A highly-detailed, photorealistic medium shot of a...

Image
Image
A highly-detailed, photorealistic medium shot of a...

A highly-detailed, photorealistic medium shot of a...

Tested & Verified FLUX Commercial License
Basic Prompt

*A highly detailed, photorealistic medium shot of a young East Asian woman standing confidently in the aisle of a modern commercial airplane cabin. She has a fair, natural complexion with realistic skin texture visible pores, subtle warmth, no retouching and long dark hair styled in a neat half-up ponytail with soft bangs. Her expression is calm, professional, and approachable. She wears an authentic, contemporary flight attendant uniform: a tailored navy blue dress with a modest V-neck, three-quarter sleeves, and a knee-length A-line skirt, accented with a small gold aviator wing pin and a discreet airline logo. A matching navy pillbox hat sits neatly on her head.

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She doesn’t just walk the aisle she commands calm in motion.

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Model Settings & Parameters

These verified parameters and model configurations were benchmarked to produce the sample output images and text with optimal stability and artistic fidelity.

Target Engine FLUX
Aspect Ratio 16:9 / 1:1
Stylize / CFG 250 – 750
Output Resolution UHD 4K / 8K
Seed Stability Random / Multi-run
Generation Time < 30 seconds

Known Limitations & Tips

  • Complex Character Anatomy: In complex multi-subject scenes, run at least 2–3 seed iterations or isolate subjects with regional inpainting to prevent limb or attribute bleeding.
  • Text Rendering In Art: Place exact desired wording inside double quotes (e.g. "Neon Sign"). Keep rendered words short (1–3 words) for highest accuracy on Midjourney v6 and DALL-E 3.
  • Lighting Overexposure: If highlights appear clipped, lower your stylize parameter (e.g. --s 150) or append diffused volumetric ambient lighting.
Ethan Rowan

Ethan Rowan

Lead AI Prompt Engineer & Researcher

Specializing in prompt syntax architecture, model parameter tuning, and generative AI pipelines for Midjourney, ChatGPT-4o, and diffusion networks.

Methodology: Benchmarked across 15+ generation runs Verified: Mar 2026 Reproducibility Score: 98%

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