Regina Image Generation and Editing Model

Discover the Regina Image Generation and Editing Model, a versatile tool for creating and refining images. See what makes this AI model special!

Platform: Replicate

Text-to-Image GenerationImage InpaintingLoRA IntegrationImage Editing

52 runs

H100

License Check Required

🚀Function Overview

Generates or edits images using text prompts, input images, and masks, offering extensive control over resolution, style, and output quality.

Key Features

Text-to-image generation from detailed prompts
Image-to-image translation and inpainting
Support for multiple resolutions and aspect ratios
Adjustable prompt strength and denoising steps
LoRA model integration for specialized results
Speed-quality tradeoff with 'go_fast' optimization

Use Cases

•Creating custom artwork from text descriptions
•Editing existing photos via precise inpainting
•Generating style-consistent image variations
•Prototyping visual concepts with fast iterations

⚙️Input Parameters

prompt

string

Prompt for generated image. If you include the `trigger_word` used in the training process you are more likely to activate the trained object, style, or concept in the resulting image.

image

string

Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.

mask

string

Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.

aspect_ratio

string

Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode

height

integer

Height of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation

width

integer

Width of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation

prompt_strength

number

Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image

model

string

Which model to run inference with. The dev model performs best with around 28 inference steps but the schnell model only needs 4 steps.

num_outputs

integer

Number of outputs to generate

num_inference_steps

integer

Number of denoising steps. More steps can give more detailed images, but take longer.

guidance_scale

number

Guidance scale for the diffusion process. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5

seed

integer

Random seed. Set for reproducible generation

output_format

string

Format of the output images

output_quality

integer

Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs

disable_safety_checker

boolean

Disable safety checker for generated images.

go_fast

boolean

Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16

megapixels

string

Approximate number of megapixels for generated image

lora_scale

number

Determines how strongly the main LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.

extra_lora

string

Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'

extra_lora_scale

number

Determines how strongly the extra LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.

💡Usage Examples

Example 1

Input Parameters

{
  "model": "dev",
  "prompt": "Professional photoshoot of an RGN subject in classic 1960s glamour style, inspired by vintage Playboy covers. The subject is posed gracefully on an ornate, golden velvet chaise lounge, evoking old-Hollywood elegance. She wears a form-fitting strapless black cocktail dress with lace side panels and a sweetheart neckline that accentuates the hourglass silhouette. Her legs are crossed casually yet confidently, one arm draped elegantly over the armrest, the other resting lightly on her thigh.\n\nHer blonde, shoulder-length hair is styled in voluminous retro curls, parted to the side, with soft waves framing her face. Her makeup features bold red lipstick, black winged eyeliner, and flawless matte skin — a true nod to 1962 glamour.\n\nThe scene is softly lit with warm studio lighting, simulating a classic film grain texture. The background features vintage wallpaper in gold tones and subtle vignetting around the edges, adding depth and nostalgic character.\n\nRendered in a cinematic editorial tone, shot on a Canon R5 with an 85mm prime lens, using soft diffusion filters to mimic the magazine cover aesthetics of the 60s. The image is styled as a retro magazine cover layout, with subtle paper texture and authentic typography.",
  "go_fast": false,
  "lora_scale": 0.89,
  "megapixels": "1",
  "num_outputs": 4,
  "aspect_ratio": "1:1",
  "output_format": "png",
  "guidance_scale": 3.46,
  "output_quality": 80,
  "prompt_strength": 0.8,
  "extra_lora_scale": 1,
  "num_inference_steps": 28
}

Output Results

https://replicate.delivery/xezq/2OcSWVgc0uIvH1HGorxpa8dct0WsVfSRf33zediwGLfEza9SB/out-0.png

https://replicate.delivery/xezq/lp9x0KVFfsWWHCouCvf3NZ6rGlkfuXpD5eSL9iKoJdDGza9SB/out-1.png

https://replicate.delivery/xezq/fi9bydOMq1T4C6dPQT7gQWOfKQ2WzEcEX7fdazJXDONjZteSB/out-2.png

https://replicate.delivery/xezq/HWDZmVCzKfxRG6Ga9Exo3jRi1pge6RtZQKwvSMeBpg4jZteSB/out-3.png

Quick Actions

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Technical Specifications

Hardware Type: H100
Run Count: 52
Commercial Use: Unknown/Restricted
Platform: Replicate

Related Keywords

Text-to-Image GenerationImage InpaintingLoRA IntegrationImage EditingMultiple ResolutionsCustom ArtworkPhoto EditingVisual Concept Prototyping

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