product-photography

Generate e-commerce product photography with studio lighting and lifestyle shots.

688|95|Updated Jan 31, 2026

Search Tags:#e-commerce #ai image generation #product photography #lifestyle photography #studio lighting #packshot

Ready to run

npx skills add https://github.com/inference-sh/skills --skill product-photography-inference-sh

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: product-photography
Source: https://github.com/inference-sh/skills/tree/main/guides/photo/product-photography
Command: npx skills add https://github.com/inference-sh/skills --skill product-photography-inference-sh

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill empowers users to generate professional-grade product photographs, including studio lighting, lifestyle shots, and e-commerce compliant packshots, without needing expensive equipment or professional photographers.

Core Features & Use Cases

Versatile Shot Types: Create hero shots, packshots (pure white background), lifestyle images, scale references, detail close-ups, and group shots.
Customizable Aesthetics: Control angles, lighting setups, shadow types, and backgrounds to match brand and platform requirements.
E-commerce Ready: Generates images compliant with major marketplace standards like Amazon.
Use Case: A small e-commerce business owner can use this Skill to create a full set of 7-9 high-quality images for a new product listing, from hero shots to lifestyle and detail views, all from a single prompt.

Quick Start

Generate a professional product photography packshot for a wireless headphone on a clean white background.

Frequently Asked Questions about product-photography

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate professional e-commerce product photography without a physical studio?▼

AI product photography generation creates professional studio lighting, lifestyle shots, and packshots using models like bytedance/seedream-4-5 and falai/flux-dev-lora. You can produce hero shots, detail close-ups, and scale references from a single prompt without physical equipment or professional photographers.

Can I create Amazon compliant packshots with a pure white background using AI image generation?▼

Yes, AI product photography generation supports e-commerce ready packshots with pure white backgrounds compliant with major marketplace standards like Amazon. You can customize angles, lighting setups, and shadow types to match specific platform requirements for your product listings.

What types of product shots can I generate for an e-commerce listing?▼

AI product photography generation supports versatile shot types including hero shots, packshots, lifestyle images, scale references, detail close-ups, and group shots. A small e-commerce business owner can create a full set of 7-9 high-quality listing images from a single prompt.

Does AI product photography support custom lighting setups and background control?▼

AI product photography generation provides customizable aesthetics allowing you to control angles, lighting setups, shadow types, and backgrounds. This enables you to match brand and platform requirements precisely using tools like falai/flux-dev-lora for image generation and editing.

What's the best way to create lifestyle product photography for online stores?▼

AI product photography generation produces lifestyle shots by utilizing models like bytedance/seedream-4-5 to render products in contextual environments. You can specify scale references and detail close-ups to create a complete lifestyle image set without hiring a professional photographer.

Are there limitations when generating product photography for e-commerce platforms?▼

AI product photography generation relies on models like bytedance/seedream-4-5 and falai/flux-dev-lora, meaning output quality depends on prompt specificity. While it covers studio lighting, lifestyle shots, and packshot conventions, complex physical lighting interactions may require iterative prompt refinement.