meta/ic_gan:b0c63bd9 – Run with an API on Replicate

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meta /ic_gan:b0c63bd9

Input

image

*file

Raw input image-instance. NOTE: The image will be preprocessed with a center crop and a 256x256 resizing before extracting its features and conditioning the model.

gen_model

string

Select type of IC-GAN model. "icgan" is conditioned on the input image. "cc_icgan" is conditioned on both input image and a conditional_class

Default: "icgan"

conditional_class

string

Choose conditional class. Only valid for gen_model=cc_icgan

num_samples

*integer

number of samples generated

seed

integer

seed=0 means no seed

Default: 0

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

npx create-replicate --model=meta/ic_gan

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

const output = await replicate.run(
  "meta/ic_gan:b0c63bd91773fff7ad9b7fbaf7cace294e397fc1e95340cca974c148bacdf97d",
  {
    input: {
      seed: 0,
      gen_model: "icgan",
      num_samples: 1,
      conditional_class: "Afghan_hound"
    }
  }
);

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

output = replicate.run(
    "meta/ic_gan:b0c63bd91773fff7ad9b7fbaf7cace294e397fc1e95340cca974c148bacdf97d",
    input={
        "seed": 0,
        "gen_model": "icgan",
        "num_samples": 1,
        "conditional_class": "Afghan_hound"
    }
)
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 meta/ic_gan 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": "meta/ic_gan:b0c63bd91773fff7ad9b7fbaf7cace294e397fc1e95340cca974c148bacdf97d",
    "input": {
      "seed": 0,
      "gen_model": "icgan",
      "num_samples": 1,
      "conditional_class": "Afghan_hound"
    }
  }' \
  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.