morpheus-fashion-designGenerate professional advertising images with AI models holding/wearing products. ✅ USE WHEN: - Need a person/model in the image WITH a product - Creating fashion ads, product campaigns, commercial photography - Want consistent model face across multiple shots - Need professional lighting/camera simulation - Input: product image + model reference (or catalog) ❌ DON'T USE WHEN: - Just editing/modifying an existing image → use nano-banana-pro - Product-only shot without a person → use nano-banana-pro - Already have the hero image, need variations → use multishot-ugc - Need video, not image → use veed-ugc after generating image - URL-based product fetch with brand profile → use ad-ready instead OUTPUT: Single high-quality PNG image (2K-4K resolution)
Install via ClawdBot CLI:
clawdbot install PauldeLavallaz/morpheus-fashion-designGenerate professional fashion/product advertising images using ComfyDeploy's Morpheus Fashion Design workflow.
Configuration packs MUST NEVER be left on auto or AUTO.
auto = empty values = neutral, boring images with no creative direction.
The pack options listed below are suggestions/ideas, but you can send custom values that better fit the brief. The goal is to select the best possible configuration to represent the image needed for the brief.
For EVERY generation, thoughtfully select values based on the creative brief:
| Pack | How to Choose |
|------|---------------|
| style_pack | Match brand personality: luxury→premium_restraint, sports→cinematic_realism, street→street_authentic |
| camera_pack | What camera would a real photographer use? Sports→sony_a1, editorial→hasselblad_x2d, street→leica_m6 |
| lens_pack | Portrait compression? Anamorphic? Wide? Match the shot type and mood |
| lighting_pack | What's described in the brief? Golden hour? Studio? Natural window? Choose accordingly |
| pose_discipline_pack | What's the model doing? Sport action→sport_in_motion, commercial→commercial_front_facing |
| film_texture_pack | Warm editorial→kodak_portra_400, cinematic→kodak_vision3_500t, clean digital→digital_clean_no_emulation |
| environment_pack | Match brief location: beach→beach_minimal, urban→urban_glass_steel, nature→provide location_ref image |
| color_science_pack | Warm tones? Cool? Cinematic contrast? Select based on mood |
| time_weather_pack | When does the scene happen? Golden hour? Midday? Overcast? |
style_pack = "cinematic_realism" # NOT auto - sports action needs energy
camera_pack = "sony_a1" # Fast sports camera
lens_pack = "wide_distortion_controlled" # Capture the action
lighting_pack = "golden_hour_backlit" # Alpine dramatic lighting
pose_discipline_pack = "sport_in_motion" # Rider in action
time_weather_pack = "golden_hour_clear" # Mountain conditionsIf none of the preset options fit, you can write your own value as a descriptive string:
lighting_pack = "harsh alpine midday sun reflecting off fresh powder"
environment_pack = "snowpark with metal rails and pristine packed snow"Morpheus Fashion Design is a comprehensive AI workflow for creating high-quality commercial photography with:
Endpoint: https://api.comfydeploy.com/api/run/deployment/queue
Deployment ID: 1e16994d-da67-4f30-9ade-250f964b2abc (production)
A curated catalog of 114 AI-generated model references is available for use when no specific model is provided.
GitHub: https://github.com/PauldeLavallaz/model_management
If the user attaches/provides a model image → use that image directly. The catalog is ONLY for when no model is specified.
# Clone the catalog to your workspace
git clone https://github.com/PauldeLavallaz/model_management.git models-catalogcd models-catalog && git pull~/clawd/models-catalog/catalog/images/
models-catalog/
└── catalog/
├── catalog.json # Full metadata for all models
└── images/ # Model reference photos (model_01.jpg - model_114.jpg)Priority order for model selection:
# List all models with basic info
cat models-catalog/catalog/catalog.json | jq '[.talents[] | {id, name, gender, ethnicity, tags: .tags[0:2]}]'
# Find models by ethnicity
cat models-catalog/catalog/catalog.json | jq '[.talents[] | select(.ethnicity == "hispanic") | {id, name, description}]'
# Find models by tag
cat models-catalog/catalog/catalog.json | jq '[.talents[] | select(.tags[] == "commercial") | {id, name, ethnicity}]'
# Find models by gender
cat models-catalog/catalog/catalog.json | jq '[.talents[] | select(.gender == "male") | {id, name, ethnicity}]'Each model entry includes:
id: Unique identifier (model_01, model_02, etc.)name: Model namegender: female, male, non-binaryethnicity: african, asian, caucasian, hispanic, mixed, etc.age_group: young_adult, adult, maturetags: editorial, commercial, beauty, lifestyle, avant-garde, etc.description: Detailed description of look and best usesimage_path: Path to reference image# For an Argentine campo/gaucho campaign, find hispanic females with commercial tags:
cat models-catalog/catalog/catalog.json | jq '[.talents[] | select(.ethnicity == "hispanic" and .gender == "female" and (.tags[] == "commercial" or .tags[] == "lifestyle")) | {id, name, description}]'
# Then use the selected model:
--model "models-catalog/catalog/images/model_08.jpg"| Pack | Options |
|------|---------|
