Module 1.0
AI Fashion Photography
A hands-on walkthrough of building a complete AI-powered fashion photography pipeline in ImagineArt — from a single flat-lay image to a full campaign. Covers generating PDP product and on-model shots, using Agent Mode to plan editorial concepts, locking in brand consistency with system prompts, techniques for realistic on-model imagery, localizing assets for different markets, and structuring workflows so the entire pipeline is repeatable across every SKU in a collection.
6 lessons · From the course: AI for Fashion & Apparel
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1.2Generating PDP Images from a Flat-Lay (Product, On-Model & Video)Build a repeatable node workflow that turns a single flat-lay product photo into a full set of PDP assets — product close-ups, on-model shots in multiple poses/ethnicities, and short 360° product videos.→1.3Ideating Concepts for Campaign ImageryUse ImagineArt's in-built chat mode in Workflows to turn a mood board and a product image into multiple campaign-ready prompts, then fan them out automatically into a full set of editorial fashion campaign images.→1.4Using System Prompts to Create Visually Consistent Campaign ImagesLearn how system prompts keep color, mood, and camera direction consistent across every image in a campaign — and how to use the Agent Mode in ImagineArt Workflows to generate one from your brand guidelines.→1.5Best Practices: Making Your AI Models Look More RealisticPractical techniques for making AI-generated models look photoreal instead of plastic — from generating your model separately with realistic skin texture to compositing them onto your garment.→1.6Building Market-Specific Assets from One CampaignSkip separate local photo shoots for every market — learn how to re-target existing campaign assets and entire workflows to a new model ethnicity while keeping art direction, styling, and framing identical.→1.7Making a Repeatable Workflow That Works for 1000+ SKUsThe one rule that determines whether your pipeline is truly repeatable across hundreds of SKUs — and how to fix prompts that accidentally break it, using the agent to rephrase them at scale.→