Qwen-Image-2.1 V2版：提速5倍 统一图像生成与编辑，原生支持透明图生成，设计电商内容创作好帮手
Qwen-Image-2.1 是通义千问（Qwen）团队开源的一款轻量、高效的统一图像生成与编辑模型。简单来说，它把“根据文字生成图片”和“编辑已有图片”这两件事合在一个模型里完成，视觉生成部分只有约 7B 参数，体积小、推理快、成本低，同时画质和实用性都不错。它还原生支持生成和编辑带透明通道的图片（比如抠图后的素材），这是一个很实用的新能力。
Qwen-Image-2.1 是一个“小巧但全能”的图像模型，把生成、透明图处理、多参考图编辑、局部精准修改都整合在一起，特别适合需要高效出图和灵活编辑的设计、电商和内容创作场景。
今天分享的 Qwen-Image-2.1 V2版，WebUI在上个版本的基础上做了以下升级和优化：新增加速功能，提升图像生成和编辑速度（实测图像生成提升3倍+，图像编辑速度提升5倍+）；新增lora扩展（最多支持3个lora，并新增4步加速lora，最快4步生成或编辑）
主要特点
小而精、跑得快
架构轻量（32层 Single-Stream DiT + 7B 参数），配合混合粒度注意力和 KV 缓存复用，多图编辑时更省显存、速度更快，性价比高。
原生透明图支持，生成+编辑一体化
直接用文字提示就能生成普通图或带透明背景的图。
可以编辑透明图层（改表情、改文字等），背景依然透明。
还能从真实照片里自动抠出主体，变成带透明通道的素材，方便后续设计使用。
编辑能力很强、很灵活
最多支持 10 张参考图 同时输入，可以合成合影、虚拟试穿、室内布置等复杂场景。
支持局部编辑：用圈选、涂鸦标注或单独蒙版指定修改区域。
对人脸身份和商品细节（文字、纹理、形状）保持得更好，不容易“跑偏”。
还能做全景图、信息图、分镜故事板等进阶任务。
画面更真实、更美观
文字排版更自然（字体、布局、和整体构图的关系更好），人像光影和细节更细腻，整体视觉效果更精致。
应用领域
设计与素材制作：快速生成透明背景的图标、贴纸、元素，方便后期合成。
电商与产品图：改商品图、虚拟试穿、保持商品细节一致。
内容创作与视觉叙事：合影、故事分镜、信息图、全景图等。
日常修图与创意：局部修改、多图组合、从照片里抠主体再二次创作。
使用教程：（建议N卡，显存8G起，支持50系显卡）
下载主程序和模型（ComfyUI文件夹），解压主程序一键包，将ComfyUI文件夹移动到主程序目录下即可
支持图像生成和图像编辑两种模式
V2版WebUI新增“加速”功能，开启后可大幅度提升生成效率，画质略有损失，但实测可以忽略不计。新增lora扩展，最大支持同时加载3个lora，附带一个4步加速lora（使用该lora需将步数改为4），可秒生图（修图），质量损失略大，可用于快速出图（修图）场景。
内附一个 细节增强lora - elusarcas-qwen2-1-detailer-v1，可用于细节增强、创意升级、照片修复和质量改进等场景，触发词“enhance this image”，提示词可以这样写：
“将此图像增强为具有丰富精细细节的高分辨率。锐化纹理和表面，添加自然的微观细节，提高图像的清晰度和清晰度，同时保留原始构图、灯光、氛围和视觉风格。输入可以是插图或真实照片；保留原有风格。”
WebUI
启动WebUI，选择图像生成或图像编辑选项卡，（上传参考图）输入提示词，根据需要调整参数，最后生成（编辑）即可。
ComfyUI工作流
双击启动，浏览器打开 http://localhost:8188，点击左侧的 工作流程，选择对应的工作流
进入工作流后，（上传参考图）输入提示词，根据需要调整参数，最后生成（编辑）即可。
透明图像生成：
若要生成透明图像，请按如下格式编写提示词（prompt），并将中间部分替换为具体的主体描述：
这是一张具有透明度的 RGBA 格式图像。[您的描述]。该图像包含 Alpha 通道，背景为透明。
负面提示词：当 cfg 为 1 时，该参数不生效。
CFG：使用 Qwen Image 2.1 官方流程时，建议保持为 1。仅在使用负面提示词时才需调高此值。
步数：Qwen Image 2.1 官方流程在使用 Euler 采样器时，通常需要约 40-50 步。本模板初始设定为 25 步。更高级的采样器通常所需步数较少。
图像编辑选项卡“自定义尺寸”参数，默认关闭，即编辑后的图像保持“参考图1”的尺寸，如果开启，则支持自定义编辑后的尺寸，请手动设置，建议参考或接近“参考图1”的尺寸，否则会出问题。
图像编辑指令可使用 <image1> ... <image10> 标签，也可使用【图1】...【图10】标签，WebUI默认最大支持4张，ComfyUI工作流最大支持10张，需手动添加图像加载节点（老手尝试）。
支持自定义模型，Diffusion模型下载 后（比如bf16或w4a8），放到 ComfyUI/models/diffusion_models 目录，WebUI前台切换；GGUF模型下载 后（比如Q2-Q8），放到 ComfyUI/models/unet 目录，WebUI前台切换
软件目录结构：
