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Enterprise: Blip Diffusion Endpoint

Overview​

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

Blip-Diffusion endpoint result
caution

Make sure you add your s3 details for image_editing server, so you can receive image generated in your bucket. Images generated without s3 details being added will be delete after 24hours

Request​

--request POST 'https://modelslab.com/api/v1/enterprise/image_editing/blip_diffusion' \

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

Body Attributes​

ParameterDescription
keyYour API Key used for request authorization
promptText prompt with description of the things you want in the image to be generated
negative_promptItems you don't want in the image
tasktask to execute. It accept zeroshot, controlnet_generation and controlnet_scribble_generation. Default is "zeroshot
condition_imageRequired when task is zeroshot
condition_subjectRequired when task is zeroshot . It is the subject from the condition image
target_subjectObject to expected from the result
style_subjectIt is the subject from style image. Required when task is controlnet_generation or controlnet_scribble_generation
controlnet_condition_imageImage 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.
widthMax Height: Width: 512 x 512
heightMax Height: Height: 512 x 512
guidance_scaleOptional. Scale for classifier-free guidance (minimum: 1; maximum: 20). Default is 8
stepsNumber of denoising steps (minimum: 1; maximum: 50) Default is 20
seedSeed is used to reproduce results, same seed will give you same image in return again. Pass null for a random number.
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.

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​

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://modelslab.com/api/v1/enterprise/image_editing/blip_diffusion", requestOptions)
  .then(response => response.text())
  .then(result => console.log(result))
  .catch(error => console.log('error', error));

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
    }
}