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Enterprise: Text to Image Endpoint

Overview

This endpoint is used to create an image from a text prompt based on trained or on public models.

You can make an API call using your trained models as well as any public model.

tip

You can find a list of the public models available and their IDs here.

This endpoint generates and returns an image from a text passed in the request body.

Text to image endpoint result

Request

--request POST 'https://stablediffusionapi.com/api/v1/enterprise/text2img' \

Make a POST request to https://stablediffusionapi.com/api/v1/enterprise/text2img endpoint and pass the required parameters as a request body.

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

Body Attributes

ParameterDescription
keyYour enterprise API Key used for request authorization
model_idThe ID of the model to be used. It can be public or your trained model.
promptText prompt with description of the things you want in the image to be generated
negative_promptItems you don't want in the image
widthMax Height: Width: 1024x1024
heightMax Height: Width: 1024x1024
samplesNumber of images to be returned in response. The maximum value is 4.
num_inference_stepsNumber of denoising steps (minimum: 1; maximum: 50)
safety_checkerA checker for NSFW images. If such an image is detected, it will be replaced by a blank image.
safety_checker_typeModify image if NSFW images are found; default: sensitive_content_text, options: blur/sensitive_content_text/pixelate/black
enhance_promptEnhance prompts for better results; default: yes, options: yes/no
seedSeed is used to reproduce results, same seed will give you same image in return again. Pass null for a random number.
guidance_scaleScale for classifier-free guidance (minimum: 1; maximum: 20)
multi_lingualAllow multi lingual prompt to generate images. Set this to "yes" if you use a language different from English in your text prompts.
panoramaSet this parameter to "yes" to generate a panorama image.
self_attentionIf you want a high quality image, set this parameter to "yes". In this case the image generation will take more time.
upscaleSet this parameter to "yes" if you want to upscale the given image resolution two times (2x). If the requested resolution is 512 x 512 px, the generated image will be 1024 x 1024 px.
embeddings_modelUse it to pass an embeddings model.
tomesdEnable tomesd to generate images: gives really fast results, default: yes, options: yes/no
use_karras_sigmasUse keras sigmas to generate images. gives nice results, default: yes, options: yes/no
algorithm_typeUsed in DPMSolverMultistepScheduler scheduler, default: none, options: dpmsolver+++
vaeuse custom vae in generating images default: null
lora_strengthStrength of lora model you are using. If using multi lora, pass each values as comma saparated
lora_modelmulti lora is supported, pass comma saparated values . Example contrast-fix,yae-miko-genshin
schedulerUse it to set a scheduler.
webhookSet an URL to get a POST API call once the image generation is complete.
track_idThis ID is returned in the response to the webhook API call. This will be used to identify the webhook request.
loadbalancerEnable load balancer; options: yes/no, default: no.
clip_skipClip Skip (minimum: 1; maximum: 8)
base64Get response as base64 string, default: "no", options: yes/no
highres_fixhighres fix for generated image, default: "no", options: yes/no
tempCreate temp image link. This link is valid for 24 hours. temp: yes, options: yes/no
info

To use the load balancer, you need to have more than 1 server. Pass the first server's API key, and it will handle the load balancing with the other servers.

tip

You can also use multi Lora. Just make sure to pass comma saparated lora model ids to the lora_model as "more_details,animie" in the request body.

Multi_lingual Supported Languages

If you use a language different from English in you text prompts, pass the "multi_lingual" parameter with "yes" value in the request body. This will trigger an automatic language detection and translation during the processing of your request.

The following languages are supported:

Arabic (ar_AR), Czech (cs_CZ), German (de_DE), English (en_XX), Spanish (es_XX), Estonian (et_EE), Finnish (fi_FI), French (fr_XX), Gujarati (gu_IN), Hindi (hi_IN), Italian (it_IT), Japanese (ja_XX), Kazakh (kk_KZ), Korean (ko_KR), Lithuanian (lt_LT), Latvian (lv_LV), Burmese (my_MM), Nepali (ne_NP), Dutch (nl_XX), Romanian (ro_RO), Russian (ru_RU), Sinhala (si_LK), Turkish (tr_TR), Vietnamese (vi_VN), Chinese (zh_CN), Afrikaans (af_ZA), Azerbaijani (az_AZ), Bengali (bn_IN), Persian (fa_IR), Hebrew (he_IL), Croatian (hr_HR), Indonesian (id_ID), Georgian (ka_GE), Khmer (km_KH), Macedonian (mk_MK), Malayalam (ml_IN), Mongolian (mn_MN), Marathi (mr_IN), Polish (pl_PL), Pashto (ps_AF), Portuguese (pt_XX), Swedish (sv_SE), Swahili (sw_KE), Tamil (ta_IN), Telugu (te_IN), Thai (th_TH), Tagalog (tl_XX), Ukrainian (uk_UA), Urdu (ur_PK), Xhosa (xh_ZA), Galician (gl_ES), Slovene (sl_SI)

