一图裂变套图 Fission Pattern

一张商品图生成完整套图。上传一张商品图并描述商品名称与卖点，生成同一商品在不同角度、不同场景、不同构图下的一整套图（主图 + 场景图 + 细节图 + 使用图），用于填满电商主图位与详情页。两种模式：商品套图（同一商品多角度多场景）与姿势套图（同一模特同一穿搭多个姿势）。商品的外形、颜色、材质纹理与结构细节在整套图中保持一致，同时每张图的机位、景别、背景与光线各不相同。适用于只有一张商品图却要凑满 5 张主图位、快速铺满详情页、批量给多 SKU 出统一风格套图。当用户需要「一张图变多张」「出套图」「多角度商品图」「凑满主图位」「同一商品不同场景」时使用本技能。

fission-pattern — 一张图裂变完整套图

一张商品图 → 一整套不同角度 / 场景 / 构图的商拍图。

电商主图位通常要 5 张，详情页要十几张。本技能解决的是「只有一张图，要凑满一屏」的问题：同一件商品，多个机位与场景，视觉识别保持一致。

---

1、能力边界

模式	说明
商品套图	同一商品 → 正面主图 / 45 度图 / 场景使用图 / 细节微距图 / 尺寸对比图
姿势套图	同一模特同一穿搭 → 正面 / 侧面 / 背面 / 走动 / 坐姿

输入	说明
商品图	1 张，主视角最佳
商品名称	例：撞色长款风衣
商品卖点	例：100% 纯棉，轻盈舒适透气，法式复古撞色元素（用于决定场景与氛围）

不做：不改商品的外形、颜色、材质与结构；不编造商品没有的功能卖点；不生成虚假促销信息。

---

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
✅ 主视角 + 纯净背景	越干净，整套图的商品一致性越高
✅ 卖点写具体	防水防汗 会带出运动场景，法式复古 会带出咖啡馆场景
✅ 商品结构完整可见	套图里的细节图要靠这张图推断结构
❌ 已经带营销文字的图	文字会被复制到每张套图里，先用 remove-watermark 洗干净
❌ 商品被手/道具遮挡	遮住的部分在每张套图里都会不一样

---

3、套图配方：5 张主图位怎么排

把「一套图」拆成固定的镜位清单，每张一条 prompt，商品描述段完全复用，只换镜位段：

#	镜位	作用	镜位段示例
1	正面主图	搜索列表首图，要最清楚	straight-on hero shot filling the frame, clean seamless background, even studio light
2	45 度立体图	交代体积与厚度	45-degree three-quarter angle showing depth and side profile, soft gradient background
3	场景使用图	建立使用联想	in-use lifestyle shot: [场景 + 人物动作], warm window light, shallow depth of field
4	细节微距图	证明材质与工艺	macro close-up of [关键工艺部位] filling the frame, hard rim light, extreme detail
5	对比 / 内构图	交代尺寸或内部	[尺寸对比物 / 内部结构] shown alongside the product, top-down layout, neutral background

一致性的关键：三段结构里，第一段（商品保真描述）在 5 条 prompt 里逐字相同，只有第三段（镜位）在变。

text

[段1 商品保真：不变]  +  [段2 卖点氛围：不变]  +  [段3 镜位：每张不同]

---

4、卖点 → 场景的映射

卖点决定第 3 张场景图长什么样，别让模型自由发挥：

卖点类型	场景写法
保暖 / 加厚	snowy outdoor street, breath visible, cold blue ambient with warm rim light
透气 / 速干	gym or running track, dynamic mid-motion, bright daylight
防水 / 三防	rainy pavement with water droplets beading on the surface, overcast light
通勤 / 商务	office lobby or subway station, dark suit context, cool neutral light
法式 / 复古	French cafe interior, marble table, warm window light, film colour grading
亲肤 / 婴童	soft nursery bedding, pastel palette, very soft diffused light
精密 / 工艺	dark navy blueprint paper with a brass ruler, cool directional side light

姿势套图用的是另一组：正面站姿 / 侧身转头 / 背面回头 / 自然行走 / 坐姿——每条只换姿势段，模特与穿搭段逐字不变（写法可直接复用 creative-scene 的改姿势句式）。

---

5、dLazy 工具调用

本技能使用 dLazy 的 gpt-image-2（套图的核心指标是整套图里的商品是同一件，需要最强的参考图保真；实测低价模型在多场景切换时会漂移出另一款商品）。

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	[商品图]（全套 N 条命令都传同一张）	保证整套图的商品同源
--size	1024x1536 竖版套图；1024x1024 方图主图位	跟随平台主图规范
--quality	medium 场景图；high 细节微距图	微距图靠纹理说话
--imageFormat	jpeg	电商上架通用格式
--batch	1（套图靠多条 prompt，不靠 batch）	batch 只会给同一镜位多个版本
--save	docs/fission-pattern/output-<sku>-<序号>.jpg	按套编号归档

成本提示：想压成本可换 dlazy seedream-5.0（单张约 1/6 价）。代价是商品保真度下降——实测在场景切换时会漂移成另一款商品，只适合对商品一致性不敏感的氛围图。

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/fission-pattern/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: 套图第 1 张（正面主图）
dlazy gpt-image-2 \
  --prompt 'E-commerce product photography, set image 1 of 5 — hero front shot. The subject is the product in the reference image. Keep it 100% faithful: same shape, colour, material texture and structural details. Straight-on hero shot filling the frame, clean seamless background, even studio light. Photorealistic, no text, no watermark.' \
  --images docs/fission-pattern/product-watch.jpg \
  --size 1024x1536 --quality medium

