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6db16b0c799
posted 5 months ago
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"A hyper-realistic,
ultra-detailed 21:9 full-body and close-up multi-pose depiction of a stunning British woman,
presented in five distinct poses within the same frame: three full-body views and two face close-ups.
Each pose is evenly spaced,
ensuring her entire figure remains fully visible from head to feet,
while the close-up shots maintain sharp facial details.
The frame is divided into two sections for perfect clarity and proportion.
The top section
(30-40% of the frame height)
features two close-up face shots.
On the left,
a front-view close-up captures her symmetrical features,
deep brown almond-shaped eyes,
full lips,
and naturally arched eyebrows.
On the right,
a side-profile close-up highlights her jawline,
high cheekbones,
and elegant nose structure.
The bottom section
(60-70% of the frame height)
presents three full-body standing poses.
On the left,
a front-facing full-body pose,
where she stands naturally with her arms at her sides and feet firmly on the ground.
In the center,
a side-profile full-body stance,
showcasing her posture,
body curvature,
and proportions.
On the right,
a full rear-view stance,
displaying her back,
shoulders,
and leg proportions.
She has a symmetrical,
captivating face with deep brown eyes,
naturally arched eyebrows,
and full lips.
Her dark brown wavy hair is tied in a messy bun,
with loose strands framing her face.
Her athletic physique is well-proportioned,
featuring a full,
balanced bust,
a defined waist,
elegant shoulders,
toned arms,
and thick thighs.
She stands 175 cm tall and wears a black deep V-neck sports bra,
high-waisted black yoga pants,
and white sneakers.
She has no makeup,
ensuring a natural look.
The lighting is soft and natural,
casting subtle highlights and shadows to enhance depth and realism.
The clean white background ensures clarity,
while HDR 4K resolution captures ultra-detailed textures and perfectly balanced skin tones,
achieving a highly cinematic effect.
The 21:9 ultra-wide aspect ratio maintains accurate proportions,
ensuring no cropping or distortion,
making it an ideal dataset for LoRA training.
"**
Generation parameters
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