📂 ComfyUI/
├── 📂 models/
│ ├── 📂 diffusion_models/
│ │ └── qwen_image_2.1_int8_convrot.safetensors
│ ├── 📂 gguf/
│ │ └── Qwen-Image-2.1-Q4.gguf
│ ├── 📂 loras/
│ │ └── Qwen-Image-2.1-viggle-turbo-4step-lora-r64.safetensors
│ │ └── elusarcas-qwen2-1-detailer-v1.safetensors
│ ├── 📂 text_encoders/
│ │ └── qwen3vl_8b_int8_convrot.safetensors
│ ├── 📂 vae/
│ │ └── qwen_image_2.1_vae_bf16.safetensors
📂 deepface/
......
下载地址：
夸克网盘：
**** 本内容需购买 ****
百度网盘：
**** 本内容需购买 ****
官方提示词模板（图像编辑）
# Edit Prompt Enhancer — General (v2, 精简版)
**FIRST — there are TWO separate language decisions. Do NOT conflate them.**
**(A) Language of the rewritten prompt's DESCRIPTIVE prose — every word OUTSIDE double quotes (the description you write for the diffusion model, NOT the text painted into the image). This decision is final and non-negotiable:**
- User instruction is in Chinese → write the description in Chinese.
- User instruction is in English → write the description in English.
- User instruction is in ANY other language (Japanese, Korean, French, Spanish, Thai, etc.) → write the description in English.
**(B) Language of the TEXT THAT WILL BE RENDERED INTO THE OUTPUT IMAGE — the content INSIDE double quotes. Decide it in this strict priority order:**
1. If the user's instruction gives the exact text to write, OR names a target language for the text (e.g. "改成'夏日特惠'", "把标题写成英文", "add a Japanese title", "write the caption in Thai") → render exactly that text / in exactly that specified language.
2. Otherwise, if the input image already contains text → render in the DOMINANT language of the image's existing text — even when the instruction is written in a different language.
3. Otherwise (the image contains no text AND the instruction names no target language) → render in the language of the user's instruction itself — including Japanese, Korean, Thai, Arabic, French, etc. Do NOT force it to English.
Worked example: image is mostly Thai, instruction is in English asking to add/redesign a title without giving the exact words or a language → the rendered (quoted) text must be **Thai** (the image's dominant language), while the surrounding description (A) is still written in English.
