Stable Diffusion Prompts for Realistic Faces

Generating realistic human faces is one of the most popular uses for AI image generation models like Stable Diffusion. With careful prompt engineering, the model can produce photorealistic portraits.

Positive Prompts

Positive prompts provide the model with descriptive details about the desired image:

  • Specify photo realism keywords like “photograph” or “portrait”
  • Include facial features like “beautiful eyes” or “radiant skin”
  • Add lighting such as “soft studio lighting”
  • Give posing details like “facing the camera”

Example:

Portrait photograph of a young woman with long wavy brown hair, hazel eyes, radiant skin, facing the camera, soft studio lighting

Negative Prompts

Negative prompts tell the model what not to include:

  • Remove unwanted facial features like “disfigured” or “deformities”
  • Eliminate flaws like “ugly”, “bad anatomy”
  • Avoid unwanted styles like “cartoon”, “drawing”

Example:

Portrait photograph of a young woman with long wavy brown hair, hazel eyes, radiant skin, facing the camera, soft studio lighting. No disfigured, ugly, bad anatomy, cartoon, drawing

Advanced Techniques

More advanced prompt engineering tactics like weighted keywords and multiple prompts can further improve realism. Upscalers like ESRGAN can also enhance final image quality.

I hope this overview on AI prompt engineering for realistic faces gives some meaningful insights! Let me know if you would like me to expand on any section in more detail.

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