Inpainting Endpoint

Overview

Inpainting API is used to change (inpaint) some part of an image according to specific requirements, based on trained or on public models. Pass the appropriate request parameters to the endpoint.

This endpoint generates and returns an image from an image and a mask passed with their URLs in the request together with a model's ID.

You can also add your description of the desired result by passing prompt and negative prompt.

Request

--request POST 'https://modelslab.com/api/v6/images/inpaint' \

Make a POST request to https://modelslab.com/api/v6/images/inpaint endpoint and pass the required parameters as a request body.

Watch the Inpaint Community Model Endpoint Demo video to see it in action Postman.

Attributes

Parameter	Description	Values
key	Your API Key used for request authorization.	string
model_id	The ID of the model to be used. It can be a public model or one you have trained.	id
prompt	A text description of what you want in the generated image.	string
negative_prompt	Items you don't want in the image.	string
init_image	Link to the initial image to be used as a reference.	url
mask_image	Link to the mask image for inpainting.	url
width	The width of the image. Maximum value is 1024 pixels.	integer
height	The height of the image. Maximum value is 1024 pixels.	integer
samples	The number of images to be returned in the response. The maximum value is 4.	integer
steps	The number of denoising steps. values range from 1 to 20, and any value above 20 will be capped at 20.	integer
safety_checker	A checker for NSFW images. If detected, such images will be replaced by a blank image. Default is "yes".	"yes"/"no"
safety_checker_type	How to modify the image if NSFW content is found. Default is "sensitive_content_text". Options: "blur", "sensitive_content_text", "pixelate", "black".	"blur", "sensitive_content_text", "pixelate", "black"
enhance_prompt	Enhance prompts for better results. Default is "yes". Options: "yes"/"no".	"yes"/"no"
enhance_style	Allows you to set the style of the image for better results. Available styles include:	`enhance`, `cinematic-diva`, `nude`, `nsfw`, `sex`, `abstract-expressionism`, `academia`, `action-figure`, `adorable-3d-character`, `adorable-kawaii`, `art-deco`, `art-nouveau`, `astral-aura`, `avant-garde`, `baroque`, `bauhaus-style-poster`, `blueprint-schematic-drawing`, `caricature`, `cel-shaded-art`, `character-design-sheet`, `classicism-art`, `color-field-painting`, `colored-pencil-art`, `conceptual-art`, `constructivism`, `cubism`, `dadaism`, `dark-fantasy`, `dark-moody-atmosphere`, `dmt-art`, `doodle-art`, `double-exposure`, `dripping-paint-splatter`, `expressionism`, `faded-polaroid-photo`, `fauvism`, `flat-2d`, `fortnite-style`, `futurism`, `glitchcore`, `glo-fi`, `googie-style`, `graffiti-art`, `harlem-renaissance-art`, `high-fashion`, `idyllic`, `impressionism`, `infographic-drawing`, `ink-dripping-drawing`, `japanese-ink-drawing`, `knolling-photography`, `light-cheery-atmosphere`, `logo-design`, `luxurious-elegance`, `macro-photography`, `mandola-art`, `marker-drawing`, `medievalism`, `minimalism`, `neo-baroque`, `neo-byzantine`, `neo-futurism`, `neo-impressionism`, `neo-rococo`, `neoclassicism`, `op-art`, `ornate-and-intricate`, `pencil-sketch-drawing`, `pop-art-2`, `rococo`, `silhouette-art`, `simple-vector-art`, `sketchup`, `steampunk-2`, `surrealism`, `suprematism`, `terragen`, `tranquil-relaxing-atmosphere`, `sticker-designs`, `vibrant-rim-light`, `volumetric-lighting`, `watercolor`, `whimsical-and-playful`, `sharp`, `masterpiece`, `photograph`, `negative`, `cinematic`, `ads-advertising`, `ads-automotive`, `ads-corporate`, `ads-fashion-editorial`, `ads-food-photography`, `ads-gourmet-food-photography`, `ads-luxury`, `ads-real-estate`, `ads-retail`, `abstract`, `abstract-expressionism`, `art-deco`, `art-nouveau`, `constructivist`, `cubist`, `expressionist`, `graffiti`, `hyperrealism`, `impressionist`, `pointillism`, `pop-art`, `psychedelic`, `renaissance`, `steampunk`, `surrealist`, `typography`, `watercolor`, `futuristic-biomechanical`, `futuristic-biomechanical-cyberpunk`, `futuristic-cybernetic`, `futuristic-cybernetic-robot`, `futuristic-cyberpunk-cityscape`, `futuristic-futuristic`, `futuristic-retro-cyberpunk`, `futuristic-retro`, `futuristic-sci-fi`, `futuristic-vaporwave`, `game-bubble`, `game-cyberpunk`, `game-fighting`, `game-gta`, `game-mario`, `game-minecraft`, `game-pokemon`, `game-retro-arcade`, `game-retro`, `game-rpg-fantasy`, `game-strategy`, `game-streetfighter`, `game-zelda`, `misc-architectural`, `misc-disco`, `misc-dreamscape`, `misc-dystopian`, `misc-fairy-tale`, `misc-gothic`, `misc-grunge`, `misc-horror`, `misc-kawaii`, `misc-lovecraftian`, `misc-macabre`, `misc-manga`, `misc-metropolis`, `misc-minimalist`, `misc-monochrome`, `misc-nautical`, `misc-space`, `misc-stained-glass`, `misc-techwear-fashion`, `misc-tribal`, `misc-zentangle`, `papercraft-collage`, `papercraft-flat-papercut`, `papercraft-kirigami`, `papercraft-paper-mache`, `papercraft-paper-quilling`, `papercraft-papercut-collage`, `papercraft-papercut-shadow-box`, `papercraft-stacked-papercut`, `papercraft-thick-layered-papercut`, `photo-alien`, `photo-film-noir`, `photo-glamour`, `photo-hdr`, `photo-iphone-photographic`, `photo-long-exposure`, `photo-neon-noir`, `photo-silhouette`, `photo-tilt-shift`, `3d-model`, `analog-film`, `anime`, `cinematic`, `comic-book`, `craft-clay`, `digital-art`, `fantasy-art`, `isometric`, `line-art`, `lowpoly`, `neonpunk`, `origami`, `photographic`, `pixel-art`, `texture`
guidance_scale	Scale for classifier-free guidance. Minimum 1, Maximum 20.	integer
tomesd	Enable tomesd to generate images quickly. Default is "yes". Options: "yes"/"no".	"yes"/"no"
use_karras_sigmas	Use Keras sigmas to generate images. Produces nice results. Default is "yes". Options: "yes"/"no".	"yes"/"no"
algorithm_type	Used in the DPMSolverMultistepScheduler scheduler. Default is "none". Options: "dpmsolver+++".	"dpmsolver+++"
vae	Use a custom VAE for generating images. Default is null.	null
lora_strength	Specify the strength of the LoRa model you're using. Range from 0.1 to 1, or comma-separated values.	string
lora_model	Pass LoRa model ID. Multiple LoRa models supported; comma-separated values. Example: "contrast-fix, yae-miko-genshin".	string
strength	Prompt strength when using the initial image. Range from 0 to 1.	float
ip_adapter_id	IP adapter ID. Supported IDs are "ip-adapter_sdxl", "ip-adapter_sd15", "ip-adapter-plus-face_sd15".	string
ip_adapter_scale	Scale for the IP adapter. Should be between 0 and 1.	float
ip_adapter_image	Valid image URL for the IP adapter.	url
scheduler	Use this to set a scheduler.	scheduler
seed	Used to reproduce results. The same seed will generate the same image again. Pass null for a random number.	integer
webhook	Set a URL to receive a POST API call once image generation is complete.	url
track_id	This ID is returned in the response to the webhook API call and is used to identify the request.	id
clip_skip	Clip Skip. Minimum 1, Maximum 8.	integer
base64	Get the response as a base64 string. Pass init_image and mask_image as base64 strings to get a base64 response. Default is "no".	"yes"/"no"
temp	Create a temporary image link valid for 24 hours.	"yes"/"no"