Schedulers

This endpoint also supports schedulers. Use the "scheduler" parameter in the request body to pass a specific scheduler from the list below:

  • DDPMScheduler
  • DDIMScheduler
  • PNDMScheduler
  • LMSDiscreteScheduler
  • EulerDiscreteScheduler
  • EulerAncestralDiscreteScheduler
  • DPMSolverMultistepScheduler
  • HeunDiscreteScheduler
  • KDPM2DiscreteScheduler
  • DPMSolverSinglestepScheduler
  • KDPM2AncestralDiscreteScheduler
  • UniPCMultistepScheduler
  • DDIMInverseScheduler
  • DEISMultistepScheduler
  • IPNDMScheduler
  • KarrasVeScheduler
  • ScoreSdeVeScheduler
  • LCMScheduler

Example

Body

Body
{
"key": "enterprise_api_key",
"model_id": "model_id",
"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",
"negative_prompt": "painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime",
"width": "512",
"height": "512",
"samples": "1",
"num_inference_steps": "20",
"safety_checker": "no",
"enhance_prompt": "yes",
"seed": null,
"guidance_scale": 7.5,
"multi_lingual": "no",
"panorama": "no",
"self_attention": "no",
"upscale": "no",
"embeddings_model": null,
"lora_model": null,
"clip_skip": "2",
"tomesd": "yes",
"use_karras_sigmas": "yes",
"vae": null,
"lora_strength": null,
"scheduler": "UniPCMultistepScheduler",
"webhook": null,
"track_id": null
}

Request

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

var raw = JSON.stringify({
"key": "",
"model_id": "model_id",
"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",
"negative_prompt": "painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime",
"width": "512",
"height": "512",
"samples": "1",
"num_inference_steps": "30",
"safety_checker": "no",
"enhance_prompt": "yes",
"seed": null,
"guidance_scale": 7.5,
"multi_lingual": "no",
"panorama": "no",
"self_attention": "no",
"upscale": "no",
"embeddings_model": null,
"lora_model": null,
"tomesd": "yes",
"use_karras_sigmas": "yes",
"vae": null,
"lora_strength": null,
"scheduler": "UniPCMultistepScheduler",
"webhook": null,
"track_id": null
});

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

fetch("https://stablediffusionapi.com/api/v1/enterprise/text2img", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));

Response

{
"status": "success",
"generationTime": 2.920767068862915,
"id": 302455,
"output": [
"https://d1okzptojspljx.cloudfront.net/generations/05c3260d-6a2e-4aa5-82f0-e952f2a5fa10-0.png"
],
"meta": {
"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",
"model_id": "runwayml/stable-diffusion-v1-5",
"negative_prompt": "painting, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, ugly, blurry, bad anatomy, bad proportions, extra limbs, cloned face, skinny, glitchy, double torso, extra arms, extra hands, mangled fingers, missing lips, ugly face, distorted face, extra legs, anime ((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, glitchy, ((extra breasts)), ((double torso)), ((extra arms)), ((extra hands)), ((mangled fingers)), ((missing breasts)), (missing lips), ((ugly face)), ((fat)), ((extra legs))",
"scheduler": "UniPCMultistepScheduler",
"revision": "fp16",
"safetychecker": "no",
"W": 512,
"H": 512,
"enable_attention_slicing": "true",
"file_prefix": "05c3260d-6a2e-4aa5-82f0-e952f2a5fa10",
"guidance_scale": 7.5,
"seed": 1793745243,
"steps": 20,
"n_samples": 1,
"upscale": "no",
"multi_lingual": "no",
"panorama": "no",
"self_attention": "no",
"embeddings": null,
"lora": null,
"outdir": "out",
"vae": "stabilityai/sd-vae-ft-mse"
}
}