POST/v1/sdxl-openpose
1const axios = require('axios');
2
3const fs = require('fs');
4const path = require('path');
5
6async function toB64(imgPath) {
7    const data = fs.readFileSync(path.resolve(imgPath));
8    return Buffer.from(data).toString('base64');
9}
10
11const api_key = "YOUR API-KEY";
12const url = "https://api.segmind.com/v1/sdxl-openpose";
13
14const data = {
15  "image": "toB64('https://segmind-sd-models.s3.amazonaws.com/outputs/sdxl_input_openpose.jpg')",
16  "prompt": "A ballerina dancing on stage with two legs",
17  "negative_prompt": "low quality, ugly, painting",
18  "samples": 1,
19  "scheduler": "Euler a",
20  "num_inference_steps": 30,
21  "guidance_scale": 7.5,
22  "seed": 65312568548,
23  "controlnet_scale": 0.5,
24  "base64": false
25};
26
27(async function() {
28    try {
29        const response = await axios.post(url, data, { headers: { 'x-api-key': api_key } });
30        console.log(response.data);
31    } catch (error) {
32        console.error('Error:', error.response.data);
33    }
34})();
RESPONSE
image/jpeg
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
Expand

Attributes

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: 30 ) 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

controlnet_scalefloat ( default: 7.5 )

Scale for classifier-free guidance

min : 0,

min : 1

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.

SDXL Open Pose

SDXL OpenPose Model, a groundbreaking AI tool that redefines human pose estimation. This model synergizes the robust control features of ControlNet with the precision of OpenPose, offering an unparalleled level of accuracy and control in human pose analysis within the Stable Diffusion framework.

The SDXL OpenPose Model is engineered with a sophisticated blend of ControlNet's control mechanisms and OpenPose's advanced pose estimation algorithms. This powerful combination processes visual data with remarkable accuracy, enabling real-time detection and manipulation of human poses.

Advantages

  1. Pose Manipulation: Allows for real-time adjustments, offering immediate control over human poses.

  2. Broad Application Spectrum: Adaptable across various industries, from entertainment to health, due to its extensive capabilities.

Use Cases

  1. Animation and Film Production:Enables animators to craft realistic human movements and postures, adding authenticity to animated features.

  2. Gaming: Enhances gaming experiences with more natural character movements and in-game interactions.

  3. Immersive VR and AR: Improves the realism of AR and VR by accurately translating real-world movements to digital avatars.