Schedulers

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

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

Example

Body

Body
{
  "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",
  "steps": "21",
  "safety_checker": "no",
  "enhance_prompt": "yes",
  "guidance_scale": 7.5,
  "strength": 0.7,
  "scheduler": "UniPCMultistepScheduler",
  "lora_model": null,
  "tomesd": "yes",
  "use_karras_sigmas": "yes",
  "vae": null,
  "lora_strength": null,
  "embeddings_model": null,
  "seed": null,
  "webhook": null,
  "track_id": null
} 

Request

JS
PHP
NODE
PYTHON
JAVA

var myHeaders = new Headers();
myHeaders.append("Content-Type", "application/json");

var raw = JSON.stringify({
  "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",
  "steps": "21",
  "safety_checker": "no",
  "enhance_prompt": "yes",
  "guidance_scale": 7.5,
  "strength": 0.7,
  "scheduler": "PNDMScheduler",
  "lora_model": null,
  "tomesd": "yes",
  "use_karras_sigmas": "yes",
  "vae": null,
  "lora_strength": null,
  "embeddings_model": null,
  "seed": null,
  "webhook": null,
  "track_id": null
});

var requestOptions = {
  method: 'POST',
  headers: myHeaders,
  body: raw,
  redirect: 'follow'
};

fetch("https://modelslab.com/api/v6/images/inpaint", requestOptions)
  .then(response => response.text())
  .then(result => console.log(result))
  .catch(error => console.log('error', error));

<?php

$payload = [
  "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", 
  "steps" => "21", 
  "safety_checker" => "no", 
  "enhance_prompt" => "yes", 
  "guidance_scale" => 7.5, 
  "strength" => 0.7, 
  "scheduler" => "PNDMScheduler",
   "lora_model" => null,
  "tomesd" => "yes",
  "use_karras_sigmas" => "yes",
  "vae" => null,
  "lora_strength" => null,
  "embeddings_model" => null,
  "seed" => null, 
  "webhook" => null, 
  "track_id" => null 
];

