Blip Diffusion Endpoint

• v5/outpainting
• v5/blip_diffusion
• v5/magic_mix
• v5/depth2img
• v5/image_guided_editing
• v5/removebg_createmask
• v5/super_resolution
• v5/image_mixer
• v5/mixture-canvas
• v5/multiview
• v5/fashion

Overview

This endpoint allow you to perform blip diffusion on image passed. It works best for object

Request

--request POST 'https://stablediffusionapi.com/api/v5/blip_diffusion' \

Make a POST request to https://stablediffusionapi.com/api/v5/blip_diffusion endpoint and pass the required parameters as a request body to the endpoint.

Body Attributes

Parameter	Description
key	Your API Key used for request authorization
prompt	Text prompt with description of the things you want in the image to be generated
negative_prompt	Items you don't want in the image
task	task to execute. It accept zeroshot, controlnet_generation and controlnet_scribble_generation. Default is "zeroshot
condition_image	Required when task is zeroshot
condition_subject	Required when task is zeroshot . It is the subject from the condition image
target_subject	Object to expected from the result
style_subject	It is the subject from style image. Required when task is controlnet_generation or controlnet_scribble_generation
controlnet_condition_image	Image URL of the controlnet_condition_image image. Used when tasks is controlnet_generation or controlnet_scribble_generation. For the controlnet_scribble_generation task, we pass in the canny image url instead of just the image.
width	Max Height: Width: 512 x 512
height	Max Height: Height: 512 x 512
guidance_scale	Optional. Scale for classifier-free guidance (minimum: 1; maximum: 20). Default is 8
steps	Number of denoising steps (minimum: 1; maximum: 50) Default is 20
seed	Seed is used to reproduce results, same seed will give you same image in return again. Pass null for a random number.
webhook	Set an URL to get a POST API call once the image generation is complete.
track_id	This ID is returned in the response to the webhook API call. This will be used to identify the webhook request.

Example

Body

When task is zeroshot, the request will look like so;

Body

{
    "key":"",
    "seed":88888,
    "task":"zeroshot",
    "prompt":"on a marble table",
    "condition_image":"https://m.media-amazon.com/images/I/61qEOpxc1WL.jpg",
    "condition_subject":"teapot",
    "target_subject":"school bag",
    "guidance_scale":7.5,
    "steps":35,
    "height":512,
    "width":512,
    "webhook": null,
    "track_id": null 
}

When task is controlnet_generation, the request will look like so

Body

{
    "key":"",
    "seed":88888,
    "task":"controlnet_generation",
    "prompt":"on a marble table",
    "style_image":"https://m.media-amazon.com/images/I/61qEOpxc1WL.jpg",
    "controlnet_condition_image":"https://m.media-amazon.com/images/I/81ELJHbkafL._AC_SX569_.jpg",
    "style_subject":"teapot",
    "target_subject":"cup",
    "guidance_scale":10,
    "steps":35,
    "height":512,
    "width":512,
    "webhook": null,
    "track_id": null 
}

When task is controlnet_scribble_generation, the request will look like so

Body

{
    "key":"",
    "seed":88888,
    "task":"controlnet_generation",
    "prompt":"on a marble table",
    "style_image":"//huggingface.co/datasets/ayushtues/blipdiffusion_images/resolve/main/flower.jpg",
    "controlnet_condition_image":"https://huggingface.co/lllyasviel/sd-controlnet-scribble/resolve/main/images/bag.png",
    "style_subject":"flower",
    "target_subject":"bag",
    "guidance_scale":10,
    "steps":35,
    "height":512,
    "width":512,
    "webhook": null,
    "track_id": null 
}

Request

JS

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

var raw = JSON.stringify({
    "key":"",
    "seed":88888,
    "task":"zeroshot",
    "prompt":"on a marble table",
    "condition_image":"https://m.media-amazon.com/images/I/61qEOpxc1WL.jpg",
    "condition_subject":"teapot",
    "target_subject":"school bag",
    "guidance_scale":7.5,
    "steps":35,
    "height":512,
    "width":512,
    "webhook": null,
    "track_id": null
});

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

fetch("https://stablediffusionapi.com/api/v5/blip_diffusion", requestOptions)
  .then(response => response.text())
  .then(result => console.log(result))
  .catch(error => console.log('error', error));

