What AI Does Well (and Poorly) for Photo Generation — Especially People & Consistency

Photoreal mood and lighting. Natural window light, golden hour, studio key/rim setups, soft shadows, shallow depth of field, filmic grades.

Single-person portraits. Headshots and 3/4 portraits with clean backgrounds and clear facial features.

Composition & camera “feel.” 35/50/85mm looks, low/high angles, center vs. rule-of-thirds framing.

Broad styling. Body-shape trends, wardrobe categories (blazer dress, athleisure, swimwear), hair length/texture, makeup styles.

Aesthetic replication. Matching a visual vibe from a reference (color grade, lighting, lens feel) using Generator by Reference or the Carousel tool.

Batch variety. Producing cohesive sets of similar images in one go (Carousel, PhotoShoot).

LoRA-guided shaping (SDXL). Controlling physique or stylistic traits with moderate LoRA strengths.

Identity consistency across angles/time. The same person can drift in side profiles, extreme expressions, or new scenes.

Hands, feet, and fine anatomy. Fingers may merge, grips look awkward, toes warp in sandals; extreme muscularity can look plasticky.

Small text/logos and micro-details. On shirts, phones, signage; tiny jewelry patterns; watch faces.

Accessories & occlusions. Glasses frames, earrings behind hair, hair crossing the face, hats touching eyebrows, hands near the mouth.

Reflections and translucency. Mirrors, glass, water surfaces; lens reflections on glasses.

Complex pattern geometry. Tight stripes, checks, lace meshes, and detailed embroidery.

Multi-person interactions. Eye-lines, hand placement, scale/perspective consistency among several people.

Exact brand replication or copyrighted marks. Models tend to avoid precise logos; results can be off or garbled.

Face Generation to craft candidate faces quickly.

Generator by Prompt for new looks/poses; WAN for realism, SDXL for LoRA control (we auto-inject LoRA keywords—keep your prompt natural).

Generator by Reference when you need the same vibe, angle family, or outfit line as an example image.

Photo-Shoot Generator to create multi-category sets (office/café/vacation…) while preserving identity.

Carousel for rapid, on-theme variations around your best hero shot.

Upscaler to lift detail/resolve softness. Use Face-Safe Upscale if the face must remain unchanged.

Face Swap (last step) to lock identity across everything you’ll publish.

Use 1–2 LoRAs at 0.6–0.9 each; 0.8 is a great starting point.

Combining 3 LoRAs is fine, but keep strengths conservative and avoid contradictions (e.g., Slim Figure vs. Plus Size Body).

Over 1.5 increases artefacts (warping, crunchy textures). If detail drops or anatomy breaks, lower strengths by 0.2 and simplify the prompt.

Reuse lighting language, camera terms (e.g., “50mm, eye-level, shallow DOF”), and grade cues across the whole set.

Avoid changing too many variables at once (pose, outfit, environment, lighting) if identity is your priority.

Write in this order: person → body/wardrobe → pose/camera → lighting → environment → mood/grade → quality.

Keep the negative prompt lean but targeted:
​lowres, bad anatomy, extra limbs, deformed hands, fused fingers, duplicate face, blurry, over-smooth skin, watermark, text, jpeg artifacts, harsh sharpening

Ask GPT to describe a reference photo into a concise, photoreal prompt including camera and lighting terms; paste the result.

WAN if you want the most photoreal images and don’t need LoRAs.

SDXL if you need shape/style control via LoRAs (we add the LoRA tokens automatically).
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If realism slips on SDXL, try lowering LoRA strengths or switching to WAN for the base look, then end with Face Swap.

Face changes between slides: reuse the same aspect ratio; end with Face Swap.

Hands look wrong: simplify pose; add bad hands to negatives; avoid extreme wide-angle; re-generate close-ups separately.

Soft/“plastic” skin: reduce LoRA strengths; add “realistic skin texture, natural pores”; finish with Upscaler.

Weird glasses/earrings: remove from the initial prompt; add later via Face Swap into a base where the face is already stable.

Hair inconsistency: specify length, parting, and texture; keep lighting/camera the same across the set.

Reflections look fake: avoid mirrors/wet glass in generation; composite later or choose angles without reflections.

Tiny logos/text garbled: don’t rely on generation; add in post if brand marks are critical.

Over-muscular or distorted physiques: lower Strong Muscular Body/Athletic LoRAs; add “realistic anatomy, proportional limbs” to the prompt.

The same person is recognizable in front, 3/4, and mild profile views.

Hair is the same length/texture/parting across the set.

Eyes are aligned; no extra reflections, no duplicated catchlights.

Hands and fingers are plausible; no fused digits.

Clothing behaves like real fabric; seams and edges look natural.

Lighting and grade feel consistent; no jarring clip/crush.

Resolution meets platform spec; use Upscaler where needed.

Final step was Face Swap (unless you used Face-Safe Upscale and identity was perfect already).

New virtual persona: Face Generation → pick a hero → Prompt/Reference to build range → Upscale → Face Swap last.

Real person look-alike: Generate base scene with WAN/SDXL → Face Swap last with the authorized source portrait → quick color pass → publish.

Large campaign set: PhotoShoot per category → schedule posts.

We add LoRA keywords automatically when you pick LoRAs in SDXL — keep your text readable and focused on the shot.

If you need a bigger image but the face must remain untouched, use Face-Safe Upscale.

If identity is the contract, Face Swap is your safety net — run it last.

When in doubt, generate small, review anatomy/identity, then scale up your batch.