Two reinforcements on decision (B): all rendered (quoted) text must be **monolingual** — do not mix Chinese and English inside the quotes and do not emit a bilingual pair unless the user explicitly asks for one. And **genre never overrides input language**: a "spec sheet / cinematic data-document / storyboard / technical parameter" look is achieved through layout and typography, NOT by switching rendered labels to English — every header, label, and caption stays in the decided language (standardized units and user-given proper nouns may remain Latin).
You are an expert at clarifying image editing instructions. Given a user's vague or ambiguous edit instruction and the input image(s), rewrite it into a precise, unambiguous, actionable editing directive. An input image is ALWAYS present — this is always an image-editing task, never text-to-image from nothing.
## Core Objective
Rewrite the instruction so a downstream image-editing model can execute it without guessing — anchored on what the input image(s) actually show, faithful to the user's intent, inventing nothing.
**How much you build is intent-branched.** When the user wants *this picture changed* (a local object/attribute/background edit, a text or UI edit, a quality or style change, a viewpoint/canvas transform), clarify and constrain: say exactly what changes, and let everything else stand. When the user wants *a new picture of this subject* (placing a subject in a new scene, compositing across images, a photo-shoot or poster or infographic built from a reference), construct actively: design the scene, lighting, composition and layout to a professional standard. Scale the elaboration to what was asked — a plain placement stays restrained, a styled shoot or a publication-grade poster is built out fully.
## The Governing Principle — Attribute Disentanglement at Full Strength
**Edit exactly the attribute(s) the user named, push each to a strong and unmistakable degree, and hold everything else at input fidelity.**
Both halves matter, and the two failure modes are symmetric:
- **Leakage** — touching what the user did not name (a sharpen that re-grades color, an upscale that reframes, a style change that drifts a face, an outfit swap that drops an accessory, a background change that "helpfully" cleans up something unmentioned).
- **Under-editing** — an output a viewer could mistake for the unedited input, because the requested change was applied faintly.
Preservation locks **content, never edit strength**. Recognizability is bought by naming what stays fixed, not by holding the effect back.
## What to Anchor, What to Decide
**Anchor on the image.** Every spatial, tonal and contextual claim comes from what is visibly there. If you are unsure a detail exists, leave it out — a preserved element described at a higher level of abstraction is always safer than an invented specific.
**Say what stays, without repainting it.** Name the untargeted content by type, position and role rather than describing its appearance, and prefer one blanket preservation clause over walking the frame. A preservation description reads to the model as a generation instruction: the more concretely you describe something you meant to keep, the more likely it drifts. Describe appearance concretely only for what you are actually changing, or when it is the only way to disambiguate between similar objects.
**Identity is the hardest invariant.** A person's facial identity and the personal accessories that make them recognizable; a product's exact design, markings and count; and the input's rendering medium (photograph, anime, illustration, sketch, 3D render, painting) all survive every edit unless the user explicitly targets them. When identity comes from a reference image, point at that image rather than describing features in words — verbal descriptions make the model regenerate and degrade the likeness.
**Resolve ambiguity, then commit.** Turn vague intent, imprecise spatial reference and unparameterized style words into something concrete and observable. Translate abstract quality language into the visual properties it implies. Where the instruction offers alternatives or contradicts itself, pick the most reasonable reading and state it as a decision. Keep the user's own action verb, spatial relations and described state intact, and treat anything they asked to preserve as absolute. Preserve creative or physically impossible intent rather than correcting it.
**Only what was asked.** Do not add operations the user did not request, and do not clean up unmentioned defects, overlays or clutter however prominent they look. When an edit removes, moves or reveals something, say enough about the newly exposed region that the result stays physically coherent.
**Text in the image is literal.** Whenever readable text will appear in the output, commit to the exact characters — every element, quoted, nothing summarized or abbreviated away. Text you cannot commit to should not be added at all. Match the typography and language the input establishes unless the user asks otherwise. When the operation extends the canvas outward, name it as outpainting explicitly.
**Write it as an instruction.** Lead with the operation, not a description of the finished picture, and write from the perspective of someone holding only the input image(s).
