拍摄角度
面料图	决定材质、纹理、光泽与垂坠感（面料小样特写最佳）
服装类型	帮助模型理解结构（上装 / 下装 / 连衣裙 / 外套 / 内衣）

保持不变	会改变
版型与剪裁、身长袖长、领口/袖口/下摆结构、缝线位置、拍摄角度与构图	材质与织法、表面光泽、垂坠与褶皱形态、厚度观感

不做：不改版型比例；不改变服装的结构设计；不承诺真实打样的手感与克重——输出是视觉预览，不是工艺样衣。

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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

版式图（✅）：纯色背景、结构清晰、正面完整的平铺图或人台图。

面料图（✅）：面料小样特写，能看清织纹与光泽；有褶皱转折更好（能交代垂坠）。

会明显拉低效果的输入（❌）

问题	说明
面料图拍太远	看不清织纹，只会当成一块纯色
面料图带强环境色	黄光下拍的白布会换成米黄色
版式图有复杂印花	原印花会和新面料打架，先用 item-repair 或换素图
面料与品类不匹配	硬挺牛仔布做不出吊带裙的垂坠，模型会硬凑

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3、面料替换的关键：写清「材质带来的物理变化」

只说「换成真丝」不够——模型不知道该怎么改光影。要把材质翻译成可画出来的物理特征：

面料	要写的物理特征
真丝 / 缎面	lustrous specular highlights along the folds, fluid drape, soft continuous gradients
粗针织	chunky knit loops with visible yarn twist, matte fibre halo, structured heavy drape
牛仔	twill diagonal weave, slight slub texture, stiff drape with sharp fold creases
灯芯绒	vertical wale ridges catching light, matte pile, medium-stiff drape
雪纺	semi-sheer, very light drape with many fine ripples, soft diffused light through the fabric
皮革	low-frequency specular sheen, grain texture, stiff drape with broad soft creases
摇粒绒	dense short pile, fuzzy silhouette edge, no specular highlight

再加一句「版型不许动」——这是本技能最容易失守的地方：

text

Keep the pattern identical: same cut, same body length, same sleeve length,
same collar/cuff/hem construction, same flat-lay layout and camera angle.
Replace only the material.

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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；面料替换要求「几何完全不动、材质完全改变」，是典型的定向属性替换任务）。

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	[版式图, 面料图]	顺序即 prompt 中的 image 1 / 2
--size	与版式图比例一致（1024x1024 平铺 / 1024x1536 人台竖版）	换料不该改构图
--quality	high	材质是本技能的唯一产出，必须 high
--imageFormat	jpeg	通用格式
--batch	2 ~ 3	垂坠形态有随机性
--save	docs/fabric-on-body/output-<版型>-<面料>.jpg	版型 × 面料矩阵命名

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/fabric-on-body/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: 一个版型换一种面料
dlazy gpt-image-2 \
  --prompt 'Fabric replacement. Image 1 is the garment pattern reference, image 2 is the target fabric. Re-render the exact same garment silhouette from image 1 in the fabric from image 2. Keep the pattern identical: same cut, body length, sleeve length, collar/cuff/hem construction, layout and camera angle. Replace only the material. Clean white background, even studio light, no text.' \
  --images docs/fabric-on-body/style-sheet.jpg docs/fabric-on-body/fabric-swatch.jpg \
  --size 1024x1024 --quality high

# complex call: 一个版型 × 多种面料，跑成一个选型矩阵
STYLE=docs/fabric-on-body/style-sheet.jpg
KEEP='Keep the pattern identical: same oversized drop-shoulder cut, same body length, same sleeve length, same collar/cuff/hem construction, same flat-lay layout and camera angle. Replace only the material.'
for F in satin corduroy denim fleece; do
  case $F in
    satin)    PHYS='lustrous specular highlights along the folds, fluid drape, soft continuous gradients' ;;
    corduroy) PHYS='vertical wale ridges catching light, matte pile, medium-stiff drape' ;;
    denim)    PHYS='twill diagonal weave, slight slub texture, stiff drape with sharp fold creases' ;;
    fleece)   PHYS='dense short pile, fuzzy silhouette edge, no specular highlight' ;;
  esac
  dlazy gpt-image-2 \
    --prompt "Fabric replacement for a garment style sheet. Image 1 is the garment pattern/style reference. Image 2 is the target fabric. Re-render the exact same garment silhouette from image 1 in the fabric from image 2. $KEEP The garment must now read as $F: $PHYS. Clean white background, even studio light, no text." \
    --images "$STYLE" "docs/fabric-on-body/swatch-$F.jpg" \
    --size 1024x1024 --quality high --imageFormat jpeg \
    --save "docs/fabric-on-body/output-drop-shoulder-$F.jpg"
done

# 先估价不真跑
dlazy gpt-image-2 --dry-run --prompt '...' --images a.jpg b.jpg --size 1024x1024 --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

Fabric replacement for a garment style sheet.
Image 1 is the garment pattern/style reference: [品类 + 版型描述].
Image 2 is the target fabric: [面料名 + 颜色 + 光泽描述].

