tripathiarpan20/pixel-portrait-lcm-anythingv3.0

tripathiarpan20 / pixel-portrait-lcm-anythingv3.0

Convert any image to pixel portraits (Updated 1 year, 7 months ago)

Cold

Public
21 runs
L40S
GitHub
License

Iterate in playground

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=tripathiarpan20/pixel-portrait-lcm-anythingv3.0

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";
import fs from "node:fs";

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

Run tripathiarpan20/pixel-portrait-lcm-anythingv3.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "tripathiarpan20/pixel-portrait-lcm-anythingv3.0:0c69710a5c14db6b86e37e3dd04f36c7c78d289836460f061f5345e1eb39a854",
  {
    input: {
      seed: 42,
      image: "",
      prompt: "A person, pixel art",
      strength: 0.5,
      controlnet_end: 1,
      guidance_scale: 8,
      negative_prompt: "bad quality, low quality",
      controlnet_scale: 0.8,
      controlnet_start: 0,
      canny_low_threshold: 0.31,
      num_inference_steps: 10,
      canny_high_threshold: 0.78
    }
  }
);

// 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 tripathiarpan20/pixel-portrait-lcm-anythingv3.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "tripathiarpan20/pixel-portrait-lcm-anythingv3.0:0c69710a5c14db6b86e37e3dd04f36c7c78d289836460f061f5345e1eb39a854",
    input={
        "seed": 42,
        "image": "",
        "prompt": "A person, pixel art",
        "strength": 0.5,
        "controlnet_end": 1,
        "guidance_scale": 8,
        "negative_prompt": "bad quality, low quality",
        "controlnet_scale": 0.8,
        "controlnet_start": 0,
        "canny_low_threshold": 0.31,
        "num_inference_steps": 10,
        "canny_high_threshold": 0.78
    }
)
print(output)

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 tripathiarpan20/pixel-portrait-lcm-anythingv3.0 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": "tripathiarpan20/pixel-portrait-lcm-anythingv3.0:0c69710a5c14db6b86e37e3dd04f36c7c78d289836460f061f5345e1eb39a854",
    "input": {
      "seed": 42,
      "image": "",
      "prompt": "A person, pixel art",
      "strength": 0.5,
      "controlnet_end": 1,
      "guidance_scale": 8,
      "negative_prompt": "bad quality, low quality",
      "controlnet_scale": 0.8,
      "controlnet_start": 0,
      "canny_low_threshold": 0.31,
      "num_inference_steps": 10,
      "canny_high_threshold": 0.78
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

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

Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

Running on Anything v3.0 with pixel-portrait LoRA by Nerijs & Latent Consistency Model (LCM) LoRA.

Uses Canny ControlNet with Img2Img pipeline.