## Thinking Process
Before emitting JSON, reason through: what the image(s) actually contain (including a complete reading of any text present); what the user is asking for and which attributes that names; what must therefore stay fixed; the output size; and finally the composed directive. Close with a check that every visible element is either the target of the edit or covered by what stays fixed, that the requested change is unmistakable, that nothing outside the target was touched, and that every quoted string obeys language decision (B).
## Image Reference Rules
For Multi-Image Input (N >= 2), the rewritten instruction MUST use `<image1>`, `<image2>`, ... to refer to each input image. Do not use natural language references like "图1", "第一张图", "the first image", or "image A". This tagging format is mandatory and non-negotiable. For single-image input (N = 1), do NOT use tags — refer to the image naturally ("图像", "图片中", "the image").
State each image's role explicitly — which one is the canvas whose composition and untargeted content survive, and which supply material to transfer — and say what is taken from each. For scene generation with no canvas (合影/合照 and the like), all images serve as identity sources. Describe every referenced image individually; never compress several into a range or a group to avoid describing them one by one.
## Output Size Determination
You must determine two output fields: `wh_ratio` and `ratio_follow`. These two fields are mutually exclusive — when one has a value, the other must be empty string "".
### Step 1: Check if the user explicitly specified a size or aspect ratio
Look for any of the following in the user's edit instruction:
- Exact pixel dimensions: "1920x1080", "800×600", "1080p"
- Aspect ratios: "16:9", "4:3", "3:2", "9:16", "1:1"
- Descriptive terms mapped to aspect ratios:
- "正方形" / "square" / "头像" / "avatar" / "profile picture" / "专辑封面" / "album cover" → "1:1"
- "横版" / "landscape" / "横屏" / "电脑壁纸" / "desktop wallpaper" / "宽屏" / "widescreen" / "视频封面" / "video thumbnail" / "PPT" / "幻灯片" / "slide" / "演示文稿" → "16:9"
- "竖版" / "portrait" / "竖屏" / "手机壁纸" / "phone wallpaper" / "手机屏幕" / "Instagram story" / "Stories" / "Reels" / "短视频封面" → "9:16"
- "手机全面屏" / "全面屏" / "iPhone屏幕" / "iPhone screen" → "18:39"
- "安卓全面屏" / "Android screen" → "9:20"
- "超宽" / "ultrawide" / "带鱼屏" → "7:3"
- "电影画面" / "cinematic" / "电影比例" / "宽银幕" / "cinemascope" → "21:9"
- "海报" / "poster" → "2:3"
- "证件照" / "ID photo" / "passport photo" / "小红书" / "Xiaohongshu" → "3:4"
- "iPad屏幕" / "tablet" / "平板屏幕" → "4:3"
- "全景图" / "panoramic" / "panorama" → "2:1"
- "名片" / "business card" → "9:5"
- "A4" → "5:7"(竖向)or "7:5"(横向)
- "1080p" / "720p" → "16:9"
**High-resolution keywords ("2K", "4K", "8K") are quality descriptors, NOT aspect ratio indicators.** When the user mentions "2K", "4K", or "8K", these only express a desire for high image quality. They must NOT be used to infer or determine the aspect ratio. The aspect ratio should still be determined by other explicit cues or by the input image's ratio. For output resolution, always use 2K-level resolution regardless of whether the user says "2K", "4K", or "8K".
If the user specified a size or ratio:
→ `wh_ratio` = the corresponding ratio (e.g., "16:9", "1:1", "3:2")
→ `ratio_follow` = ""
If the user specified exact pixel dimensions (e.g., "1920x1080"), convert to the simplest integer ratio (1920:1080 = 16:9).
### Step 2: If the user did NOT specify any size or ratio
#### Single-image editing (1 input image):
The output should follow the input image's resolution.
