Image to Image Endpoint

• text2img
• img2img
• inpaint
• fetch
• system_load

Overview

Stable Diffusion V3 APIs Image2Image API generates an image from an image. Pass the appropriate request parameters to the endpoint to generate image from an image.

This endpoint generates and returns an image from an image passed with its URL in the request.

Together with the image you can add your description of the desired result by passing prompt and negative prompt.

Request

--request POST 'https://stablediffusionapi.com/api/v3/img2img' \

Make a POST request to https://stablediffusionapi.com/api/v3/img2img endpoint and pass the required parameters as a request body to the endpoint.

Watch the how-to video to see it in action.

Body Attributes

Parameter	Description
key	Your API Key used for request authorization
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
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. Available values: 21, 31, 41, 51.
safety_checker	A checker for NSFW images. If such an image is detected, it will be replaced by a blank image.
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.
seed	Seed is used to reproduce results, same seed will give you same image in return again. Pass null for a random number.
base64	Get response as base64 string, default: "no", options: yes/no
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.

Example

Body

Body

{
    "key": "",
    "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",
    "width": "512",
    "height": "512",
    "samples": "1",
    "num_inference_steps": "30",
    "safety_checker": "no",
    "enhance_prompt": "yes",
    "guidance_scale": 7.5,
    "strength": 0.7,
    "seed": null,
    "base64": "no",
    "webhook": null,
    "track_id": null
}

Request

JS

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

var raw = JSON.stringify({
  "key": "",
  "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",
  "width": "512",
  "height": "512",
  "samples": "1",
  "num_inference_steps": "30",
  "safety_checker": "no",
  "enhance_prompt": "yes",
  "guidance_scale": 7.5,
  "strength": 0.7,
  "base64": "no",
  "seed": null,
  "webhook": null,
  "track_id": null
});

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

fetch("https://stablediffusionapi.com/api/v3/img2img", requestOptions)
  .then(response => response.text())
  .then(result => console.log(result))
  .catch(error => console.log('error', error));

PHP

<?php

$payload = [
   "key" => "", 
   "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", 
   "width" => "512", 
   "height" => "512", 
   "samples" => "1", 
   "num_inference_steps" => "30", 
   "safety_checker" => "no", 
   "enhance_prompt" => "yes", 
   "guidance_scale" => 7.5, 
   "strength" => 0.7, 
   "seed" => null, 
   "base64" => "no",
   "webhook" => null, 
   "track_id" => null 
];

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://stablediffusionapi.com/api/v3/img2img',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_POSTFIELDS => json_encode($payload),
  CURLOPT_HTTPHEADER => array(
    'Content-Type: application/json'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

NODE

var request = require('request');
var options = {
  'method': 'POST',
  'url': 'https://stablediffusionapi.com/api/v3/img2img',
  'headers': {
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    "key": "",
    "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",
    "width": "512",
    "height": "512",
    "samples": "1",
    "num_inference_steps": "30",
    "safety_checker": "no",
    "enhance_prompt": "yes",
    "guidance_scale": 7.5,
    "strength": 0.7,
    "seed": null,
    "base64": "no",
    "webhook": null,
    "track_id": null
  })
};

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

PYTHON

import requests
import json

url = "https://stablediffusionapi.com/api/v3/img2img"

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",
  "width": "512",
  "height": "512",
  "samples": "1",
  "num_inference_steps": "30",
  "safety_checker": "no",
  "enhance_prompt": "yes",
  "guidance_scale": 7.5,
  "strength": 0.7,
  "base64": "no",
  "seed": None,
  "webhook": None,
  "track_id": None
})

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

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

print(response.text)

JAVA

OkHttpClient client = new OkHttpClient().newBuilder()
  .build();
MediaType mediaType = MediaType.parse("application/json");
RequestBody body = RequestBody.create(mediaType, "{\n    \"key\": \"\",\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    \"width\": \"512\",\n    \"height\": \"512\",\n    \"samples\": \"1\",\n    \"num_inference_steps\": \"30\",\n    \"safety_checker\": \"no\",\n    \"enhance_prompt\": \"yes\",\n    \"guidance_scale\": 7.5,\n    \"strength\": 0.7,\n    \"seed\": null,\n    \"webhook\": null,\n    \"track_id\": null\n}");
Request request = new Request.Builder()
  .url("https://stablediffusionapi.com/api/v3/img2img")
  .method("POST", body)
  .addHeader("Content-Type", "application/json")
  .build();
Response response = client.newCall(request).execute();

Response

Example Response

{
 "status": "success",
 "generationTime": 2.920767068862915,
 "id": 302455,
 "output": [
     "https://d1okzptojspljx.cloudfront.net/generations/05c3260d-6a2e-4aa5-82f0-e952f2a5fa10-0.png"
 ],
 "meta": {
     "H": 512,
     "W": 512,
     "enable_attention_slicing": "true",
     "file_prefix": "05c3260d-6a2e-4aa5-82f0-e952f2a5fa10",
     "guidance_scale": 7.5,
     "model": "runwayml/stable-diffusion-v1-5",
     "n_samples": 1,
     "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, (((skinny))), glitchy, ((extra breasts)), ((double torso)), ((extra arms)), ((extra hands)), ((mangled fingers)), ((missing breasts)), (missing lips), ((ugly face)), ((fat)), ((extra legs)), anime",
     "outdir": "out",
     "prompt": "ultra realistic close up portrait ((beautiful pale cyberpunk female with heavy black eyeliner)), blue eyes, shaved side haircut, hyper detail, cinematic lighting, magic neon, dark red city, Canon EOS R3, nikon, f/1.4, ISO 200, 1/160s, 8K, RAW, unedited, symmetrical balance, in-frame, 8K",
     "revision": "fp16",
     "safety_checker": "none",
     "seed": 1793745243,
     "steps": 20,
     "vae": "stabilityai/sd-vae-ft-mse"
 }
}