| style_pack | auto, premium_restraint, editorial_precision, cinematic_realism, cinematic_memory, campaign_hero, product_truth, clean_commercial, street_authentic, archive_fashion, experimental_authorial |
| shot_pack | auto, full_body_wide, medium_shot, close_up, low_angle_hero, three_quarter, waist_up, etc. |
| camera_pack | auto, arri_alexa35, canon_r5, hasselblad_x2d, leica_m6, sony_a1, etc. |
| lens_pack | auto, cooke_anamorphic_i_50, leica_noctilux_50, zeiss_otus_55, etc. |
| lighting_pack | auto, golden_hour_backlit, natural_window, studio_three_point, etc. |
| pose_discipline_pack | auto, commercial_front_facing, street_style_candid_walk, sport_in_motion, etc. |
| film_texture_pack | auto, kodak_portra_400, fujifilm_velvia_50, digital_clean_no_emulation, etc. |
| color_science_pack | auto, neutral_premium_clean, warm_golden_editorial, cinematic_low_contrast, etc. |
| environment_pack | AUTO, beach_minimal, urban_glass_steel, street_crosswalk, etc. |
| time_weather_pack | auto, golden_hour_clear, bright_midday_sun, overcast_winter_daylight, etc. |
| branding_pack | logo_none, logo_discreet_lower, logo_top_corner, logo_center_watermark, logo_integrated |
| intent | auto, awareness, consideration, conversion, retention |
| aspect_ratio | 9:16, 16:9, 1:1, 4:5, 5:4, 3:4, 4:3 |
uv run ~/.clawdbot/skills/morpheus-fashion-design/scripts/generate.py \
--product "path/to/product.jpg" \
--model "path/to/model-face.jpg" \
--brief "Campaign brief text..." \
--target "Target audience description..." \
--aspect-ratio "4:5" \
--style-pack "street_authentic" \
--output "output-filename.png"La campaña Franuí Carnaval captura el espíritu festivo y la alegría del carnaval brasileño
en Copacabana. Una mujer afrobrasileña baila en medio de la multitud, sosteniendo el
producto Franuí Milk hacia la cámara en un gesto espontáneo y celebratorio. La escena
está llena de confeti, movimiento y energía. La fotografía adopta un estilo documental
con motion blur intencional, ángulo bajo que empodera al sujeto, y el producto como
elemento hero en primer plano. La luz es natural de día tropical, cálida y vibrante.Jóvenes adultos 18-35, principalmente mujeres pero inclusivo, que celebran la vida,
la música y los momentos compartidos. Consumidores de experiencias premium que buscan
productos que se integren naturalmente a sus momentos de disfrute. Activos en redes
sociales, valoran la autenticidad y la conexión cultural. Mercado: Brasil y LATAM.The workflow has an automatic studio_override that activates when no location reference is provided. This will use a white cyclorama background regardless of the brief description.
To get environmental backgrounds:
location_ref image, ORenvironment_pack to a specific environment (e.g., beach_minimal, street_crosswalk)The system follows this priority:
DO NOT pass the API key via parameter. Leave it empty.
The API key is already configured in ComfyDeploy. Passing --api-key will cause authentication errors.
Si la imagen generada sale completamente negra o vacía, es el filtro de moderación de Google/Gemini. Causas comunes:
Solución: Modificar el prompt para evitar referencias a personas reales/famosas, o cambiar elementos que puedan activar el filtro.
Generated Mar 1, 2026
Online retailers can generate professional model shots wearing new clothing lines, ensuring consistent model faces across product categories. This reduces photoshoot costs and accelerates campaign launches for seasonal collections.
Brands launching athletic gear can create dynamic action shots with models in motion, using packs like cinematic realism and sport_in_motion. This highlights product functionality in realistic environments like gyms or outdoor settings.
High-end fashion houses can produce premium advertising images with luxury styling, using packs like premium_restraint and hasselblad_x2d. This maintains brand aesthetics for magazine spreads or digital campaigns.
Streetwear brands can generate authentic urban shots with models in street settings, leveraging packs like street_authentic and urban_glass_steel. This creates engaging content for social media and promotional materials.
Companies selling accessories like watches or bags can integrate products with models in lifestyle contexts, using environment packs to match briefs like beach_minimal or studio settings. This enhances product appeal in commercial photography.
Marketing and advertising agencies can subscribe for bulk image generation, using the skill to produce campaigns for multiple clients. This offers scalable, cost-effective creative services without hiring photographers.
Freelance designers and photographers can offer custom ad creation, leveraging the skill to deliver high-quality images quickly. They can charge per project or hourly rates for tailored campaigns.
Fashion brands can integrate the skill into their internal workflows to generate all advertising imagery in-house. This reduces reliance on external studios and speeds up time-to-market for new products.
💬 Integration Tip
Ensure all configuration packs are set to specific values, not auto, and prioritize user-provided model images over the catalog for best results.
Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.
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