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://modelslab.com/api/v6/images/inpaint',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_POSTFIELDS =>  json_encode($payload),
  CURLOPT_HTTPHEADER => array(
    'Content-Type: application/json'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

var request = require('request');
var options = {
  'method': 'POST',
  'url': 'https://modelslab.com/api/v6/images/inpaint',
  'headers': {
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    "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",
    "steps": "21",
    "safety_checker": "no",
    "enhance_prompt": "yes",
    "guidance_scale": 7.5,
    "strength": 0.7,
    "scheduler": "PNDMScheduler",
    "lora_model": null,
    "tomesd": "yes",
    "use_karras_sigmas": "yes",
    "vae": null,
    "lora_strength": null,
    "embeddings_model": null,
    "seed": null,
    "webhook": null,
    "track_id": null
  })
};

request(options, function (error, response) {
  if (error) throw new Error(error);
  console.log(response.body);
});

import requests
import json

url = "https://modelslab.com/api/v6/images/inpaint"

payload = json.dumps({
  "key": "",
  "prompt": "a cat sitting on a bench",
  "negative_prompt": None,
  "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",
  "steps": "21",
  "safety_checker": "no",
  "enhance_prompt": "yes",
  "guidance_scale": 7.5,
  "strength": 0.7,
  "scheduler": "PNDMScheduler",
  "seed": None,
  "lora_model": null,
  "tomesd": "yes",
  "use_karras_sigmas": "yes",
  "vae": None,
  "lora_strength": None,
  "embeddings_model": None,
  "webhook": None,
  "track_id": None
})

headers = {
  'Content-Type': 'application/json'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

OkHttpClient client = new OkHttpClient().newBuilder()
  .build();
MediaType mediaType = MediaType.parse("application/json");
RequestBody body = RequestBody.create(mediaType, "{\n    \"key\": \"\",\n  \"model_id\": \"your_model_id\",\n  \"prompt\": \"a cat sitting on a bench\",\n  \"negative_prompt\": null,\n  \"init_image\": \"https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png\",\n  \"mask_image\": \"https://raw.githubusercontent.com/CompVis/stable-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png\",\n  \"width\": \"512\",\n  \"height\": \"512\",\n  \"samples\": \"1\",\n  \"num_inference_steps\": \"21\",\n  \"safety_checker\": \"no\",\n  \"enhance_prompt\": \"yes\",\n  \"guidance_scale\": 7.5,\n  \"strength\": 0.7,\n  \"scheduler\": \"PNDMScheduler\",\n  \"lora_model\": \"lora_model_id\",\n  \"tomesd\": \"yes\",\n  \"use_karras_sigmas\": \"yes\",\n  \"vae\": null,\n  \"lora_strength\": null,\n  \"embeddings_model\": null,\n  \"seed\": null,\n  \"webhook\": null,\n  \"track_id\": null\n}");
Request request = new Request.Builder()
  .url("https://modelslab.com/api/v6/images/inpaint")
  .method("POST", body)
  .addHeader("Content-Type", "application/json")
  .build();
Response response = client.newCall(request).execute();

Response

Example Response
{
  "status": "success",
  "generationTime": 20.970642805099487,
  "id": 13446970,
  "output": [
    "https://pub-8b49af329fae499aa563997f5d4068a4.r2.dev/generations/dc639bd6-d605-42c7-950e-48c531124d0d-0.png"
  ],
  "meta": {
    "prompt": " a cat sitting on a bench DSLR photography, sharp focus, Unreal Engine 5, Octane Render, Redshift, ((cinematic lighting)), f/1.4, ISO 200, 1/160s, 8K, RAW, unedited, symmetrical balance, in-frame",
    "model_id": "midjourney-v4-painta",
    "scheduler": "PNDMScheduler",
    "safetychecker": "no",
    "negative_prompt": " ((out of frame)), ((extra fingers)), mutated hands, ((poorly drawn hands)), ((poorly drawn face)), (((mutation))), (((deformed))), (((tiling))), ((naked)), ((tile)), ((fleshpile)), ((ugly)), (((abstract))), blurry, ((bad anatomy)), ((bad proportions)), ((extra limbs)), cloned face, glitchy, ((extra breasts)), ((double torso)), ((extra arms)), ((extra hands)), ((mangled fingers)), ((missing breasts)), (missing lips), ((ugly face)), ((fat)), ((extra legs))",
    "W": 512,
    "H": 512,
    "guidance_scale": 7.5,
    "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",
    "steps": 21,
    "n_samples": 1,
    "full_url": "no",
    "upscale": "no",
    "seed": 1343687916,
    "outdir": "out",
    "file_prefix": "dc639bd6-d605-42c7-950e-48c531124d0d"
  }
}

Overview​

Request​

Watch the Inpaint Community Model Endpoint Demo video to see it in action Postman.​

Attributes​

Schedulers​

Example​

Body​

Request​

Response​

Overview

Request

Watch the Inpaint Community Model Endpoint Demo video to see it in action Postman.

Attributes

Schedulers

Example

Body

Request

Response