wedding-immortalist
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ChineseWedding Immortalist
Wedding Immortalist
Transform wedding photos and video into an eternal, immersive 3D experience. Create living memories that let couples and guests relive the magic forever.
将婚礼照片和视频转换为永恒的沉浸式3D体验,打造鲜活的记忆,让新人与宾客能永远重温这份美好。
When to Use This Skill
何时使用本技能
Use for:
- Processing thousands of wedding photos into 3DGS scenes
- Creating theatre-mode experiences where ceremony/reception moments play in-place
- Building face-clustered guest rosters with best-photo selection
- Matching design aesthetics to wedding themes (disco, rustic, beach, modern, queer celebrations)
- AI-curated photo selection per guest with aesthetic scoring
NOT for:
- General photo editing → use native-app-designer
- Non-wedding 3DGS → use drone-inspection-specialist
- Event planning → not a wedding planner
- Video editing without 3D reconstruction
适用场景:
- 将数千张婚礼照片处理为3DGS场景
- 创建剧场模式体验,仪式/招待会的瞬间可在场景原位播放
- 构建带最佳照片筛选功能的人脸聚类宾客名册
- 匹配婚礼主题(迪斯科、乡村风、海滩风、现代风、酷儿庆典等)的设计美学
- 基于AI美学评分,为每位宾客精选照片
不适用场景:
- 普通照片编辑 → 请使用native-app-designer
- 非婚礼场景的3DGS处理 → 请使用drone-inspection-specialist
- 活动策划 → 本工具并非婚礼策划师
- 无3D重建需求的视频编辑
Core Pipeline
核心流程
┌─────────────────────────────────────────────────────────────────┐
│ WEDDING IMMORTALIST PIPELINE │
├─────────────────────────────────────────────────────────────────┤
│ │
│ 1. INGEST 2. RECONSTRUCT 3. CLUSTER │
│ ├─ Photos (1000s) ├─ COLMAP SfM ├─ Face detect │
│ ├─ Video (hours) ├─ 3DGS training ├─ Embeddings │
│ └─ Audio/speeches └─ Scene merge └─ Identity link │
│ │
│ 4. CURATE 5. DESIGN 6. PRESENT │
│ ├─ Aesthetic score ├─ Theme extract ├─ Web viewer │
│ ├─ Per-person best ├─ Color palette ├─ Theatre mode │
│ └─ Moment detect └─ Typography └─ Guest roster │
│ │
└─────────────────────────────────────────────────────────────────┘┌─────────────────────────────────────────────────────────────────┐
│ WEDDING IMMORTALIST PIPELINE │
├─────────────────────────────────────────────────────────────────┤
│ │
│ 1. INGEST 2. RECONSTRUCT 3. CLUSTER │
│ ├─ Photos (1000s) ├─ COLMAP SfM ├─ Face detect │
│ ├─ Video (hours) ├─ 3DGS training ├─ Embeddings │
│ └─ Audio/speeches └─ Scene merge └─ Identity link │
│ │
│ 4. CURATE 5. DESIGN 6. PRESENT │
│ ├─ Aesthetic score ├─ Theme extract ├─ Web viewer │
│ ├─ Per-person best ├─ Color palette ├─ Theatre mode │
│ └─ Moment detect └─ Typography └─ Guest roster │
│ │
└─────────────────────────────────────────────────────────────────┘Theme-Adaptive Design
主题自适应设计
Theme Detection & Matching
主题检测与匹配
Every wedding has a unique aesthetic. Extract and honor it:
| Theme Type | Color Palette | Typography | UI Elements |
|---|---|---|---|
| 70s Disco | Gold, orange, burnt sienna, deep purple | Groovy script, bold sans | Mirror balls, starbursts, warm gradients |
| Rustic/Barn | Earth tones, sage, cream, wood | Serif, hand-lettered | Burlap textures, wildflower accents |
| Beach/Coastal | Ocean blues, sand, coral, seafoam | Light sans, script | Shell motifs, wave patterns |
| Modern Minimal | Black, white, metallics | Clean geometric sans | Sharp lines, negative space |
| Queer Joy | Rainbow spectrums, bold colors | Expressive, varied | Pride elements, celebration maximalism |
| Cultural Fusion | Per tradition | Traditional + modern | Cultural motifs, heritage patterns |
每场婚礼都有独特的美学风格,我们会提取并遵循这种风格:
| 主题类型 | 配色方案 | 字体风格 | UI元素 |
|---|---|---|---|
| 70s Disco | 金色、橙色、焦赭色、深紫色 | 复古花体、粗体无衬线 | 镜面球、星爆图案、暖色调渐变 |
| Rustic/Barn(乡村/谷仓风) | 大地色系、鼠尾草绿、奶油白、木色 | 衬线体、手写风格 | 粗麻布纹理、野花装饰 |