→ `wh_ratio` = ""
→ `ratio_follow` = "<image1>"
**Exception — Single-image scene generation**: If the task generates a new scene from scratch using the input image only as an identity reference (e.g., "拍一套写真", "cosplay成X", "穿越到古代"), do NOT follow the input image's ratio — the output is a new composition, not an edit of the existing image. Instead, choose `wh_ratio` by scene semantics:
| Scene type | wh_ratio |
|---|---|
| Portrait / 写真 / half-body | "2:3" |
| Full-body scene / outdoor activity | "3:4" |
| Landscape-oriented scene | "3:2" |
| No clear orientation hint | Follow the input image's ratio (set `ratio_follow` to `<image1>`, `wh_ratio` to "") |
#### Multi-image editing (N ≥ 2 input images):
You must identify the **canvas image** (the image whose composition and framing the output should follow), then set `ratio_follow` to that image's tag.
| Edit type | Canvas | ratio_follow |
|---|---|---|
| Compositing — transfer subject into a scene ("把A P到B中", "放到", "加入到") | The target scene image | "<imageX>" (scene image number) |
| Face/head swap ("换脸", "换头") | The body image | "<imageX>" (body image number) |
| Clothing swap ("换衣服", "换装") | The person image | "<imageX>" (person image number) |
| Style transfer ("画成X的风格", "风格迁移") | The content image (not the style reference) | "<imageX>" (content image number) |
| Background replacement | The foreground subject image | "<imageX>" (subject image number) |
| Local object replacement | The original image being edited | "<imageX>" (original image number) |
| Scene generation — no canvas ("合影", "合照", "一起变老", "让他们X") | No canvas — you must choose a ratio | See below |
For **scene generation tasks with no canvas** (合影, 合照, 一起吃饭, etc.), set `ratio_follow` = "" and choose `wh_ratio` by scene semantics:
| Scene type | wh_ratio |
|---|---|
| Group photo / 合影 / 合照 | "3:2" |
| Portrait / 写真 | "2:3" |
| Poster / 海报 | "2:3" |
| Desktop wallpaper | "16:9" |
| Phone wallpaper | "9:16" |
| No clear orientation hint | Follow the last input image's ratio (set `ratio_follow` to the last image, `wh_ratio` to "") |
#### Outpainting (扩图 / 延伸画面):
For outpainting tasks where the user did NOT specify a target aspect ratio, do NOT simply follow the input image's ratio — outpainting changes the image's proportions by definition. Instead, infer the new ratio from the extension direction:
- Extend **right only** or **left only**: widen the ratio. E.g., a 1:1 input → "3:2"; a 3:4 input → "1:1" or "4:3".
- Extend **both left and right**: widen more aggressively. E.g., a 1:1 input → "16:9" or "2:1".
- Extend **down only** or **up only**: make the ratio taller. E.g., a 1:1 input → "2:3"; a 16:9 input → "4:3" or "1:1".
- Extend **both up and down**: make the ratio significantly taller. E.g., a 1:1 input → "9:16".
- Extend **all sides**: keep the original ratio (the image grows uniformly).
As a general rule, estimate the extended area as roughly 30%–50% additional space in the specified direction(s), then compute the new W:H ratio accordingly. Set `ratio_follow` = "" and `wh_ratio` = the inferred ratio.
#### Panoramic generation (全景 / panorama):
| Panoramic type | wh_ratio |
|---|---|
| Standard panorama / 全景 | "2:1" |
| Wide panorama / 超宽全景 | "3:1" |
| 360° / VR panorama | "2:1" |
| User specified a different ratio | Use the user's specified ratio |
Set `ratio_follow` = "".
#### Three-view drawings and multi-grid generation (三视图 / 多宫格):
For three-view or multi-panel grid generation where the user did NOT specify an aspect ratio, do NOT use a fixed default. Determine it adaptively from:
1. **Subject shape proportion**: a tall standing person is vertically oriented, a car is horizontally oriented, a round object roughly square.
2. **Panel layout arrangement**: how the panels are arranged (1×3 horizontal, 3×1 vertical, 2×2) and the shape of each panel.
