philz1337x/clarity-lowres-upscaler – Run with an API on Replicate

philz1337x / clarity-lowres-upscaler

Low resolution image Upscaler and Enhancer. For images between 64 - 512 px. Use at ClarityAI.co Twitter/X: @philz1337x

Cold

Public
2.3K runs
A100 (80GB)
GitHub
Paper

Run with an API

Playground API Examples README Versions

Input

Run this model in Node.js with one line of code:

npx create-replicate --model=philz1337x/clarity-lowres-upscaler

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run philz1337x/clarity-lowres-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "philz1337x/clarity-lowres-upscaler:894c3ac7eac4be245853b67c1eaa61e29560dcb37592fb52da68a9a12ce8ec4a",
  {
    input: {
      steps: 32,
      prompt: "best quality",
      strength: 1,
      output_size: 1024,
      negative_prompt: "blur, lowres, bad anatomy, bad hands, cropped, worst quality"
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run philz1337x/clarity-lowres-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "philz1337x/clarity-lowres-upscaler:894c3ac7eac4be245853b67c1eaa61e29560dcb37592fb52da68a9a12ce8ec4a",
    input={
        "steps": 32,
        "prompt": "best quality",
        "strength": 1,
        "output_size": 1024,
        "negative_prompt": "blur, lowres, bad anatomy, bad hands, cropped, worst quality"
    }
)

# The philz1337x/clarity-lowres-upscaler model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/philz1337x/clarity-lowres-upscaler/api#output-schema
    print(item)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run philz1337x/clarity-lowres-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "894c3ac7eac4be245853b67c1eaa61e29560dcb37592fb52da68a9a12ce8ec4a",
    "input": {
      "steps": 32,
      "prompt": "best quality",
      "strength": 1,
      "output_size": 1024,
      "negative_prompt": "blur, lowres, bad anatomy, bad hands, cropped, worst quality"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/philz1337x/clarity-lowres-upscaler@sha256:894c3ac7eac4be245853b67c1eaa61e29560dcb37592fb52da68a9a12ce8ec4a \
  -i 'steps=32' \
  -i 'prompt="best quality"' \
  -i 'strength=1' \
  -i 'output_size=1024' \
  -i 'negative_prompt="blur, lowres, bad anatomy, bad hands, cropped, worst quality"'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/philz1337x/clarity-lowres-upscaler@sha256:894c3ac7eac4be245853b67c1eaa61e29560dcb37592fb52da68a9a12ce8ec4a
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "steps": 32,
      "prompt": "best quality",
      "strength": 1,
      "output_size": 1024,
      "negative_prompt": "blur, lowres, bad anatomy, bad hands, cropped, worst quality"
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

No output yet! Press "Submit" to start a prediction.

Run time and cost

This model costs approximately $0.010 to run on Replicate, or 100 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia A100 (80GB) GPU hardware. Predictions typically complete within 8 seconds.

Readme

This model doesn't have a readme.