$2x2 网格，16:9，4 个著名城市 A = { 纸质地图层：卷曲边缘、撕裂区域、纤维、分层纸材 } B = { 城市群：$LANDMARK_A..E + 推断出的标志性配套建筑，街道网格，...$

PROMPT RECORD图像记录

2x2 网格，16:9，4 个著名城市 A = { 纸质地图层：卷曲边缘、撕裂区域、纤维、分层纸材 } B = { 城市群：$LANDMARK_A..E + 推断出的标志性配套建筑，街道网格，...

GPT-Image-2 Gdgtify Sun Jul 05 13:20:00 +0000 2026

2x2 grid, 16:9, 4 famous cities A = { paper map layer: curled edges, tear region, fibers, layered stock } B = { city cluster: $LANDMARK_A..E + inferred iconic supporting buildings, street grid, greenery, guardrails } C = { 3D wordmark: $ CITY, organic extrusion from sidewalks/plazas } D = { lighting rig: softboxes, rim, negative fill } E = { seamless white background }  SCENE = (A ∩ paper_physics) ∪ (B ∩ cityscape_model) ∪ (C ∩ typographic_terrain) ∪ (D ∩ illumination) ∪ (E) where: - B elements are arranged into a tight skyline via an attraction‑repulsion graph that maintains realistic scale cues. - The map tear is a subtraction (A \ intact_surface) with exposed paper layers as edge details. - Wordmark letters are grown from pedestrian paths using a diffusion‑limited aggregation from street network nodes. - Camera: 40mm equivalent, dynamic low angle with parallax between map and skyline. - Post: mild clarity, neutral white balance, shadow catcher. No neon.

2x2 网格，16:9，4 个著名城市 A = { 纸质地图层：卷曲边缘、撕裂区域、纤维、分层纸材 } B = { 城市群：$LANDMARK_A..E + 推断出的标志性配套建筑，街道网格，绿地，护栏 } C = { 3D 字标：$ CITY，从人行道/广场有机挤出成型 } D = { 灯光设备：柔光箱、轮廓光、负向补光 } E = { 无缝白色背景 } SCENE = (A ∩ 纸张物理) ∪ (B ∩ 城市景观模型) ∪ (C ∩ 字体地形) ∪ (D ∩ 照明) ∪ (E) 其中：- B 元素通过吸引‑排斥图排列成紧凑的天际线，保持真实比例线索。- 地图撕裂为减法操作 (A \ 完整表面)，并以暴露的纸层作为边缘细节。- 字标字母通过基于扩散限制聚集算法从街道网络节点沿行人路径生长。- 相机：等效 40...

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中文说明

2x2 网格，16:9，4 个著名城市 A = { 纸质地图层：卷曲边缘、撕裂区域、纤维、分层纸材 } B = { 城市群：$LANDMARK_A..E + 推断出的标志性配套建筑，街道网格，绿地，护栏 } C = { 3D 字标：$ CITY，从人行道/广场有机挤出成型 } D = { 灯光设备：柔光箱、轮廓光、负向补光 } E = { 无缝白色背景 } SCENE = (A ∩ 纸张物理) ∪ (B ∩ 城市景观模型) ∪ (C ∩ 字体地形) ∪ (D ∩ 照明) ∪ (E) 其中：- B 元素通过吸引‑排斥图排列成紧凑的天际线，保持真实比例线索。- 地图撕裂为减法操作 (A \ 完整表面)，并以暴露的纸层作为边缘细节。- 字标字母通过基于扩散限制聚集算法从街道网络节点沿行人路径生长。- 相机：等效 40...

原始 Prompt

2x2 grid, 16:9, 4 famous cities A = { paper map layer: curled edges, tear region, fibers, layered stock } B = { city cluster: $LANDMARK_A..E + inferred iconic supporting buildings, street grid, greenery, guardrails } C = { 3D wordmark: $ CITY, organic extrusion from sidewalks/plazas } D = { lighting rig: softboxes, rim, negative fill } E = { seamless white background }  SCENE = (A ∩ paper_physics) ∪ (B ∩ cityscape_model) ∪ (C ∩ typographic_terrain) ∪ (D ∩ illumination) ∪ (E) where: - B elements are arranged into a tight skyline via an attraction‑repulsion graph that maintains realistic scale cues. - The map tear is a subtraction (A \ intact_surface) with exposed paper layers as edge details. - Wordmark letters are grown from pedestrian paths using a diffusion‑limited aggregation from street network nodes. - Camera: 40mm equivalent, dynamic low angle with parallax between map and skyline. - Post: mild clarity, neutral white balance, shadow catcher. No neon.

广角暖色调仰视多分屏柔光画面文字城市景观城市或街道