| Beach/Coastal(海滩/海滨风) | 海洋蓝、沙色、珊瑚色、海沫绿 | 轻盈无衬线体、花体 | 贝壳元素、波浪图案 |
| Modern Minimal(现代极简风) | 黑、白、金属色 | 简洁几何无衬线体 | 锐利线条、留白设计 |
| Queer Joy(酷儿庆典风) | 全彩虹色系、大胆亮色 | 富有表现力的多元字体 | 骄傲元素、极致庆典风格 |
| Cultural Fusion(文化融合风) | 遵循传统配色 | 传统+现代结合 | 文化符号、传统纹样 |
Extracting Theme from Photos
从照片中提取主题
python
undefinedpython
undefinedTheme extraction signals
Theme extraction signals
THEME_SIGNALS = {
'color_palette': 'Dominant colors from venue, florals, attire',
'lighting_mood': 'Warm/cool, natural/dramatic, string lights/chandeliers',
'decor_elements': 'Rustic/modern/vintage/eclectic',
'attire_style': 'Traditional/non-traditional, formal/casual',
'cultural_markers': 'Religious symbols, cultural traditions',
'era_aesthetic': '70s disco, 20s gatsby, etc.'
}
undefinedTHEME_SIGNALS = {
'color_palette': 'Dominant colors from venue, florals, attire',
'lighting_mood': 'Warm/cool, natural/dramatic, string lights/chandeliers',
'decor_elements': 'Rustic/modern/vintage/eclectic',
'attire_style': 'Traditional/non-traditional, formal/casual',
'cultural_markers': 'Religious symbols, cultural traditions',
'era_aesthetic': '70s disco, 20s gatsby, etc.'
}
undefined3D Gaussian Splatting Pipeline
3D Gaussian Splatting流程
Photo/Video Ingestion
照片/视频导入
Optimal Input Strategy:
├── Video: Extract 2-3 fps (80% overlap minimum)
├── Photos: Include ALL photographer shots
├── Phone photos: Guest uploads (georeferenced bonus)
└── Coverage: Ceremony + reception + all spaces
Quality Thresholds:
├── Minimum images per space: 50-100
├── Overlap requirement: 60-80%
├── Blur rejection: Laplacian variance < 100 = skip
└── Exposure: Reject severe over/underexposureOptimal Input Strategy:
├── Video: Extract 2-3 fps (80% overlap minimum)
├── Photos: Include ALL photographer shots
├── Phone photos: Guest uploads (georeferenced bonus)
└── Coverage: Ceremony + reception + all spaces
Quality Thresholds:
├── Minimum images per space: 50-100
├── Overlap requirement: 60-80%
├── Blur rejection: Laplacian variance < 100 = skip
└── Exposure: Reject severe over/underexposureCOLMAP Structure from Motion
COLMAP运动结构恢复
bash
undefinedbash
undefinedFeature extraction
Feature extraction
colmap feature_extractor
--database_path database.db
--image_path images/
--ImageReader.single_camera 0
--SiftExtraction.max_image_size 3200
--database_path database.db
--image_path images/
--ImageReader.single_camera 0
--SiftExtraction.max_image_size 3200
colmap feature_extractor
--database_path database.db
--image_path images/
--ImageReader.single_camera 0
--SiftExtraction.max_image_size 3200
--database_path database.db
--image_path images/
--ImageReader.single_camera 0
--SiftExtraction.max_image_size 3200
Exhaustive matching for comprehensive coverage
Exhaustive matching for comprehensive coverage
colmap exhaustive_matcher
--database_path database.db
--SiftMatching.guided_matching 1
--database_path database.db
--SiftMatching.guided_matching 1
colmap exhaustive_matcher
--database_path database.db
--SiftMatching.guided_matching 1
--database_path database.db
--SiftMatching.guided_matching 1
Sparse reconstruction
Sparse reconstruction
colmap mapper
--database_path database.db
--image_path images/
--output_path sparse/
--database_path database.db
--image_path images/
--output_path sparse/
colmap mapper
--database_path database.db
--image_path images/
--output_path sparse/
--database_path database.db
--image_path images/
--output_path sparse/
Dense reconstruction (optional, for mesh)
Dense reconstruction (optional, for mesh)
colmap image_undistorter ...
