POST/v1/dminhk-dog-example-sdxl-lora
1const axios = require('axios');
2
3
4const api_key = "YOUR API-KEY";
5const url = "https://api.segmind.com/v1/dminhk-dog-example-sdxl-lora";
6
7const data = {
8  "prompt": "cute puppy dog excited",
9  "negative_prompt": "boring, poorly drawn, bad artist, (worst quality:1.4), simple background, uninspired, (bad quality:1.4), monochrome, low background contrast, background noise, duplicate, crowded, (nipples:1.2), big breasts",
10  "scheduler": "UniPC",
11  "num_inference_steps": 25,
12  "guidance_scale": 8,
13  "samples": 1,
14  "seed": 3426017487,
15  "img_width": 1024,
16  "img_height": 1024,
17  "base64": false,
18  "lora_scale": 1
19};
20
21(async function() {
22    try {
23        const response = await axios.post(url, data, { headers: { 'x-api-key': api_key } });
24        console.log(response.data);
25    } catch (error) {
26        console.error('Error:', error.response.data);
27    }
28})();
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


promptstr *

Prompt to render


negative_promptstr ( default: None )

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


schedulerenum:str ( default: UniPC )

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


samplesint ( default: 1 ) Affects Pricing

Number of samples to generate.

min : 1,

min : 4


seedint ( default: -1 )

Seed for image generation.


img_widthenum:int ( default: 1024 ) Affects Pricing

Width of the image.

Allowed values:


img_heightenum:int ( default: 1024 ) Affects Pricing

Height of the Image

Allowed values:


base64boolean ( default: 1 )

Base64 encoding of the output image.


lora_scalefloat ( default: 1 )

Scale of the lora

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.

Dog Example SDXL LoRA

The Dog Example SDXL LoRA, a specialized AI model within the Stable Diffusion XL framework, uniquely trained to enhance canine imagery. This model is based on LoRA adaptation weights, specifically trained using DreamBooth on a photograph of a dog. This training approach ensures the model's proficiency in accurately rendering canine features, textures, and expressions

Advantages

  1. Canine-Focused Imagery: Excellently captures the essence and details of dogs in images.

  2. High Precision:Trained on dog photos for enhanced accuracy in canine features.

  3. Versatile Applications: Suitable for various uses, from pet photography enhancement to creative dog-themed art.

Use Cases

  1. Pet Photography:Enhance the quality and detail of dog photographs.

  2. Veterinary Education: Create detailed canine images for educational purposes.

  3. Pet Care Industry: Ideal for creating visuals for pet care products and services.

  4. Advertising and Marketing: Use in campaigns or materials featuring dogs.