Sector Keypad 2 Image Generation

Sector Keypad 2 is a powerful tool for image generation and modification. Ready to experience the power of AI? Start your journey here!

Platform: Replicate

Image InpaintingText-to-ImageLoRA AdaptationAspect Ratio Control

43 runs

H100

License Check Required

🚀Function Overview

A diffusion-based image generation model that creates or modifies images using text prompts, supports inpainting with masks, applies LoRA adaptations, and allows extensive customization of aspect ratios and generation parameters.

Key Features

Text-to-image generation using prompts
Image-to-image transformation with prompt strength control
Inpainting with mask support
Aspect ratio and resolution customization
Multiple model variations for speed/quality trade-offs
LoRA weight integration for style/object adjustments
Quantization options for faster generation

Use Cases

•Generating images from text descriptions
•Editing existing images through inpainting
•Applying specific styles/concepts via LoRA adaptations
•Product photography simulation
•Creating variations of images with custom aspect ratios

⚙️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": "A standalone white rectangular (sectorKeypad), placed upright on a clean, neutral background. The device is centered, photographed under soft natural light. Minimalistic, high-resolution product photography style, everything in sharp focus. In the image, a human hand is seen pressing a button on a white digital keypad. The keypad is mounted on a white wall, and the hand is positioned on the right side of the keypad. The keypad has a total of 12 buttons, each marked with a number from 0 to 9, and also includes the numbers 1, 2, and 3. The background of the image reveals a room with a white ceiling and a window, providing a stark contrast to the white wall and keypad. The image does not contain any discernible text. The overall scene suggests an interaction with a digital interface, possibly for security or access control purposes.",
  "go_fast": false,
  "lora_scale": 0.8,
  "megapixels": "1",
  "num_outputs": 4,
  "aspect_ratio": "5:4",
  "output_format": "png",
  "guidance_scale": 3,
  "output_quality": 100,
  "prompt_strength": 0.85,
  "extra_lora_scale": 1,
  "num_inference_steps": 33
}

Output Results

https://replicate.delivery/xezq/0oo3tpSTrKLsFxLcNYf7XT5ntWDtGQEohu99ard0E8te2UtUA/out-0.png

https://replicate.delivery/xezq/3BZEll6uIdayFxk3OJQFOyQsn4yeqG3UgHn1lPWSpfc92UtUA/out-1.png

https://replicate.delivery/xezq/O0prBjECJZLyGFr6AURxgZ3RZLeRyzRAW5ilW4Np4Cpe2UtUA/out-2.png

https://replicate.delivery/xezq/9pgSRFjL7HaxLNpfSxDdgrdtW5lc9brG0VF1lPHOz7se2UtUA/out-3.png

Quick Actions

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Technical Specifications

Hardware Type: H100
Run Count: 43
Commercial Use: Unknown/Restricted
Platform: Replicate

Related Keywords

Text-to-Image GenerationImage InpaintingLoRA AdaptationAspect Ratio ControlImage-to-Image TransformationCustomizable ParametersQuantization OptionsProduct Photography Simulation

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