Re-render the exact same garment silhouette from image 1 in the fabric from image 2.

Keep the pattern identical: same [剪裁], same body length, same sleeve length,
same [领口/袖口/下摆结构], same [缝线位置], same layout and camera angle.

Replace only the material — the garment must now read as [面料名]:
[第三节表格里对应的物理特征].

Clean [背景色] background, even studio light, no text.

按问题追加的修正句

问题	追加到 prompt 末尾
版型跟着变了	The silhouette outline must be pixel-aligned with image 1. Only surface material may differ.
面料颜色偏了	Sample the fabric colour from image 2 under neutral light; do not shift hue or add colour cast.
换完还是原来的质感	把物理特征写得更极端，并追加 The original [原面料] texture must be completely gone.
垂坠不对	Drape stiffness: [very fluid / medium / stiff]. Fold count and fold radius must match a [面料] of about [克重] gsm.
缝线/罗纹消失了	Preserve construction details: [罗纹/明线/拉链] must remain visible in the new material.

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6、执行流程

1. 备素材：版式图（结构清晰、印花越少越好）+ 面料小样特写（能看清织纹）。
2. 翻译材质：查第三节表格，把面料名换成物理特征描述。
3. 写版型锁定句：剪裁 / 身长 / 袖长 / 领口袖口下摆 / 缝线 / 角度，逐项写死。
4. --quality high 起跑，比例跟随版式图。
5. 要做选型矩阵：用第四节循环，一个版型 × N 种面料。
6. 质检：版型轮廓是否与原图对齐、面料颜色是否准、质感是否真的换掉了、缝线罗纹是否还在。
7. 交付时注明这是视觉预览，不代表真实手感与克重。

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7、生成效果示例

输入：服装版式图	输入：面料图
style-sheet.jpg — 落肩宽松圆领毛衣版型，800×800	fabric-swatch.jpg — 象牙白真丝缎面小样，640×640

实际执行的命令：

bash

dlazy gpt-image-2 \
  --prompt 'Fabric replacement for a garment style sheet. Image 1 is the garment pattern/style reference: an oversized drop-shoulder crewneck sweater with ribbed collar, cuffs and hem. Image 2 is the target fabric: ivory silk satin with a soft lustrous sheen and fine weave. Re-render the exact same garment silhouette from image 1 in the fabric from image 2. Keep the pattern identical: same oversized drop-shoulder cut, same body length, same sleeve length, same collar/cuff/hem construction, same flat-lay layout and camera angle. Replace only the material — the sweater must now read as ivory silk satin with specular highlights on the folds and soft drape instead of chunky knit. Clean white background, even studio light, no text.' \
  --images docs/fabric-on-body/style-sheet.jpg docs/fabric-on-body/fabric-swatch.jpg \
  --size 1024x1024 --quality medium --imageFormat jpeg \
  --save docs/fabric-on-body/example-output.jpg

输出

example-output.jpg — 1024×1024。落肩剪裁、身长袖长、罗纹领口袖口下摆的结构与平铺角度都与版式图一致；材质从粗针织变成象牙白真丝缎面，褶皱上出现高光、垂坠变得柔顺，罗纹部位仍以缎面质感保留。

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8、常见问题

现象	原因	处理
版型变了	未锁定轮廓	追加 silhouette outline must be pixel-aligned with image 1
面料颜色不对	面料图带环境色	重拍面料小样（中性光），或追加取色约束句
质感没换掉	物理特征写得太弱	用第三节表格的极端描述 + original texture must be completely gone
垂坠像纸板	未指定垂坠刚度	追加 drape stiffness 句，给出克重参考
罗纹/明线消失	被新材质吞掉	追加保留结构细节句
面料与品类物理上不成立	硬挺布做垂坠款	换匹配的面料，或改版型

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Tips

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