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muapi-photo-pack-generator

muapi-photo-pack-generator

github.com/samuraigptCreative & media25966 installsUpdated 4w ago
Repository

About muapi-photo-pack-generator

muapi-photo-pack-generator is a skill for turning one reference photo into a themed set of images while prioritizing facial identity preservation. It guides scene analysis and prompt construction without describing the person, for agents generating professional, lifestyle, or stylized portraits.

Key features

  1. 01Preserve facial identity from a reference photo
  2. 02Analyze pose, expression, lighting, and framing
  3. 03Construct identity-lock prompts and negative prompts
  4. 04Generate themed photo packs
  5. 05Support professional, lifestyle, and fantasy categories

Use cases

  1. 01Create professional portrait variations from one photo
  2. 02Generate themed dating or travel images
  3. 03Produce cinematic or fantasy-style portraits
  4. 04Keep facial identity consistent across generated images

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/samuraigpt/generative-media-skills --skill muapi-photo-pack-generator

After installing, type/muapi-photo-pack-generatorin Claude Code to confirm it loaded.

Bundled filesscripts/generate-pack.sh

Details

From the project README

📸 Photo Pack Generator Expert Skill (Identity-Lock Edition)

Transform a single reference photo into a collection of themed images while maintaining extremely high facial identity fidelity.

This skill prioritizes identity preservation first, then applies stylistic transformations like LinkedIn portraits, dating photos, cinematic shots, or fantasy styles.

The system uses Identity Lock Prompting instead of describing the person, preventing the model from generating a new face.


Core Principles

1️⃣ Identity Lock (MOST IMPORTANT)

The generated images must always depict the same person from the reference image.

All prompts MUST include identity lock instructions.

Required identity rules:

  • Preserve the exact facial identity from the reference image
  • Do not modify eye shape or spacing
  • Do not modify nose structure
  • Do not modify jawline or chin shape
  • Do not modify cheekbones
  • Do not modify face proportions
  • Identity must remain identical to the reference photo

2️⃣ Vision-First Scene Analysis

The agent MUST analyze the reference image before generation.

However the analysis must NOT describe the person (age, ethnicity, hair etc).

Allowed analysis fields:

  • head orientation
  • facial angle
  • expression
  • lighting direction
  • framing (portrait / half body / full body)

Example:

Head orientation: slight left tilt
Expression: neutral friendly
Lighting: soft frontal light
Framing: head and shoulders portrait


Agent Execution Flow

Step 1 — Grounding Check

Ensure the user has provided a reference image.

Supported inputs:

  • local image
  • URL
  • uploaded file

Step 2 — Vision Analysis

Extract scene attributes only.

DO NOT describe:

  • age
  • ethnicity
  • beard
  • hair
  • body type

Identity must come directly from the image.


Step 3 — Category Selection

If the user does not specify a category suggest:

  • LinkedIn
  • Tinder
  • OldMoney

Step 4 — Prompt Construction

Use the reference image as the identity source.

Preserve the exact facial identity from the reference image.

Identity must remain identical to the reference photo.

Do not change:

  • eye shape
  • eye spacing
  • nose structure
  • jawline
  • cheekbones
  • face proportions

Maintain similar head orientation as the reference.

Scene example:

Outdoor café portrait
Soft natural daylight
35mm portrait lens
Shallow depth of field
Photorealistic skin texture


Step 5 — Negative Prompt

Always include:

different person
altered face
changed facial features
new identity
generic face
beautified face
plastic skin
face distortion


Step 6 — Execution

Example:

bash scripts/generate-pack.sh
--image "./my_face.jpg"
--category "LinkedIn"
--identity-lock true
--num 5


Supported Categories

CategoryBest ForAesthetic
LinkedInProfessionalStudio
CEOFoundersOffice
TinderDatingLifestyle
OldMoneyLuxuryEstate
CyberpunkFantasyNeon
FitnessGymAthletic
TravelSocialBali/Paris
90sRetroVintage
HolidaySeasonalFestive

Guardrails

Fidelity First

Identity preservation is always more important than style.

Never Re-Describe the Person

Avoid prompts like:

"Indian man in his 20s with short hair"

This causes the model to generate a new face.

Identity must come from the reference image only.


Recommended Models

Best results with:

  • nano-banana-edit

Result

This system produces:

  • consistent identity
  • photorealistic images
  • multi-style photo packs
  • professional outputs

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