服装细节放大图 Clothing Detail

服装图生成细节放大图。上传一张服装图，生成局部放大的细节特写图：领口罗纹、袖口、下摆、纽扣、拉链、刺绣、印花、织法结构、面料纤维等关键部位的微距特写，用于详情页证明材质与工艺。可指定服装类型，可用参考图或自定义提示词控制取景部位与拍摄风格，支持 1:1 / 3:4 生成比例。细节图的颜色、织法与结构严格沿用原图，只改变景别与景深。适用于详情页缺少细节图、没有微距镜头拍不出工艺特写、需要给每个 SKU 批量补 2-3 张细节图的场景。当用户需要「细节图」「细节放大图」「工艺特写」「面料微距」「局部放大」时使用本技能。

clothing-detail — 服装图生成细节放大图

一张服装图 → 局部微距特写。详情页里「证明这件衣服做得好」的那几张图。

为什么需要：转化率高的详情页通常有 2~3 张细节图（领口、袖口、面料纹理），但拍微距要专门的镜头和布光。本技能从常规商品图推出这些特写。

---

1、能力边界

能力	说明
取景部位	领口罗纹 / 袖口 / 下摆 / 纽扣 / 拉链 / 口袋 / 刺绣 / 印花 / 织法结构 / 面料纤维
风格控制	参考图（照抄某张细节图的机位与光线）或自定义提示词
服装类型	帮助模型判断哪些部位值得放大
生成比例	1:1（方图细节位）/ 3:4（竖版详情页）

不做：不改颜色、织法与结构；不添加原图没有的工艺（不存在的刺绣、不存在的拉链）；不虚构面料成分。

---

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

输入建议

做法	说明
✅ 原图分辨率越高越好	微距是在放大原图信息，原图糊 = 细节图编
✅ 目标部位在原图里清晰可见	原图里看不清的部位，输出的是模型的想象
✅ 一次只放大一个部位	一张图里塞三个特写等于都不清楚
❌ 低分辨率 / 强压缩图	会放大出塑料感的假纹理
❌ 目标部位被遮挡	挡住的工艺只能靠编

---

3、取景部位 → prompt 写法

部位	取景描述
领口罗纹	the ribbed crewneck collar meeting the body panel, showing rib wale spacing and the seam join
袖口	the ribbed cuff and the sleeve seam, showing rib elasticity and stitch density
下摆	the hem band and side seam, showing hem width and the finishing stitch
纽扣	a single button and its buttonhole, showing button material, thread cross and hole finishing
拉链	the zipper teeth and puller, showing tooth pitch, metal finish and the tape stitching
刺绣 / 印花	the [刺绣/印花] motif filling the frame, showing thread direction / print edge sharpness and substrate texture
织法结构	the [麻花/罗纹/提花] stitch structure, showing individual yarn plies and the twist of each loop
面料纤维	the fabric surface at extreme magnification, showing fibre halo and weave interlacing

每条都要补三件事：

text

filling the frame                      ← 特写要占满画面
shallow depth of field with the far edge softly out of focus   ← 微距的景深特征
soft directional light raking across the surface to reveal depth  ← 侧光才能显出立体纹理

---

4、dLazy 工具调用

本技能使用 dLazy 的 gpt-image-2（图像编辑模型 + --quality high；细节图的全部价值就是纹理保真度，这是本技能唯一不能省的地方）。

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]；带风格参考时 [原图, 参考图]	顺序即 prompt 中的 image 1 / 2
--size	1024x1024（方图细节位）/ 1024x1536（竖版详情页）	对应原站 1:1 / 3:4
--quality	high（不要降）	细节图靠纹理说话
--imageFormat	jpeg	通用格式
--batch	2	取景位置有随机性
--save	docs/clothing-detail/output-<sku>-<部位>.jpg	按部位归档

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/clothing-detail/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: 领口细节
dlazy gpt-image-2 \
  --prompt 'Macro detail shot for an e-commerce detail page. Zoom into the collar area of this garment and render a photorealistic close-up filling the frame. Show the ribbed crewneck collar meeting the body panel, individual yarn plies and the twist of each loop, soft directional light raking across the surface. Keep colour and stitch pattern exactly as in the source. Shallow depth of field, clean neutral background bokeh, no person, no text.' \
  --images docs/clothing-detail/garment-flatlay.jpg \
  --size 1024x1024 --quality high

