tommoore515/pix2pix_tf_albedo2pbrmaps – Run with an API on Replicate

tommoore515 / pix2pix_tf_albedo2pbrmaps

pix2pix model for predicting pbr texture maps from an albedo texture

Cold

Public
7.1K runs
L40S
GitHub
License

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=tommoore515/pix2pix_tf_albedo2pbrmaps

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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e",
  {
    input: {
      model: "albedo2normal",
      imagepath: "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg"
    }
  }
);

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

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

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 tommoore515/pix2pix_tf_albedo2pbrmaps using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "tommoore515/pix2pix_tf_albedo2pbrmaps:21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e",
    input={
        "model": "albedo2normal",
        "imagepath": "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg"
    }
)
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 tommoore515/pix2pix_tf_albedo2pbrmaps 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": "21bd96b6e69f40e54502d67798f9025ab9e4a9e08f2a1b51dde5131b129a825e",
    "input": {
      "model": "albedo2normal",
      "imagepath": "https://replicate.delivery/mgxm/f659f510-534d-4d31-a96d-4c2eac6cda19/Diagonal_cedar.jpg"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.5 seconds

Tweak itReport

Examples

View more examples

Run time and cost

This model costs approximately $0.00098 to run on Replicate, or 1020 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 L40S GPU hardware. Predictions typically complete within 1 seconds.

Readme

This is an implementation of Tensorflow’s pix2pix trained on a dataset of pbr materials.

pix2pix is a general purpose conditional adversarial network for image-to-image translation prediction. There are 4 separate models intended to be used to generate each of the texture maps needed for a Unity Standard Shader PBR Material.

example