Lakeside Romantic Portrait of Young Woman AI Image Prompt
Scene type: luxury outdoor lifestyle portrait, location: {argument name="location" default="Mediterranean-style lakeside mountain village"}, foreground: vibrant pink flowers, stone pathway, soft floral vegetation, background: turquoise lake, blurred mountain range, warm stone buildings, bright blue sky with soft clouds, atmosphere: romantic, dreamy, sunny vacation aesthetic. Subject: young woman, early 20s, pose: slightly turned sideways, looking away from camera, touching curly hair softly, expression: natural joyful smile. Appearance: dark brown short curly bob, soft voluminous curls, warm light tan skin, smooth glowing skin, features: defined eyebrows, soft natural makeup, bright eyes, natural glossy lips, radiant smile. Clothing: {argument name="outfit" default="floral summer dress"} (pink floral print, lightweight soft cotton, feminine romantic style), outerwear: transparent white shawl (sheer organza fabric, loosely draped over shoulders). Lighting: golden hour natural sunlight, soft side lighting, warm cinematic glow, highlights: hair rim light, soft skin reflections, natural sun bloom. Camera: medium close-up portrait, eye level, 85mm portrait lens, shallow DOF, sharp focus on face, creamy bokeh. Color palette: warm beige, soft pink, sky blue, emerald green, white, tone: soft cinematic pastel. Style: ultra realistic, cinematic portrait photography, luxury travel editorial, high fashion lifestyle, Instagram aesthetic, dreamy romantic realism. Quality: 8K UHD, HDR, hyper detailed, photorealistic textures, natural skin details, professional color grading. Render settings: resolution 4K, aspect ratio 4:5.
Content: Structure: Subject (young woman, pose, expression, appearance, clothing) + Scene (foreground, background, atmosphere) + Lighting (golden hour, side light) + Camera (medium close-up, 85mm, shallow DOF) + Color (warm pink tones) + Style (ultra-realistic, cinematic) + Quality (8K, HDR). Includes replaceable arguments.
Pros: Well-structured with key elements parameterizable; high detail for quality output.
Cons: Arguments may not suit all models; prompt length may exceed some model limits.
Reference image: No obvious reference-image dependency
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