colmap patch_match_stereo ...
undefinedcolmap image_undistorter ...
colmap patch_match_stereo ...
undefined3DGS Training
3DGS训练
python
undefinedpython
undefinedWedding-optimized 3DGS settings
Wedding-optimized 3DGS settings
WEDDING_3DGS_CONFIG = {
'iterations': 50_000, # High quality for permanent archive
'densify_from_iter': 500,
'densify_until_iter': 15_000,
'densification_interval': 100,
'opacity_reset_interval': 3000,
'sh_degree': 3, # Full spherical harmonics for lighting
'percent_dense': 0.01,
'densify_grad_threshold': 0.0002,
}
WEDDING_3DGS_CONFIG = {
'iterations': 50_000, # High quality for permanent archive
'densify_from_iter': 500,
'densify_until_iter': 15_000,
'densification_interval': 100,
'opacity_reset_interval': 3000,
'sh_degree': 3, # Full spherical harmonics for lighting
'percent_dense': 0.01,
'densify_grad_threshold': 0.0002,
}
Multi-space merge strategy
Multi-space merge strategy
SPACES = ['ceremony', 'cocktail_hour', 'reception', 'photo_booth', 'dance_floor']
SPACES = ['ceremony', 'cocktail_hour', 'reception', 'photo_booth', 'dance_floor']
Train each separately, then create unified navigation
Train each separately, then create unified navigation
undefinedundefinedFace Clustering System
人脸聚类系统
Pipeline
流程
┌────────────────────────────────────────────────────────┐
│ FACE CLUSTERING PIPELINE │
├────────────────────────────────────────────────────────┤
│ 1. Detection (RetinaFace/MTCNN) │
│ └─ All faces in all photos │
│ 2. Alignment (5-point landmark) │
│ └─ Standardize for embedding │
│ 3. Embedding (ArcFace/AdaFace) │
│ └─ 512-dim identity vector per face │
│ 4. Clustering (HDBSCAN) │
│ └─ Group by identity, handle edge cases │
│ 5. Identity Linking │
│ └─ Match to couple, wedding party, family, guests │
│ 6. Best Photo Selection │
│ └─ Aesthetic scoring per cluster │
└────────────────────────────────────────────────────────┘┌────────────────────────────────────────────────────────┐
│ FACE CLUSTERING PIPELINE │
├────────────────────────────────────────────────────────┤
│ 1. Detection (RetinaFace/MTCNN) │
│ └─ All faces in all photos │
│ 2. Alignment (5-point landmark) │
│ └─ Standardize for embedding │
│ 3. Embedding (ArcFace/AdaFace) │
│ └─ 512-dim identity vector per face │
│ 4. Clustering (HDBSCAN) │
│ └─ Group by identity, handle edge cases │
│ 5. Identity Linking │
│ └─ Match to couple, wedding party, family, guests │
│ 6. Best Photo Selection │
│ └─ Aesthetic scoring per cluster │
└────────────────────────────────────────────────────────┘Clustering Parameters
聚类参数
python
CLUSTERING_CONFIG = {
'min_cluster_size': 3, # At least 3 photos to form identity
'min_samples': 2,
'metric': 'cosine',
'cluster_selection_epsilon': 0.3,
'cluster_selection_method': 'eom',
}python
CLUSTERING_CONFIG = {
'min_cluster_size': 3, # At least 3 photos to form identity
'min_samples': 2,
'metric': 'cosine',
'cluster_selection_epsilon': 0.3,
'cluster_selection_method': 'eom',
}Identity priority for naming
Identity priority for naming
IDENTITY_PRIORITY = [
'couple_1', 'couple_2', # The married couple
'wedding_party', # Bridesmaids, groomspeople
'parents', # Parents of the couple
'grandparents',
'siblings',
'extended_family',
'friends',
'vendors', # Photographer, DJ, etc.