# complex call: 一个 SKU 批量出 3 个部位的细节图
SRC=docs/clothing-detail/garment-flatlay.jpg
COMMON='Render a photorealistic macro close-up filling the frame. Keep the colour and stitch pattern exactly as in the source image. Shallow depth of field with the far edge softly out of focus, soft directional light raking across the surface to reveal depth, clean neutral background bokeh. No person, no text, no watermark.'
for P in collar cuff stitch; do
  case $P in
    collar) VIEW='Zoom into the collar area: the ribbed crewneck collar meeting the body panel, showing rib wale spacing and the seam join' ;;
    cuff)   VIEW='Zoom into the cuff area: the ribbed cuff and the sleeve seam, showing rib elasticity and stitch density' ;;
    stitch) VIEW='Zoom into the cable-knit panel: the stitch structure, showing individual yarn plies and the twist of each loop' ;;
  esac
  dlazy gpt-image-2 \
    --prompt "Macro detail shot for an e-commerce detail page. $VIEW. $COMMON" \
    --images "$SRC" --size 1024x1024 --quality high --imageFormat jpeg \
    --save "docs/clothing-detail/output-sku001-$P.jpg"
done

# 先估价不真跑
dlazy gpt-image-2 --dry-run --prompt '...' --images a.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.

---

5、Prompt 模板

text

Macro detail shot for an e-commerce detail page.

Zoom into [部位] of this [品类 + 颜色 + 面料] and render a photorealistic close-up
that fills the frame. Show [第三节表格里的取景描述].

Keep the colour and stitch pattern exactly as in the source.

Shallow depth of field with the far edge softly out of focus,
soft directional light raking across the surface to reveal depth,
clean neutral background bokeh.

No person, no text, no watermark.

按问题追加的修正句

问题	追加到 prompt 末尾
纹理像塑料	Resolve individual [yarn plies / weave threads / fibre ends]; the surface must read as real textile, not plastic or CG.
放大得不够	Extreme magnification: the [部位] must occupy at least 70% of the frame.
编出了不存在的工艺	Do not invent any construction detail that is not visible in the source image.
整张都很实、没有微距感	Only the [部位] is in focus; everything beyond [X] must fall into smooth bokeh.
颜色变了	Sample the colour directly from the source image; no grading, no saturation boost.

---

6、执行流程

1. 挑原图：分辨率越高越好；确认目标部位清晰可见、无遮挡。
2. 列部位清单：一个 SKU 通常出 2~3 张（领口 + 面料 + 一个特色工艺）。
3. 每条 prompt 只放大一个部位，从第三节取景描述抄。
4. 补齐三件事：占满画面 / 浅景深 / 侧光。
5. --quality high（不要降档）→ --batch 2 挑图，落盘到 docs/clothing-detail/。
6. 质检：纹理是否真实（不是塑料感）、有没有编出不存在的工艺、颜色是否一致。

---

7、生成效果示例

输入：服装图
garment-flatlay.jpg — 军绿麻花针织毛衣平铺图，800×800

实际执行的命令：

bash

dlazy gpt-image-2 \
  --prompt 'Macro detail shot for an e-commerce detail page. Zoom into the shoulder-and-collar area of this olive-green cable-knit sweater and render a photorealistic close-up that fills the frame. Show the ribbed crewneck collar meeting the raglan-style cable panel, individual yarn plies and the twist of the cable braid, the loft of the wool fibres, and soft directional light raking across the surface to reveal depth. Keep the colour and stitch pattern exactly as in the source. Shallow depth of field with the far edge softly out of focus, clean neutral background bokeh, no person, no text, no watermark.' \
  --images docs/clothing-detail/garment-flatlay.jpg \
  --size 1024x1024 --quality high --imageFormat jpeg \
  --save docs/clothing-detail/example-output.jpg

输出

example-output.jpg — 1024×1024，60 credits。领口罗纹与麻花panel的交接、每根纱线的捻向、羊毛纤维的绒毛感都被解析出来，侧光让菱形提花的凹凸立体可见，远端落入柔和虚化。

---

8、常见问题

现象	原因	处理
纹理塑料感	质量档位低或原图糊	--quality high + 追加解析纹理句；换高分辨率原图
放大不够，还是半身	未写占比	追加 70% 画面占比句
编出了原图没有的拉链/刺绣	模型补全	追加禁止编造句
没有微距景深	未写景深	追加只有目标部位对焦的句子
颜色比原图艳	自动调色	追加取色约束句
三个部位挤在一张图	一条 prompt 写了多个部位	拆成多条，一条一个部位

---

Tips

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