recreate-thumbnails

name	recreate-thumbnails
description	Face-swap YouTube thumbnails to feature Your Name using AI. Use when user asks to recreate thumbnails, face swap images, generate YouTube thumbnails, or create thumbnail variations.

Recreate YouTube Thumbnails

Goal

Face-swap YouTube thumbnails to feature Your Name using Gemini image model. The system analyzes face direction, matches reference photos by pose, and generates variations.

Scripts

• ./scripts/recreate_thumbnails.py - Main generation script
• ./scripts/analyze_face_directions.py - Reference photo analyzer

Quick Start

# From YouTube video (auto-downloads thumbnail)
python3 ./scripts/recreate_thumbnails.py --youtube "https://youtube.com/watch?v=VIDEO_ID"

# From local thumbnail
python3 ./scripts/recreate_thumbnails.py --source ".tmp/thumbnails/source.jpg"

# Edit pass on generated thumbnail
python3 ./scripts/recreate_thumbnails.py --edit ".tmp/thumbnails/recreated_v3.png" \
  --prompt "Change colors to teal. Change 'AI GOLD RUSH' to 'AGENTIC FLOWS'."

Full Workflow

Step 1: Build Reference Photo Bank (One-time)

# Drop 30-40 photos of Nick into raw folder
mkdir -p .tmp/reference_photos/raw

# Analyze and rename with face direction metadata
python3 ./scripts/analyze_face_directions.py

Creates files like:

• nick_yawL30_pitchU10.jpg — looking 30° left, 10° up
• nick_yawR45_pitch0.jpg — looking 45° right, level

Step 2: Generate Thumbnails

# From YouTube URL (analyzes face, finds best reference, generates 3 variations)
python3 ./scripts/recreate_thumbnails.py --youtube "VIDEO_URL"

# Custom variation count
python3 ./scripts/recreate_thumbnails.py --source "thumbnail.jpg" -n 5

# Skip direction matching
python3 ./scripts/recreate_thumbnails.py --source "thumbnail.jpg" --no-match

Step 3: Edit & Refine

# Single edit
python3 ./scripts/recreate_thumbnails.py --edit ".tmp/thumbnails/recreated_v3.png" \
  --prompt "Change colors to teal brand colors."

# Chain multiple edits
python3 ./scripts/recreate_thumbnails.py --edit ".tmp/thumbnails/edited_1.png" \
  --prompt "Make text bigger. Change background to white."

CLI Reference

Flag	Description
--youtube, -y	YouTube video URL
--source, -s	Source thumbnail path or URL
--edit, -e	Image to edit (enables edit mode)
--prompt, -p	Edit instructions (required for edit mode)
--variations, -n	Number of variations (default: 3)
--refs	Number of reference photos (default: 2)
--no-match	Skip face direction matching

Output Organization

.tmp/thumbnails/
├── 20251205/              # Date folder
│   ├── 104016_1.png       # Variation 1
│   ├── 104016_2.png       # Variation 2
│   ├── 104016_3.png       # Variation 3
│   └── 104532_edited.png  # Edit pass

API Details

• Model: gemini-3-pro-image-preview (Nano Banana Pro)
• Cost: ~$0.14-0.24 per generation/edit
• Latency: 10-60+ seconds per image
• Output: ~1376x768 (close to 16:9)

Learnings

• 2 reference photos is optimal (1 loses likeness, 3+ causes regeneration)
• Must explicitly request 16:9 format in prompt
• Label images in prompt: "IMAGE 1: Reference, IMAGE 2: Thumbnail"
• "100% exact duplicate except face" instruction works well
• Edit passes work for text, colors, graphs, backgrounds

Environment

NANO_BANANA_API_KEY=your_key

---

Schema

Inputs

Name	Type	Required	Description
youtube_url	string	No	YouTube video URL (auto-downloads thumbnail)
source	file_path	No	Source thumbnail image path
variations	integer	No	Number of variations (default: 3)
edit_image	file_path	No	Image to edit (enables edit mode)
prompt	string	No	Edit instructions for edit mode

Outputs

Name	Type	Description
thumbnails	array	Generated thumbnail file paths in .tmp/thumbnails/

Credentials

Name	Source
NANO_BANANA_API_KEY	.env

Composable With

Skills that chain well with this one: cross-niche-outliers, youtube-outliers

Cost

$0.14-0.24 per generation