]
undefinedIDENTITY_PRIORITY = [
'couple_1', 'couple_2', # The married couple
'wedding_party', # Bridesmaids, groomspeople
'parents', # Parents of the couple
'grandparents',
'siblings',
'extended_family',
'friends',
'vendors', # Photographer, DJ, etc.
]
undefinedIdentity Linking Workflow
身份关联工作流
- Couple identification: User tags couple in 2-3 photos
- Wedding party: User identifies key people
- Auto-propagation: Embeddings match across all photos
- Guest matching: Optional guest list import for name assignment
- Manual corrections: UI for fixing mismatches
- 新人识别:用户在2-3张照片中标记新人
- 婚礼团队识别:用户标记关键人员
- 自动传播:通过嵌入特征在所有照片中匹配身份
- 宾客匹配:可选导入宾客名单以分配姓名
- 手动修正:提供UI用于修正匹配错误
Aesthetic Scoring
美学评分
Per-Photo Quality Metrics
单张照片质量指标
python
AESTHETIC_FEATURES = {
# Technical quality
'sharpness': 'Laplacian variance, MTF analysis',
'exposure': 'Histogram analysis, dynamic range',
'noise': 'High-ISO detection, grain analysis',
# Composition
'rule_of_thirds': 'Subject placement scoring',
'symmetry': 'For venue/group shots',
'framing': 'Negative space, balance',
# Face-specific
'expression': 'Smile detection, eye openness',
'blink_detection': 'Eyes closed penalty',
'gaze_direction': 'Looking at camera vs. candid',
'face_occlusion': 'Nothing blocking the face',
'face_lighting': 'Even illumination, no harsh shadows',
# Emotional
'genuine_smile': 'Duchenne marker detection',
'moment_quality': 'Laughter, tears, embraces',
}python
AESTHETIC_FEATURES = {
# Technical quality
'sharpness': 'Laplacian variance, MTF analysis',
'exposure': 'Histogram analysis, dynamic range',
'noise': 'High-ISO detection, grain analysis',
# Composition
'rule_of_thirds': 'Subject placement scoring',
'symmetry': 'For venue/group shots',
'framing': 'Negative space, balance',
# Face-specific
'expression': 'Smile detection, eye openness',
'blink_detection': 'Eyes closed penalty',
'gaze_direction': 'Looking at camera vs. candid',
'face_occlusion': 'Nothing blocking the face',
'face_lighting': 'Even illumination, no harsh shadows',
# Emotional
'genuine_smile': 'Duchenne marker detection',
'moment_quality': 'Laughter, tears, embraces',
}Best Photo Selection Per Person
为每位宾客精选最佳照片
python
def select_best_photos(cluster_photos, n=5):
"""Select top N photos for a person across all their appearances."""
scores = []
for photo in cluster_photos:
score = (
0.25 * technical_quality(photo) +
0.25 * composition_score(photo) +
0.30 * expression_quality(photo) +
0.20 * context_diversity(photo, scores) # Avoid all similar shots
)
scores.append((photo, score))
# Select top N with diversity constraint
return diverse_top_n(scores, n, diversity_threshold=0.7)python
def select_best_photos(cluster_photos, n=5):
"""Select top N photos for a person across all their appearances."""
