PASD Image to Image

fal-ai/pasd
Pixel-Aware Diffusion Model for Realistic Image Super-Resolution and Personalized Stylization
Inference
Commercial use

About

Perform high-quality image super-resolution using PASD-SDXL.

The model applies AI-enhanced super-resolution with:

  • Pixel-aware stable diffusion
  • ControlNet guidance for structure preservation
  • Wavelet color correction for natural results

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/pasd", {
  input: {
    image_url: "https://fal.media/files/rabbit/JlBgYUyQRS3zxiBu_B4fM.png"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In case your app is running in an environment where you cannot set environment variables, you can set the API Key manually as a client configuration.
import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

3. Queue#

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/pasd", {
  input: {
    image_url: "https://fal.media/files/rabbit/JlBgYUyQRS3zxiBu_B4fM.png"
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/pasd", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/pasd", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Read more about file handling in our file upload guide.

5. Schema#

Input#

image_url string* required

Input image to super-resolve

scale integer

Upscaling factor (1-4x) Default value: 2

steps integer

Number of inference steps (10-50) Default value: 25

guidance_scale float

Guidance scale for diffusion (1.0-20.0) Default value: 7

conditioning_scale float

ControlNet conditioning scale (0.1-1.0) Default value: 0.8

prompt string

Additional prompt to guide super-resolution Default value: ""

negative_prompt string

Negative prompt to avoid unwanted artifacts Default value: "blurry, dirty, messy, frames, deformed, dotted, noise, raster lines, unclear, lowres, over-smoothed, painting, ai generated"

{
  "image_url": "https://fal.media/files/rabbit/JlBgYUyQRS3zxiBu_B4fM.png",
  "scale": 2,
  "steps": 25,
  "guidance_scale": 7,
  "conditioning_scale": 0.8,
  "negative_prompt": "blurry, dirty, messy, frames, deformed, dotted, noise, raster lines, unclear, lowres, over-smoothed, painting, ai generated"
}

Output#

images list<Image>* required

The generated super-resolved images

timings Timings

Timing information for different processing stages

{
  "images": [
    {
      "file_size": 2010575,
      "height": 1024,
      "file_name": "4732818e18b542ca8dc3f0e6c1775ac8.png",
      "content_type": "image/png",
      "url": "https://v3.fal.media/files/koala/ncEbdm4Ig6dAGBp-3dR63_4732818e18b542ca8dc3f0e6c1775ac8.png",
      "width": 1024
    }
  ]
}

Other types#

Image#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

file_data string

File data

width integer

The width of the image in pixels.

height integer

The height of the image in pixels.