SD 1.5

You can use adapters to fix hands, fingers, faces or any deformaties. One of the most commonly used application of Adaper is to lock face and generate same face in any environments. Other applications include fixing hands, fingers and adding details to a specific image.

To use adapters, you will need to pass three extra parameters - adapter name, ip adapter image and scale of the adapter

Tip

Use only face as input image instead of the full body while using face adapters.
Supports all checkpoint models on SD 1.5

Python
JavaScript
php

import requests
import json
url = "https://api.imagepipeline.io/sd/text2image/v1"
headers = {
    "API-Key": "Your API Key"
}
data = {
    "model_id":  "sd1.5", 
    "prompt": "cinematic still woman holding mango juice. emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy holding a glass of mango juice,",
    "negative_prompt": "error, cropped, worst quality, low quality, duplicate, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, blurry, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck",
    "num_inference_steps": 20,
    "ip_adapter": ["ip-adapter-plus_sd15"],
    "ip_adapter_scale": [0.6],
    "ip_adapter_style_images": [], //For multi-ip-adapter
    "ip_adapter_image": "https://www.keep-calm-and-eat-ice-cream.com/wp-content/uploads/2022/08/Ice-cream-sundae-hero-11.jpg",
    "samples": 1,
    "guidance_scale": 7.5,
    "width": 512,
    "height": 512
}    
   
response = requests.post(url, headers=headers, data=json.dumps(data))
print(response.json())

const url = "https://api.imagepipeline.io/sd/text2image/v1";
const headers = {
  "API-Key": "Your API Key",
  "Content-Type": "application/json"
};
const data = {
  "model_id":  "sd1.5",
  "prompt": "cinematic still woman holding mango juice. emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy holding a glass of mango juice,",
  "negative_prompt": "error, cropped, worst quality, low quality, duplicate, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, blurry, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck",
  "num_inference_steps": 20,
  "ip_adapter": ["ip-adapter-plus_sd15"],
  "ip_adapter_scale": [0.6],
  "ip_adapter_style_images": [], //For multi-ip-adapter
  "ip_adapter_image": "https://www.keep-calm-and-eat-ice-cream.com/wp-content/uploads/2022/08/Ice-cream-sundae-hero-11.jpg",  
  "samples": 1,
  "guidance_scale": 7.5,
  "width": 512,
  "height": 512
};
fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(data)
})
.then(response => response.json())
.then(data => console.log(data))
.catch((error) => console.error('Error:', error));

<?php
$url = "https://api.imagepipeline.io/sd/text2image/v1";
$headers = array(
  "API-Key: Your-API-Key",
  "Content-Type: application/json"
);
$data = array(
  "model_id" =>  "sd1.5",
  "prompt" => "cinematic still woman holding mango juice. emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy holding a glass of mango juice,",
  "negative_prompt" => "error, cropped, worst quality, low quality, duplicate, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, deformed, blurry, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck",
  "num_inference_steps" => 20,
  "samples" => 1,
  "guidance_scale" => 7.5,
  "width" => 512,
  "height" => 512,
  "ip_adapter"=> ["ip-adapter-plus_sd15"],
  "ip_adapter_scale"=> [0.6],
  "ip_adapter_style_images"=> [], //For multi-ip-adapter
  "ip_adapter_image"=> "https://www.keep-calm-and-eat-ice-cream.com/wp-content/uploads/2022/08/Ice-cream-sundae-hero-11.jpg"
);
$ch = curl_init($url);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($data));
$response = curl_exec($ch);
if($response === FALSE){
  die(curl_error($ch));
}
$responseData = json_decode($response, TRUE);
curl_close($ch);
var_dump($responseData);
?>

JSON Parameters

Parameter	Permissible values	Notes
model_id	`str`	model_id can be found in models page. Filter by SD-1.5 models
prompt	`str, 75 tokens`	Check our Prompt Guide for tips
negative_prompt	`str, 75 tokens`	Check our Prompt Guide for tips
num_inference_steps	`int, [1-100]`	Noise is removed with each step, resulting in a higher-quality image over time. Ideal value 20-30
strength	`float, [0-1]`	Optional denoise strength
samples	`int, [1-4]`	Generates a maximum of 4 samples per API call
guidance_scale	`float, [1-20]`	Higher guidance scale prioritizes text prompt relevance but sacrifices image quality. Ideal value 7.5-12.5
width	`int`	Width in pixels. Lower than or equal to 512 for best results
height	`int`	Height in pixels. Lower than or equal to 512 for best results
ip_adapter	`str, array`	Model id of adapters to be used. You can add multiple by comma separated values. Allowed values are: `ip-adapter_sd15_light`, `ip-adapter_sd15`, `ip-adapter-plus_sd15`, `ip-adapter-plus-face_sd15`
ip_adapter_scale	`float, array[0-1]`	How much adapters should guide the generations. You can add multiple by comma separated values.
ip_adapter_image	`str`	Input image to the primary adapter model. Mostly used for face lock
ip_adapter_style_images	`str, array`	Images to be used by multi IP-adapters for usecases like style transfer or image mixing

Status

Your response will include a status.

If the status = SUCCESS, you will also have download_urls that will have the links to your generated image based on the number of samples you have entered. The maximum number of samples that can be generated is 4.
If the status = PENDING, you will receive a id. You can use the status endpoint to fetch your image using the id.
If the status = FAILURE, you will receive only an error message.

Endpoint: [GET]

https://api.imagepipeline.io/sd/text2image/v1/status/{{id}}

Pass the API-Key as the authorization in the header.

Input
Output

{
  "model_id":  "2e05152a-82c1-4b51-9aae-4475b76fad6a",
  "prompt": "cinematic still woman holding mango juice. emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope",
  "negative_prompt": "error, cropped, worst quality, low quality, duplicate, bad proportions, incomplete subject",
  "num_inference_steps": 20,
  "samples": 4,
  "guidance_scale": 7.5,
  "width": 512,
  "height": 512,
  "ip_adapter": ["ip-adapter-plus-face_sd15"],
  "ip_adapter_image": "https://t4.ftcdn.net/jpg/06/44/30/09/360_F_644300965_7asrChyeknn9fA0GuYrmIUFSBHR5HTpo.jpg",
  "ip_adapter_scale": [0.6]
} 

 {
        "download_urls": [
        "https://f005.backblazeb2.com/b2api/v2/b...",
    ]
    }