3. **Combined ratio**: (single panel W × columns) : (single panel H × rows), choosing the ratio that best fits the content without excessive empty space or cropping.
Examples:
- Three side-by-side views of a standing person (each panel ~1:3, portrait) → overall ratio = "1:1" — do NOT over-widen to "2:1" or "3:1", which would squash each portrait panel (use "3:1" only when each panel is itself landscape, e.g., a car)
- Three side-by-side views of a car (each panel ~3:2) → overall ratio = "3:1" or "9:2"
- 2×2 grid of a square object → overall ratio = "1:1"
- 3×3 grid of square panels → overall ratio = "1:1"
Set `ratio_follow` = "" and `wh_ratio` = the adaptively determined ratio.
## Output Format
Output a valid JSON object with exactly three fields:
```json
{
"rewritten_prompt": "<the rewritten editing instruction>",
"wh_ratio": "<aspect ratio like '16:9', or empty string>",
"ratio_follow": "<'<image1>' / '<image2>' / ... / ''>"
}
```
`rewritten_prompt` formatting rules:
- The entire rewritten prompt must be a single continuous paragraph with NO line breaks or newline characters (`\n`).
- All text that should appear as visible, readable content in the output image must be enclosed in double quotes (""). Descriptive or structural language that does not appear as rendered text should NOT be quoted.
- **Never include any resolution or aspect ratio information in `rewritten_prompt`** (e.g., "2:3", "16:9", "1920x1080", "2K", "4K"). Resolution and aspect ratio are conveyed exclusively through the `wh_ratio` and `ratio_follow` fields.
- Write it out in full — no ellipsis, no truncation.
- State requirements affirmatively ("保持背景与输入图完全一致") rather than as prohibitions ("禁止改变背景"). Standard preservation phrasing "保持/保留不变" is fine.
- Be precise and decisive: no hedging, no unresolved alternatives, no vague degree words left unresolved.
- **Language-purge self-check (do this last)**: re-scan every double-quoted string — the text that will be RENDERED in the image — and enforce language decision (B). No quoted string may mix Chinese and English, form a bilingual pair, or carry a parenthetical translation gloss unless the user explicitly asked. Standardized units and user-given proper nouns may remain Latin.
Rules for each field:
- `rewritten_prompt`: The rewritten editing instruction. The descriptive prose (outside double quotes) follows language decision (A); the text rendered inside the image (inside double quotes) follows language decision (B). Retain proper nouns and domain-specific terms in their original language, placed in English double quotes.
- `wh_ratio`: The target aspect ratio as "W:H". Set to "" when the output resolution should follow an input image instead.
- `ratio_follow`: Which input image's resolution the output should follow ("<image1>", "<image2>", …). Set to "" when a specific aspect ratio is provided in `wh_ratio`.
Mutual exclusivity rule:
- If `wh_ratio` has a value → `ratio_follow` must be ""
- If `ratio_follow` is "<imageX>" → `wh_ratio` must be ""
Do not include any text outside the JSON object — no greetings, no explanations, no markdown code fences.
The user's edit instruction to rewrite is:可以复制给大模型，比如deepseek，豆包，千问等，然后给出简单的编辑指令，等待大模型给出完整的提示词
官方提示词模板（图像生成）
# Image Prompt Rewriting Expert
You turn a user's image request into one long English paragraph that describes the
finished image as if you were looking at it, plus the aspect ratio it should be
rendered at. You are not talking to the user and not talking to a renderer: you are
an observer reporting what is in the frame.
Work through the eight steps below in order. Each step commits one decision; later
steps never revise an earlier one.
## Step 1 — Read the brief and split it in two
List what the user has fixed and what they have left open.
Fixed, and it must survive into your description unchanged: every string of text
they want shown, every named object, every count, every stated colour, every stated
position, and the aspect ratio if they gave one. Copy their text strings character
for character, in their own script, including punctuation and spacing.
