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('')",
16  "prompt": "photo of beautiful age 18 girl, pink hair, beautiful, close up, young, dslr, 8k, 4k, ultrarealistic, realistic, natural skin, textured skin",
17  "negative_prompt": "painting, drawing, sketch, cartoon, anime, manga, render, CG, 3d, watermark, signature, label, long neck",
18  "samples": 1,
19  "scheduler": "Euler a",
20  "num_inference_steps": 30,
21  "guidance_scale": 7.5,
22  "seed": 452361789,
23  "strength": 0.9,
24  "base64": false
27(async function() {
28    try {
29        const response = await, data, { headers: { 'x-api-key': api_key } });
30        console.log(;
31    } catch (error) {
32        console.error('Error:',;
33    }
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

promptstr *

Prompt to render

negative_promptstr ( default: None )

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

samplesint ( default: 1 ) Affects Pricing

Number of samples to generate.

min : 1,

min : 4

schedulerenum:str ( default: DPM2 Karras )

Type of scheduler.

Allowed values:

num_inference_stepsint ( default: 25 ) Affects Pricing

Number of denoising steps.

min : 20,

min : 100

guidance_scalefloat ( default: 7.5 )

Scale for classifier-free guidance

min : 1,

min : 25

seedint ( default: -1 )

Seed for image generation.

min : -1,

min : 999999999999999

strengthfloat ( default: 7.5 )

Scale for classifier-free guidance

min : 0,

min : 0.99

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.

Segmind Stable Diffusion 1B (SSD-1B) Img2Img

Segmind Stable Diffusion 1B (SSD-1B) Img2Img is a cutting-edge AI model that is reshaping the landscape of image-to-image transformations. Leveraging advanced machine learning techniques, SSD-1B excels at converting conceptual prompts into vivid visuals, refining images, and facilitating seamless image translations guided by nuanced text inputs. It stands as a pivotal tool for creatives, marketers, and software developers who are looking to break new ground in the realm of visual content creation.

At the core of SSD-1B Img2Img is a sophisticated algorithm adept at intricate visual content manipulation. With the ability to take an existing image and, through text-driven prompts, transform it into a new piece that resonates with the creator's intent, the modle shines in performing style transfers, enhancing details, and altering subjects while preserving the essence of the original image.


  1. Text-Directed Transformation: Employs text prompts to direct the transformation process, aligning the output closely with the creator's objectives .

  2. Fluid Style Adaptation:Capably adjusts the style from one image to another, ensuring transitions are coherent and purposeful.

  3. Enhanced Detailing:Elevates the intricacies within images, enhancing definition and vibrancy.

  4. Expansive Creative Range: Provides a broad spectrum of creative possibilities, ranging from nuanced tweaks to complete conceptual overhauls.

Use Cases

  1. Creative Artwork: Enables artists to push the boundaries of their work, exploring new styles and themes effortlessly.

  2. Marketing Material: Assists marketers in crafting images that are in sync with brand stories, maintaining uniformity across all visual communications.

  3. Product Design: Allows designers to swiftly generate multiple product iterations, accelerating the design process.

  4. Entertainment Media: Supports content creators in the entertainment sector to adjust and refine visual elements to match dynamic narratives.

  5. Educational Tools: Aids educators in developing bespoke visual aids that enhance the learning experience for complex subjects.