Inpainting - ModelsLab

Request

Make a POST request to below endpoint and pass the required parameters as a request body.

curl

--request POST 'https://modelslab.com/api/v1/enterprise/pony/inpaint' \

To use the load balancer, you need to have more than 1 server. Pass the first server’s API key, and it will handle the load balancing with the other servers.

Body

json

{  
  "key": "enterprise_api_key",  
  "model_id": "your_model_id",  
  "prompt": "a cat sitting on a bench",  
  "negative_prompt": null,  
  "init_image": "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png",  
  "mask_image": "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png",  
  "width": "512",  
  "height": "512",  
  "samples": "1",  
  "num_inference_steps": "30",  
  "safety_checker": "no",   
  "guidance_scale": 7.5,  
  "strength": 0.7,  
  "scheduler": "PNDMScheduler",  
  "seed": null,  
  "lora_model": null,  
  "tomesd": "yes",  
  "use_karras_sigmas": "yes",  
  "vae": null,  
  "lora_strength": null,  
  "webhook": null,  
  "track_id": null
}

Schedulers

This endpoint also supports schedulers. Use the “scheduler” parameter in the request body to pass a specific scheduler from the list below:

EulerDiscreteScheduler
EulerAncestralDiscreteScheduler
LMSDiscreteScheduler
HeunDiscreteScheduler
KDPM2DiscreteScheduler
KDPM2AncestralDiscreteScheduler
DPMSolverMultistepScheduler
DPMSolverSinglestepScheduler
DDIMScheduler
DDPMScheduler
PNDMScheduler
UniPCMultistepScheduler
DEISMultistepScheduler
LCMScheduler
IPNDMScheduler

Body Attributes

Parameter	Description
key	Your enterprise API Key used for request authorization
model_id	The ID of the model to be used. It can be public or your trained model.
prompt	Text prompt with description of the things you want in the image to be generated
negative_prompt	Items you don’t want in the image
init_image	Link to the Initial Image
mask_image	Link to the mask image for inpainting
width	Max Height: Width: 1024x1024
height	Max Height: Width: 1024x1024
samples	Number of images to be returned in response. The maximum value is 4.
num_inference_steps	Number of denoising steps, The value accepts 21,31,41.
safety_checker	A checker for NSFW images. If such an image is detected, it will be replaced by a blank image; default: yes, options: yes/no
safety_checker_type	Modify image if NSFW images are found; default: sensitive_content_text, options: blur/sensitive_content_text/pixelate/black
enhance_prompt	Enhance prompts for better results; default: yes, options: yes/no
guidance_scale	Scale for classifier-free guidance (minimum: 1; maximum: 20)
strength	Prompt strength when using init image. 1.0 corresponds to full destruction of information in the init image.
tomesd	Enable tomesd to generate images: gives really fast results, default: yes, options: yes/no
use_karras_sigmas	Use keras sigmas to generate images. gives nice results, default: yes, options: yes/no
algorithm_type	Used in DPMSolverMultistepScheduler scheduler, default: none, options: dpmsolver+++
vae	Use custom vae in generating images default: null
lora_strength	Specify the strength of the LoRa model you’re using. If using multiple LoRa, provide each value as a comma-separated range from minimum 0.1 to maximum 1.
lora_model	Multi lora is supported, pass comma saparated values . Example contrast-fix,yae-miko-genshin
scheduler	Use it to set a scheduler.
seed	Seed is used to reproduce results, same seed will give you same image in return again. Pass null for a random number.
webhook	Set an URL to get a POST API call once the image generation is complete.
track_id	This ID is returned in the response to the webhook API call. This will be used to identify the webhook request.
clip_skip	Clip Skip (minimum: 1; maximum: 8)
base64	Get response as base64 string, pass init_image, mask_image as base64 string, to get base64 response. default: “no”, options: yes/no
temp	Create temp image link. This link is valid for 24 hours. temp: yes, options: yes/no

​Request

​Body

​Schedulers

​Body Attributes

Request

Body

Schedulers

Body Attributes