PHP

<?php

$payload = [
    "key" => "",
    "seed" => 88888,
    "task" => "zeroshot",
    "prompt" => "on a marble table",
    "condition_image" => "https://m.media-amazon.com/images/I/61qEOpxc1WL.jpg",
    "condition_subject" => "teapot",
    "target_subject" => "school bag",
    "guidance_scale"=> 7.5,
    "steps"=>35,
    "height"=>512,
    "width" => 512,
    "webhook" => null,
    "track_id" => null 
];

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://stablediffusionapi.com/api/v5/blip_diffusion',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_POSTFIELDS => json_encode($payload),
  CURLOPT_HTTPHEADER => array(
    'Content-Type: application/json'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

NODE

var request = require('request');
var options = {
  'method': 'POST',
  'url': 'https://stablediffusionapi.com/api/v5/blip_diffusion',
  'headers': {
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    "key":"",
    "seed":88888,
    "task":"zeroshot",
    "prompt":"on a marble table",
    "condition_image":"https://m.media-amazon.com/images/I/61qEOpxc1WL.jpg",
    "condition_subject":"teapot",
    "target_subject":"school bag",
    "guidance_scale":7.5,
    "steps":35,
    "height":512,
    "width":512,
    "webhook": null,
    "track_id": null 
  })
};

request(options, function (error, response) {
  if (error) throw new Error(error);
  console.log(response.body);
});

PYTHON

import requests
import json

url = "https://stablediffusionapi.com/api/v5/blip_diffusion"

payload = json.dumps({
    "key":"",
    "seed":88888,
    "task":"zeroshot",
    "prompt":"on a marble table",
    "condition_image":"https://m.media-amazon.com/images/I/61qEOpxc1WL.jpg",
    "condition_subject":"teapot",
    "target_subject":"school bag",
    "guidance_scale":7.5,
    "steps":35,
    "height":512,
    "width":512,
    "webhook": None,
    "track_id": None
})

headers = {
  'Content-Type': 'application/json'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

JAVA

         OkHttpClient client = new OkHttpClient().newBuilder()
      .build();
    MediaType mediaType = MediaType.parse("application/json");
    RequestBody body = RequestBody.create(mediaType, "{\n    \"key\":\"bXagUMkX2VTOTc1Z2TAoU0Yh39N1TftQ8BmQCQzKM4Ng5G5qmufiCzX6Arnn\",\n    \"seed\":88888,\n    \"task\":\"zeroshot\",\n    \"prompt\":\"on a marble table\",\n    \"condition_image\":\"https://m.media-amazon.com/images/I/61qEOpxc1WL.jpg\",\n    \"condition_subject\":\"teapot\",\n    \"target_subject\":\"shoe\",\n    \"guidance_scale\":7.5,\n    \"steps\":35,\n    \"height\":512,\n    \"width\":512\n}");
    Request request = new Request.Builder()
      .url("https://stablediffusionapi.com/api/v5/blip_diffusion")
      .method("POST", body)
      .addHeader("Content-Type", "application/json")
      .build();
    Response response = client.newCall(request).execute();

Response

Example Response

{
    "status": "success",
    "generationTime": 3.270559072494507,
    "id": 563,
    "output": [
        "https://pub-3626123a908346a7a8be8d9295f44e26.r2.dev/generations/9c1e05cc-16f0-4a11-9900-a6edd56586dd.png.png"
    ],
    "meta": {
        "base64": "no",
        "file_prefix": "9c1e05cc-16f0-4a11-9900-a6edd56586dd.png",
        "guidance_scale": 7.5,
        "height": 512,
        "instant_response": "no",
        "neg_prompt": "over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, out of frame, ugly, bad anatomy, bad proportions, deformed, blurry, duplicate",
        "num_inference_steps": 35,
        "outdir": "out",
        "prompt": "on a marble table",
        "prompt_reps": 20,
        "prompt_strength": 1,
        "reference_image": "https://m.media-amazon.com/images/I/61qEOpxc1WL.jpg",
        "seed": 88888,
        "source_subject_category": "teapot",
        "sub_task": "zeroshot",
        "target_subject_category": "shoe",
        "temp": "no",
        "width": 512
    }
}