1const axios = require('axios');
3const fs = require('fs');
4const path = require('path');
6async function toB64(imgPath) {
7    const data = fs.readFileSync(path.resolve(imgPath));
8    return Buffer.from(data).toString('base64');
11const api_key = "YOUR API-KEY";
12const url = "";
14const data = {
15  "image": "toB64('/sd-img2img-input.jpeg')",
16  "samples": 1,
17  "prompt": "A fantasy landscape, trending on artstation, mystical sky",
18  "negative_prompt": "nude, disfigured, blurry",
19  "scheduler": "DDIM",
20  "num_inference_steps": 25,
21  "guidance_scale": 10.5,
22  "strength": 0.75,
23  "seed": 98877465625,
24  "img_width": 512,
25  "img_height": 512,
26  "base64": false
29(async function() {
30    try {
31        const response = await, data, { headers: { 'x-api-key': api_key } });
32        console.log(;
33    } catch (error) {
34        console.error('Error:',;
35    }
HTTP Response Codes
200 - OKImage Generated
401 - UnauthorizedUser authentication failed
404 - Not FoundThe requested URL does not exist
405 - Method Not AllowedThe requested HTTP method is not allowed
406 - Not AcceptableNot enough credits
500 - Server ErrorServer had some issue with processing


imageimage *

Input Image.

samplesint ( default: 1 ) Affects Pricing

Number of samples to generate.

min : 1,

min : 4

promptstr *

Prompt to render

negative_promptstr ( default: None )

Prompts to exclude, eg. 'bad anatomy, bad hands, missing fingers'

schedulerenum:str ( default: DDIM )

Type of scheduler.

Allowed values:

num_inference_stepsint ( default: 20 ) Affects Pricing

Number of denoising steps.

min : 20,

min : 100

guidance_scalefloat ( default: 7.5 )

Scale for classifier-free guidance

min : 0.1,

min : 25

strengthfloat ( default: 1 )

How much to transform the reference image

min : 0.1,

min : 1

seedint ( default: -1 )

Seed for image generation.

img_widthenum:int ( default: 512 ) Affects Pricing

Image resolution.

Allowed values:

img_heightenum:int ( default: 512 ) Affects Pricing

Image resolution.

Allowed values:

base64boolean ( default: 1 )

Base64 encoding of the output image.

To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.

Stable Diffusion Img2Img

Stable Diffusion Img2Img is a transformative AI model that's revolutionizing the way we approach image-to-image conversion. This model harnesses the power of machine learning to turn concepts into visuals, refine existing images, and translate one image to another with text-guided precision. It's an invaluable asset for creatives, marketers, and developers seeking to push the boundaries of digital imagery.

At the heart of Stable Diffusion Img2Img is a robust algorithm capable of understanding and manipulating visual content at a granular level. It takes an existing image and, guided by textual prompts, morphs it into a new creation that aligns with the user's vision. This model excels in tasks such as style transfer, detail enhancement, and subject transformation, all while maintaining the integrity of the original composition.


  1. Text-Guided Imagery: Integrates textual prompts to steer the image transformation process, ensuring outputs are aligned with user intent.

  2. Seamless Style Transfers: Adapts the style of one image to another, enabling a smooth transition that feels natural and intentional..

  3. Detail Enhancement:Amplifies the details within images, bringing clarity and vibrance to visual elements.

  4. Creative Flexibility: Offers a wide range of possibilities, from subtle alterations to complete thematic overhauls..

Use Cases

  1. Creative Artwork: Artists can evolve their work, experimenting with different styles and motifs without starting from scratch.

  2. Marketing Material: Marketers can tailor images to fit brand narratives, ensuring consistency across campaigns.

  3. Product Design: Designers can visualize product variations quickly, streamlining the development process.

  4. Entertainment Media: Content creators in film and gaming can modify and enhance visual assets to fit evolving storylines.

  5. Educational Tools: Educators can create custom visuals to aid in teaching complex concepts.