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

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

Outputs

Credentials

Composable With

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

Cost

$0.14-0.24 per generation