Unlock the full potential of generative AI with Segmind. Create stunning visuals and innovative designs with total creative control. Take advantage of powerful development tools to automate processes and models, elevating your creative workflow.
Gain greater control by dividing the creative process into distinct steps, refining each phase.
Customize at various stages, from initial generation to final adjustments, ensuring tailored creative outputs.
Integrate and utilize multiple models simultaneously, producing complex and polished creative results.
Deploy Pixelflows as APIs quickly, without server setup, ensuring scalability and efficiency.
Each parameter of the model controls a specific aspect of the furniture staging process. Here's a breakdown:
prompt:
This describes the scene or subject you want to stage. Write a detailed description of how the staged furniture or design should look.
main_image:
The primary image of the room or space where the furniture will be staged. Ensure the URL is accessible and points to a clear, high-quality image.
overlay_image:
The secondary image containing the furniture or staging items to overlay on the main image. Provide the URL of the furniture/staging image.
main_image_mask:
A mask for the main image. This defines areas to focus on for staging (e.g., walls, floors). If not provided, staging might be applied globally.
overlay_image_mask (optional):
steps:
This determines the number of processing steps. Higher values lead to better quality but take longer.
seed:
Sets a random seed for reproducibility. Change this if you want different variations of the same setup.
guidance:
Controls how strictly the output adheres to the prompt. Higher values ensure the output matches your prompt but can reduce creativity.
image_format:
Specifies the format of the output image. Options are usually png
, jpeg
, etc. Choose png
for lossless quality.
image_quality:
Sets the quality of the output image. Higher values produce better quality but larger file sizes.
Prepare Your Inputs
Make sure all inputs are ready:
Images:
main_image
and overlay_image
to a cloud service or use an accessible URL.Prompt:
SDXL Img2Img is used for text-guided image-to-image translation. This model uses the weights from Stable Diffusion to generate new images from an input image using StableDiffusionImg2ImgPipeline from diffusers
Take a picture/gif and replace the face in it with a face of your choice. You only need one image of the desired face. No dataset, no training
CodeFormer is a robust face restoration algorithm for old photos or AI-generated faces.
Take a picture/gif and replace the face in it with a face of your choice. You only need one image of the desired face. No dataset, no training