# complex call: 用 shell 循环一次跑完整套 5 张
PRODUCT='a polished stainless-steel watch with a silver sunburst dial, applied baton markers and a black crocodile-embossed leather strap'
KEEP="Keep the product 100% faithful: same case shape and polish, same dial colour and marker layout, same hand shapes, same crown, same strap embossing and stitching."
i=0
for SHOT in \
  'straight-on hero shot filling the frame, clean seamless background, even studio light' \
  '45-degree three-quarter angle showing depth and side profile, soft gradient background' \
  'in-use lifestyle shot: worn on a man wrist beside a coffee cup on a wooden cafe table, warm window light, shallow depth of field' \
  'macro close-up of the dial edge, applied markers and knurled crown filling the frame, hard rim light, extreme detail' \
  'top-down flat layout beside a brass ruler for scale, dark navy blueprint paper, cool side light'
do
  i=$((i+1))
  dlazy gpt-image-2 \
    --prompt "E-commerce product photography, set image $i of 5. The subject is $PRODUCT from the reference image. $KEEP $SHOT. Photorealistic commercial product photography, no text, no watermark." \
    --images docs/fission-pattern/product-watch.jpg \
    --size 1024x1536 --quality medium --imageFormat jpeg \
    --save docs/fission-pattern/output-sku001-$i.jpg
done

# 先估价不真跑（乘以套图张数就是总价）
dlazy gpt-image-2 --dry-run --prompt '...' --images a.jpg --size 1024x1536

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.

---

6、Prompt 模板

三段结构，前两段整套复用，第三段每张不同：

text

E-commerce product photography, set image [N] of [总数].

【段1 · 商品保真，整套逐字相同】
The subject is [商品名称 + 颜色 + 材质] from the reference image.
Keep the product 100% faithful: same [外形], same [颜色], same [材质纹理],
same [结构细节：五金/缝线/图案/logo 位置] — it must be recognisably the identical product
across the whole set.

【段2 · 卖点氛围，整套逐字相同】
[从第四节表格取对应的氛围与色调描述]

【段3 · 镜位，每张不同】
[从第三节表格取镜位描述]

Photorealistic commercial product photography, no text, no watermark.

按问题追加的修正句

问题	追加到 prompt 末尾
套图里像两件不同商品	Cross-check against the reference image: [关键识别特征] must match exactly. Any deviation is a failure.
场景抢了商品的戏	The product must occupy at least 40% of the frame and be the sharpest element; keep the environment subordinate and softly defocused.
整套色调不统一	Grade the whole set consistently: [色温 + 对比度描述].
细节图糊	改 --quality high，并追加 resolve individual [纹理单位：yarn plies / gear teeth / leather pores]

---

7、执行流程

1. 洗干净输入：商品图上如有营销文字，先走 remove-watermark。
2. 写商品保真段：把商品的关键识别特征列全（外形 / 颜色 / 材质 / 五金 / 缝线 / logo 位置）——这段整套复用。
3. 卖点 → 氛围段：查第四节表格，把卖点翻译成场景与色调，整套复用。
4. 列镜位清单：查第三节，按平台主图位数量取 5 条（或详情页取 8~12 条）。
5. 循环跑：用第四节的 shell 循环，每条只换镜位段。
6. 质检整套：把 N 张图并排看——商品是不是同一件？色调是否统一？有没有哪张场景抢戏？
7. 不合格的单张重跑，不用整套重来。

---

8、生成效果示例

输入：商品图
product-watch.jpg — 黑色鳄鱼纹皮带钢壳银色太阳纹表盘手表

实际执行的命令（套图第 2 张，其余两张只换第三段镜位）：

bash

dlazy gpt-image-2 \
  --prompt 'E-commerce product photography, set image 2 of 3 — in-use lifestyle shot. The subject is the watch from the reference image: a polished stainless-steel watch with a silver sunburst dial, applied baton markers and a black crocodile-embossed leather strap. Keep the product 100% faithful: same case shape and polish, same dial colour and marker layout, same hand shapes, same crown, same strap embossing and stitching — it must be recognisably the identical watch as the reference. Show it worn on a man wrist resting on a wooden cafe table beside a white coffee cup, dark suit sleeve and white shirt cuff visible, warm window light, shallow depth of field with a blurred cafe background. Photorealistic, no text, no watermark.' \
  --images docs/fission-pattern/product-watch.jpg \
  --size 1024x1536 --quality medium --imageFormat jpeg \
  --save docs/fission-pattern/example-output-2.jpg

输出：一套三张

1 · 正面主图	2 · 场景使用图	3 · 细节微距图
蓝图纸 + 黄铜直尺，冷调侧光	手腕佩戴 + 咖啡桌，暖色窗光	表盘/刻度/表冠微距，硬光勾边

三张的商品保真段逐字相同，只有镜位段在变。

---

9、常见问题

现象	原因	处理
套图里的商品明显不是同一件	商品保真段太笼统，或用了低保真模型	列全关键识别特征；换 gpt-image-2
每张色调都不一样	未统一氛围段	氛围段整套逐字相同，并追加统一调色句
场景太满，商品变小	场景描述比商品描述更长	追加 40% 画面占比约束句
细节图看不出材质	--quality medium	改 high 并写明要解析到的纹理单位
套图里出现了营销文字	输入图自带文字	先洗图；prompt 末尾保留 no text, no watermark
想出 12 张但成本太高	张数 × 单价	主图位 5 张用 gpt-image-2，详情页氛围图用 seedream-5.0 补量

---

Tips

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