tengfei-wang/hfgi – Run with an API on Replicate

tengfei-wang / hfgi

High-Fidelity GAN Inversion for Image Attribute Editing

Cold

Public
22.2K runs
T4
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=tengfei-wang/hfgi

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 tengfei-wang/hfgi using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "tengfei-wang/hfgi:7a67b1861633a89e4ba600d39dd4cb447ce06091833cc9df13ecdb078c1e3f64",
  {
    input: {
      image: "https://replicate.delivery/mgxm/caf4c15f-fe0e-406a-a62b-f2700f427910/00044.jpg",
      edit_degree: 1.5,
      edit_attribute: "smile"
    }
  }
);

// 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 tengfei-wang/hfgi using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "tengfei-wang/hfgi:7a67b1861633a89e4ba600d39dd4cb447ce06091833cc9df13ecdb078c1e3f64",
    input={
        "image": "https://replicate.delivery/mgxm/caf4c15f-fe0e-406a-a62b-f2700f427910/00044.jpg",
        "edit_degree": 1.5,
        "edit_attribute": "smile"
    }
)
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 tengfei-wang/hfgi 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": "tengfei-wang/hfgi:7a67b1861633a89e4ba600d39dd4cb447ce06091833cc9df13ecdb078c1e3f64",
    "input": {
      "image": "https://replicate.delivery/mgxm/caf4c15f-fe0e-406a-a62b-f2700f427910/00044.jpg",
      "edit_degree": 1.5,
      "edit_attribute": "smile"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Tweak itReport

This output was created using a different version of the model, tengfei-wang/hfgi:1e8ae7ea.

Examples

View more examples

Run time and cost

This model costs approximately $0.0011 to run on Replicate, or 909 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 T4 GPU hardware. Predictions typically complete within 5 seconds.

Readme

High-Fidelity GAN Inversion for Image Attribute Editing

Update: We released the inference code and the pre-trained model on Oct. 31. The training code is coming soon.

paper | project website | demo video

Introduction

We present a novel high-fidelity GAN inversion framework that enables attribute editing with image-specific details well-preserved (e.g., background, appearance and illumination).

Citation

If you find this work useful for your research, please cite:

@article{wang2021HFGI,
      author = {Tengfei Wang and Yong Zhang and Yanbo Fan and Jue Wang and Qifeng Chen},
      title = {High-Fidelity GAN Inversion for Image Attribute Editing}, 
      journal = {arxiv:2109.06590},  
      year = {2021}
}