scores = []
for photo in cluster_photos:
score = (
0.25 * technical_quality(photo) +
0.25 * composition_score(photo) +
0.30 * expression_quality(photo) +
0.20 * context_diversity(photo, scores) # Avoid all similar shots
)
scores.append((photo, score))
# Select top N with diversity constraint
return diverse_top_n(scores, n, diversity_threshold=0.7)Theatre Mode
剧场模式
Moment Detection & Playback
瞬间检测与回放
KEY MOMENTS (auto-detected + user-tagged):
├── Ceremony
│ ├── Processional
│ ├── Vows exchange
│ ├── Ring ceremony
│ ├── First kiss
│ └── Recessional
├── Reception
│ ├── Grand entrance
│ ├── First dance
│ ├── Parent dances
│ ├── Toasts/speeches
│ ├── Cake cutting
│ └── Bouquet/garter
├── Party
│ ├── Dance floor highlights
│ └── Exit/sendoff
└── Candids
├── Emotional moments (tears, laughter)
└── Spontaneous joyKEY MOMENTS (auto-detected + user-tagged):
├── Ceremony
│ ├── Processional
│ ├── Vows exchange
│ ├── Ring ceremony
│ ├── First kiss
│ └── Recessional
├── Reception
│ ├── Grand entrance
│ ├── First dance
│ ├── Parent dances
│ ├── Toasts/speeches
│ ├── Cake cutting
│ └── Bouquet/garter
├── Party
│ ├── Dance floor highlights
│ └── Exit/sendoff
└── Candids
├── Emotional moments (tears, laughter)
└── Spontaneous joyIn-Scene Video Projection
场景内视频投影
Theatre Mode Rendering:
1. User navigates 3DGS scene freely
2. Approaches "moment marker" (glowing orb/frame)
3. Video/slideshow plays IN the 3D space
├── On walls where projector was
├── Floating frames in dance floor area
└── Photo booth backdrop location
4. Spatial audio for speeches/music
5. User can pause, scrub, exit to continue exploringTheatre Mode Rendering:
1. User navigates 3DGS scene freely
2. Approaches "moment marker" (glowing orb/frame)
3. Video/slideshow plays IN the 3D space
├── On walls where projector was
├── Floating frames in dance floor area
└── Photo booth backdrop location
4. Spatial audio for speeches/music
5. User can pause, scrub, exit to continue exploringWeb Viewer Architecture
Web查看器架构
javascript
// Wedding Immortalist Viewer Components
const VIEWER_FEATURES = {
// 3DGS Navigation
gaussianSplatting: {
renderer: 'three-gaussian-splat',
navigation: 'orbit + first-person',
qualityLevels: ['preview', 'standard', 'maximum'],
},
// Theatre Mode
theatreMode: {
momentMarkers: true,
videoInScene: true,
spatialAudio: true,
transitionEffects: 'theme-matched',
},
// Guest Roster
guestRoster: {
faceGrid: 'clustered by identity',
photoGallery: 'per-person best shots',
searchByName: true,
shareableLinks: 'per-guest galleries',
},
// Theme
theming: {
colorPalette: 'extracted from wedding',
typography: 'theme-matched',
uiElements: 'aesthetic-consistent',
},
};javascript
// Wedding Immortalist Viewer Components
const VIEWER_FEATURES = {
// 3DGS Navigation
gaussianSplatting: {
renderer: 'three-gaussian-splat',
navigation: 'orbit + first-person',
qualityLevels: ['preview', 'standard', 'maximum'],
},
// Theatre Mode
theatreMode: {
momentMarkers: true,
videoInScene: true,
spatialAudio: true,
transitionEffects: 'theme-matched',
},
// Guest Roster
guestRoster: {
faceGrid: 'clustered by identity',
photoGallery: 'per-person best shots',
searchByName: true,
shareableLinks: 'per-guest galleries',
},
// Theme
theming: {
colorPalette: 'extracted from wedding',
typography: 'theme-matched',
uiElements: 'aesthetic-consistent',
},
};Anti-Patterns
反模式
"All Frames, All the Time"
"全帧全量处理"
Wrong: Extracting every video frame for 3DGS.
Why: Redundant data, 10x slower processing, no quality improvement.
Right: 2-3 fps extraction with motion-based keyframe selection.
错误做法:提取视频的每一帧用于3DGS处理。
原因:数据冗余,处理速度慢10倍,且无质量提升。
正确做法:以2-3帧/秒的频率提取,并基于运动选择关键帧。
"One Giant Scene"
"单一巨型场景"
Wrong: Training single 3DGS for entire venue.
Why: Memory explosion, quality degradation, impossible on consumer hardware.
Right: Train per-space, create unified navigation with seamless transitions.
错误做法:为整个场地训练单个3DGS模型。
原因:内存占用爆炸,质量下降,消费级硬件无法运行。
正确做法:按区域分别训练,创建带无缝过渡的统一导航系统。
"Default Clustering Threshold"
"默认聚类阈值"
Wrong: Using default HDBSCAN settings.
Why: Wedding photos have varying lighting, makeup, angles—need tuning.
Right: Tune per-wedding based on photo count and quality variance.
