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AI Product & People Photography Suite

Hyper-realistic imagery for products and people using state-of-the-art local AI models. No shoots. No delays.

Published January 15, 2024
1 min read

Technologies Used

SD / FLUX
ControlNet
ComfyUI
Docker
Next.js
AWS EC2
AI-generated product photography example showing high quality output
90%
Faster Turnaround Time
$1.8M
Annual Savings on Shoots & Editing
98.5%
User Satisfaction with Image Output

From Product to Persona: Personalized Photoshoots, AI-Driven

We built an AI-driven suite enabling brands and individuals to generate hyper-realistic product & people photography — without traditional shoots. Our system reduced turnaround time by 90%, cut costs by $1.8M annually, and enabled user-led creative direction at scale. Integrated with our Campaign Readiness Scanner for immediate ad deployment.

The Challenge

Expensive traditional shoots for product and model imagery
Limited ability to customize outputs for niche markets
Slow turnaround and dependency on availability of models/studios
Lack of personalization in eCommerce imagery

Our Solution

AI-powered image-to-image & text-to-image model pipelines
User shares products and model pictures (real or virtual, even themselves)
Locally hosted stable diffusion workflows ensure data privacy & speed
End-to-end stylization, lighting, and rendering handled by AI

Key Features

Personalized Model Selection

Choose from curated models or upload your own image

  • Face matching AI
  • Skin tone & posture alignment
  • User-generated avatars

Product + Model Composition

AI places your product on the model naturally and accurately

  • Perspective alignment
  • Dynamic lighting match
  • Shadow synthesis

Text-to-Style Shoot Generator

Describe the look — AI generates it

  • Prompt-based outfit/environment generation
  • Style templates
  • Brand-specific stylization

Batch Creation Pipeline

High-speed image generation and enhancement engine

  • Multi-GPU parallelism
  • Concurrent renders
  • Automated enhancement layers

Background & Setting Control

Generate indoor, outdoor, studio-style backdrops with a prompt

  • Scene detection
  • Depth-aware rendering
  • Realistic DOF

Output Optimization

Export for marketplaces, ads, social in one click

  • Multi-size exports
  • Format presets
  • Compression intelligence

Technology Stack

SD / FLUX
ControlNet
ComfyUI
Docker
Next.js
AWS EC2

Project Timeline & Results

1
Week 1-2

Model Pipeline Prototyping

Deployed base image-to-image workflow with style preservation

Established the foundational AI pipeline using Stable Diffusion and FLUX models. Implemented ControlNet for precise image control and style preservation. Set up ComfyUI workflows for consistent image generation and created the initial Docker containerization for scalable deployment.

2
Week 3-5

User Model Personalization

Enabled face/image injection with < 3 input photos

Developed advanced face matching algorithms and skin tone alignment systems. Built user avatar generation capabilities that require minimal input photos. Implemented perspective alignment and dynamic lighting match systems for natural-looking compositions.

3
Week 6-8

Batch Processing + Output Pipeline

Built interface for multi-scenario image generation with queue handling

Created high-speed batch processing system with multi-GPU parallelism. Implemented concurrent rendering capabilities and automated enhancement layers. Built comprehensive output optimization for different platforms and formats with intelligent compression.

4
Week 9-10

Launch & Testing

Achieved 98.5% match-to-expectation score from beta users

Conducted extensive beta testing with real users and products. Fine-tuned the AI models based on feedback and performance metrics. Deployed the final system on AWS EC2 infrastructure with auto-scaling capabilities and achieved production-ready performance standards.

Interested in AI Product & People Photography Suite?

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