Use the attached person image as the primary identity reference and preserve 100% facial identity accuracy.
Identity Preservation (Critical)
Use the exact face from the attached image.
Maintain 100% facial structure accuracy, including:
same eyes, eyebrows, and eye spacing
same nose shape
same lips and jawline
same beard or facial hair (if present)
same hairstyle and hairline
same skin tone
Do not stylize, beautify, cartoonize, or modify the face.
The final result must look like the same person photographed in a different scene.
Scene Description
Create an ultra-realistic devotional scene at the Ram Mandir in Ayodhya, India.
A devotee is standing in front of the grand Ram Mandir temple, facing the temple with hands joined in a Namaste position, showing devotion and prayer.
Person Appearance
The person is wearing:
traditional white kurta
white pajama
saffron/orange cloth draped around the neck
bright red tilak on the forehead
Posture:
standing respectfully
hands joined in Namaste
facing the temple
calm devotional expression
Background
The Ram Mandir in Ayodhya should be clearly visible behind the person.
Include:
detailed temple architecture
carved sandstone pillars
temple steps and courtyard
saffron flags near the temple
a few devotees in the background (softly blurred)
Lighting
golden sunrise lighting
warm spiritual glow on the temple
soft sunlight illuminating the devotee
cinematic light rays
Camera Style
cinematic photography
50mm DSLR lens
shallow depth of field
sharp focus on the person
temple slightly blurred for depth
ultra realistic photography
8k detail
Quality Constraints
photorealistic
no illustration or cartoon style
no distortion
no watermark
professional DSLR quality
face must remain identical to the attached reference image
Just copy the prompt and paste it into your AI tool (like ChatGPT, Gemini, or Midjourney). For best results, use it as it is first, then adjust if needed.
Yes! You can change the tone, style, length, or details to match your specific goal. Prompts are flexible.
AI tools generate slightly different results each time. Output can vary depending on model version, settings, or small wording changes.
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