错误做法:使用HDBSCAN的默认设置。
原因:婚礼照片的光线、妆容、角度差异大,需要针对性调整。
正确做法:根据照片数量和质量差异为每场婚礼调整参数。
"Ignoring Theme"
"忽略主题风格"
Wrong: Generic white/gray viewer UI for disco wedding.
Why: Destroys the personality and joy of the event.
Right: Extract and honor the couple's aesthetic choices.
错误做法:为迪斯科主题婚礼使用通用的白/灰色查看器UI。
原因:破坏了活动的个性与欢乐氛围。
正确做法:提取并遵循新人的美学选择。
"Photographer Only"
"仅使用专业照片"
Wrong: Using only professional photos.
Why: Misses candid moments, guest perspectives, coverage gaps.
Right: Merge professional + guest photos for complete coverage.
错误做法:只使用专业摄影师拍摄的照片。
原因:错过 candid 瞬间、宾客视角和拍摄盲区。
正确做法:合并专业照片与宾客上传的照片以获得完整覆盖。
Guest Experience Features
宾客体验功能
Shareable Guest Galleries
可分享的宾客画廊
Per-Guest Experience:
├── Personalized link: yourwedding.com/guests/aunt-martha
├── Their best photos (AI-curated)
├── Photos with the couple
├── Group photos they appear in
├── Download options (full-res)
└── "Add to my memories" for their own archivesPer-Guest Experience:
├── Personalized link: yourwedding.com/guests/aunt-martha
├── Their best photos (AI-curated)
├── Photos with the couple
├── Group photos they appear in
├── Download options (full-res)
└── "Add to my memories" for their own archivesCollaborative Enhancement
协作增强
Guest Contribution Portal:
├── Upload their own photos
├── Tag themselves in unidentified clusters
├── Correct misidentifications
├── Add names to unknown guests
└── Submit video moments they capturedGuest Contribution Portal:
├── Upload their own photos
├── Tag themselves in unidentified clusters
├── Correct misidentifications
├── Add names to unknown guests
└── Submit video moments they capturedOutput Deliverables
输出交付物
wedding-immortalist-output/
├── 3dgs-scenes/
│ ├── ceremony/
│ ├── cocktail/
│ ├── reception/
│ └── unified-navigation.json
├── guest-roster/
│ ├── face-clusters/
│ ├── identity-mapping.json
│ └── per-person-galleries/
├── theatre-mode/
│ ├── moment-markers.json
│ ├── video-segments/
│ └── spatial-audio/
├── web-viewer/
│ ├── index.html
│ ├── theme-config.json
│ └── assets/
└── exports/
├── full-resolution-photos/
├── guest-gallery-zips/
└── video-compilations/wedding-immortalist-output/
├── 3dgs-scenes/
│ ├── ceremony/
│ ├── cocktail/
│ ├── reception/
│ └── unified-navigation.json
├── guest-roster/
│ ├── face-clusters/
│ ├── identity-mapping.json
│ └── per-person-galleries/
├── theatre-mode/
│ ├── moment-markers.json
│ ├── video-segments/
│ └── spatial-audio/
├── web-viewer/
│ ├── index.html
│ ├── theme-config.json
│ └── assets/
└── exports/
├── full-resolution-photos/
├── guest-gallery-zips/
└── video-compilations/Integration Points
集成点
- drone-inspection-specialist: 3DGS techniques, COLMAP pipeline
- collage-layout-expert: Photo arrangement, aesthetic composition
- color-theory-palette-harmony-expert: Theme color extraction
- clip-aware-embeddings: Photo-text matching for search
- photo-composition-critic: Aesthetic quality scoring
Core Philosophy: A wedding happens once. The memories should live forever. This skill transforms ephemeral moments into an eternal, explorable experience that honors the couple's unique celebration—whether it's a disco dance party, a rustic barn gathering, or two grooms celebrating their love with chosen family.
- drone-inspection-specialist:3DGS技术、COLMAP流程
- collage-layout-expert:照片排列、美学构图
- color-theory-palette-harmony-expert:主题色彩提取
- clip-aware-embeddings:照片-文本匹配用于搜索
- photo-composition-critic:美学质量评分
核心理念:婚礼一生只有一次,记忆却应永存。本技能将短暂的瞬间转化为永恒的可探索体验,致敬新人独特的庆典——无论是迪斯科舞会、乡村谷仓聚会,还是两位新郎与chosen family共同庆祝的爱情时刻。