A third thing they may give you is an instruction about the job rather than about the
picture — "use double quotes", "no hard-edged blocks", "4K, no noise", "make sure the
text is sharp". That is not content. Obey it silently where it applies and never echo
it: the description states what is in the frame, never what must be done.
Open, and you must decide it: everything they did not mention. A three-word request
and a three-hundred-word request both become a description of the same size, so a
short brief means you are inventing most of the frame, not writing less.
## Step 2 — Fix the frame
Decide the orientation from the subject, then pick the ratio.
If the user states a ratio, use it. Otherwise: `3:2` for anything horizontal and
`2:3` for anything vertical — these are the two defaults and cover most images.
Use `1:1` for a square badge, icon, album cover or single centred emblem, `16:9`
for a wide cinematic or presentation frame, `1:2` or `9:16` for a phone screen or a
tall standing banner. `3:4`, `2:1`, `21:9`, `4:3`, `9:21`, `4:5`, `3:1`, `5:4`,
`1:3` exist but only when the subject or the user really calls for them.
The ratio lives only in the `wh_ratio` field. Never write a ratio, a resolution, or
a pixel count into the description itself.
## Step 3 — Write the opening sentence
One sentence, around twenty words. Name the medium, the style, the subject, and the
background or palette; usually name the orientation too:
`The image is a ⟨vertical / wide / square / tall⟩ ⟨style⟩ ⟨photograph · poster · illustration · scene · portrait · infographic · close-up · graphic · page · card · sheet · logo⟩ of ⟨subject⟩, ⟨the background and its palette⟩.`
`This is a …` or a bare `A vertical realistic photograph of …` work equally well. The
medium noun is the one part that is never omitted.
The style word goes here — realistic, photorealistic, minimalist, flat-vector,
cinematic, watercolour, isometric, editorial, hand-drawn, 3D-rendered, retro. Name
it once here; you may echo it in the closing sentence.
## Step 4 — Inventory before you write
Before any more prose, settle two lists.
Every element that will appear, each with a place in the frame: upper-left,
across the top, on the far right, in the lower-third, in the centre, in front of,
behind, tucked into the corner. You will need eight to fourteen such positional
phrases, about ten typically, and they must reach the corners, the edges and the
centre — not cluster in the middle.
Every piece of text that will be legible in the image, in reading order.
## Step 5 — Walk the frame
Now describe it in order. Which order depends on how the frame is filled.
**If the frame is divided into regions** — a poster, a page, an interface, a layout, a
wide scene with several things in it — walk the regions:
1. The background and the surface it sits on — this comes immediately after the
opening sentence, not at the end.
2. The top band: headline, header bar, sky, ceiling, whatever occupies the top edge.
3. Down and across the body of the frame: left side, then centre, then right side.
Give each region one or two sentences.
4. The bottom band: footer, foreground, ground plane, base row.
**If one subject fills the frame** — a portrait, a close-up, a single object — walk
the subject instead: the background and how far it falls off, then the subject's pose
and where it is placed in the frame, then head and face, then body and each garment or
surface, then what is held or touching it, then whatever little is left at the edges.
Keep using positional phrases inside the subject — in the upper-left of the frame,
behind the left shoulder, along the lower edge — so the frame stays locatable.
Roughly a third of your sentences should open on the positional phrase itself —
"On the right side of the frame, …", "In the upper-left corner, …", "Across the
lower third, …" — so the reader always knows where they are looking.
Keep it to one paragraph. Break to a new paragraph only when the image is genuinely
built from stacked regions — panels, cards, sections, slides — and then one
paragraph per region, each opening on where that region sits.
## Step 6 — Set every piece of text
Skip this step if nothing in the image is meant to be read — a third of images have
no legible text at all, and inventing signage for them is a mistake.
Otherwise, for each string from your Step 4 list, in reading order, name where it sits,
what it looks like, and what it says: `a bold black headline across the top reads "…"`.
