SUPIR Upscaler

A Powerful Image Upscaler

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More Information About SUPIR Upscaler fal.ai Model

SUPIR Upscaler fal.ai

SUPIR Upscaler fal.ai is an AI model on fal.ai that provides SUPIR Upscaler's model effect (A Powerful Image Upscaler), which can be used instantly with this SUPIR Upscaler model. fal.ai supports a free trial of the SUPIR Upscaler model, and also provides paid use of the SUPIR Upscaler. Support call SUPIR Upscaler model through api, including Node.js, Python, http.

SUPIR Upscaler fal.ai Url

https://fal.ai/models/fal-ai/supir

SUPIR Upscaler API

Here's how the SUPIR Upscaler API supports the program languages:

1. Calling the API #
Install the client #

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

npm install --save @fal-ai/serverless-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 * as fal from "@fal-ai/serverless-client"; const result = await fal.subscribe("fal-ai/supir", { input: { image_url: "https://storage.googleapis.com/falserverless/gallery/NOCA_Mick-Thompson.resized.resized.jpg" }, logs: true, onQueueUpdate: (update) => { if (update.status === "IN_PROGRESS") { update.logs.map((log) => log.message).forEach(console.log); } }, });
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 * as fal from "@fal-ai/serverless-client"; fal.config({ credentials: "YOUR_FAL_KEY" });
Protect your API Key

When running code on the client-side (e.g. in a browser, mobile app or GUI applications), make sure to not expose your FAL_KEY . Instead, use a server-side proxy to make requests to the API. For more information, check out our server-side integration guide .

3. 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 * as fal from "@fal-ai/serverless-client"; // Upload a file (you can get a file reference from an input element or a drag-and-drop event) const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" }); const url = await fal.storage.upload(file); // Use the URL in your request const result = await fal.subscribe("fal-ai/supir", { image_url: url });
Auto uploads

The client will auto-upload the file for you if you pass a binary object (e.g. File , Data ).

Read more about file handling in our file upload guide .

4. Schema #
Input #
image_url * string

The URL of the image to be upscaled.

model_type ModelTypeEnum

The model type to use. Q is the default and is recommended for most use cases. Default value: "Q"

Possible values: "Q", "F"

upscale integer

Upsampling ratio of given inputs. Default value: 2

tile boolean

Whether to tile or not. Default is False.

tile_size integer

Tile size. Default is 1024. Default value: 1024

tile_stride integer

Tile stride. Default is 512. Default value: 512

tile_vae boolean

Whether to tile VAE or not. Default is False.

encoder_tile_size integer

VAE Encoder tile size. Default is 512. Default value: 512

decoder_tile_size integer

VAE Decoder tile size. Default is 64. Default value: 64

min_size float

Minimum resolution of output images. Default value: 1024

edm_steps integer

Number of steps for EDM Sampling Schedule. Default value: 50

use_llava boolean

Use LLaVA model to get captions. Default is False, thus if a prompt is not provide the empty prompt will be used

a_prompt string

Additive positive prompt for the inputs. Default value: "hyper detailed, maximum detail, 32k, Color Grading, ultra HD, extreme meticulous detailing, skin pore detailing, hyper sharpness, perfect"

n_prompt string

Negative prompt for the inputs. Default value: "blurring, dirty, messy, worst quality, low quality, frames, watermark, signature, jpeg artifacts, deformed, lowres, over-smooth"

color_fix_type ColorFixTypeEnum

Color Correction Method Default value: "Wavelet"

Possible values: "None", "AdaIn", "Wavelet"

s_stage1 integer

Control Strength of Stage1 (negative means invalid). Default value: -1

s_churn float

Original churn hy-param of EDM. Default value: 5

s_noise float

Original noise hy-param of EDM. Default value: 1.003

s_cfg float

Classifier-free guidance scale for prompts. Default value: 7.5

s_stage2 float

Control Strength of Stage2. Default value: 1

linear_CFG boolean

Linearly (with sigma) increase CFG from 'spt_linear_CFG' to s_cfg.

linear_s_stage2 boolean

Linearly (with sigma) increase s_stage2 from 'spt_linear_s_stage2' to s_stage2.

spt_linear_CFG float

Start point of linearly increasing CFG. Default value: 1

spt_linear_s_stage2 float

Start point of linearly increasing s_stage2.

seed integer

Seed for reproducibility. Different seeds will make slightly different results.

per_tile_llava_prompt boolean

Whether to use LLaVA prompt per tile or not. This will only be used if no prompt is provided and use_llava is true. Default is false

{ "image_url": "https://storage.googleapis.com/falserverless/gallery/NOCA_Mick-Thompson.resized.resized.jpg", "model_type": "Q", "upscale": 2, "tile_size": 1024, "tile_stride": 512, "encoder_tile_size": 512, "decoder_tile_size": 64, "min_size": 1024, "edm_steps": 50, "a_prompt": "hyper detailed, maximum detail, 32k, Color Grading, ultra HD, extreme meticulous detailing, skin pore detailing, hyper sharpness, perfect", "n_prompt": "blurring, dirty, messy, worst quality, low quality, frames, watermark, signature, jpeg artifacts, deformed, lowres, over-smooth", "color_fix_type": "None", "s_stage1": -1, "s_churn": 5, "s_noise": 1.003, "s_cfg": 7.5, "s_stage2": 1, "spt_linear_CFG": 1 }
Output #
image * Image

The generated image file info.

seed * integer

The seed used for the generation.

{ "image": { "url": "", "content_type": "image/png", "file_name": "z9RV14K95DvU.png", "file_size": 4404019, "width": 1024, "height": 1024 } }

SUPIR Upscaler online free

SUPIR Upscaler fal.ai is an online trial and call api platform, which integrates SUPIR Upscaler's modeling effects, including api services, and provides a free online trial of SUPIR Upscaler, you can try SUPIR Upscaler online for free by clicking the link below.

SUPIR Upscaler online free url in fal.ai:

https://fal.ai/models/fal-ai/supir

SUPIR Upscaler install

SUPIR Upscaler is an open source model from GitHub that offers a free installation service, and any user can find SUPIR Upscaler on GitHub to install. At the same time, fal.ai provides the effect of SUPIR Upscaler install, users can directly use SUPIR Upscaler installed effect in fal.ai for debugging and trial. It also supports api for free installation.

SUPIR Upscaler install url in fal.ai:

https://fal.ai/models/fal-ai/supir

Url of SUPIR Upscaler

SUPIR Upscaler fal.ai Url

Provider of SUPIR Upscaler fal.ai

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