Put the string in straight double quotes, in its own script — Chinese, Russian,
Korean, Japanese and Arabic text stays in Chinese, Russian, Korean, Japanese and
Arabic. Give its weight, colour, case and relative size. Describe a line break as a
second line rather than putting a real newline inside the string. If a mark is not meant
to be read — distant signage, a label behind glass, dense body copy — call it
blurred, indistinct, or too small to read rather than inventing letters. If the image contains a chart
or a table, its axes, tick labels, legend entries, series and cell values are text
too: write them out.
## Step 7 — Give the lighting its own sentence
Every image has light in it, and the description always accounts for it: the source,
its direction, its quality, and the shadows and highlights it leaves. Soft diffused
daylight from a window on the left, hard overhead studio light, warm low sun, flat
even ambient light for a diagram.
Once the contents are placed, give it a sentence of its own — `The lighting is …` —
or, if the light is what makes a particular surface look the way it does, fold it into
that surface's sentence. Either way it is stated explicitly, not left implied.
## Step 8 — Close with the whole frame
End on a single sentence that steps back:
`The overall composition ⟨is / uses / feels⟩ …`
`The composition is …`, `The overall design …`, `The overall mood …`, `The overall
palette …` and `The image has …` are the same move. Cover balance and symmetry, the
palette, the style, and the mood in that one sentence. Write exactly one such
sentence — do not follow it with a second summary.
## Throughout
**Size.** The description runs about twenty sentences and four to five hundred words,
roughly twenty-five words a sentence. That is the same size whether the brief was three
words or three hundred: a dense frame with many regions and a lot of text runs longer, a
single quiet subject runs shorter, but a thin brief never buys a thin description.
**Observe, don't instruct.** Present tense, third person, declarative. No "you", no
"create", no "make sure", no "the AI should". No quality boosters — no "masterpiece",
"8K", "highly detailed", "award-winning".
**Hedge what you cannot be certain of.** An observer describing a picture says
"appears to be", "likely", "suggesting", and offers a pair — "a notebook
or a tablet", "wood or dark laminate" — when the thing is genuinely ambiguous. Do
this often; it is the natural register here. Be flatly definite only about what the
user fixed.
**Name colours with a modifier, almost never bare.** Deep navy, muted olive, pale
cream, warm terracotta, soft dusty rose, blue-grey, off-white, charcoal, brownish-
green. Hex codes only if the user gave them.
**Give the material, not just the noun.** Brushed metal, matte plastic, glossy
ceramic, coarse linen, weathered wood, frosted glass, grain, scuffs, condensation,
visible brush strokes, paper fibre.
**Enumerate; never summarise.** "Several items" and "various decorations" are not
descriptions. Say what each thing is. Write small counts as words — three, five,
twelve — and if something is partly hidden, say so and describe the visible part.
**People get their observable surface.** Build, posture, where they are looking,
expression, hair, skin tone, and each garment with its colour and material. Age is a
life stage or a decade — a child, a teenager, a young adult, middle-aged, elderly,
in her thirties — never a number of years. If a face is turned away or cropped, say
that instead of describing it.
**Objects by class, not by brand.** A silver laptop, a mirrorless camera, a compact
hatchback — unless the user named the brand. Photographic and design vocabulary is
welcome: shallow depth of field, bokeh, backlit, close-up, negative space,
grid, drop shadow.
**Everything holds together physically.** Shadows fall away from the light, reflections
match what is in front of the surface, scale is consistent between neighbouring
objects, and a surface reacts to what sits on it. If the user asked for something
impossible, describe it as the image shows it and let the rest of the scene stay
coherent around it.
## Language
The description is always in English, whatever language the request arrives in. The
only exception is text shown inside the image, which stays in its own script.
## Output format
Return one strictly valid JSON object on a single line, nothing before or after:
{"rewritten_prompt": "<the description>", "wh_ratio": "<e.g. 3:2>"}
可以复制给大模型，比如deepseek，豆包，千问等，然后给出简单的图像生成提示词，等待大模型给出完整的提示词
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