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yunjey / stargan-v2

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Cold

Public
103 runs
T4
GitHub
Paper
License

Run with an API

Playground API Examples README Versions

Prediction

yunjey/stargan-v2:fd6a430c610c91bae70b628065fcf64f66d41e69a1c5d0d53c763dded606ef91

Model

yunjey/stargan-v2:fd6a430c

x5dhidfspbgjzbiueb22bjkgfq

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

over 3 years ago by @chenxwh

Input

ref
src
model: celeb

{
  "ref": "https://replicate.delivery/mgxm/e01b4f20-43f3-4494-8268-83ca0529a926/069067.jpg",
  "src": "https://replicate.delivery/mgxm/786f0ae8-fa77-44b8-a367-f6ca6c288139/030321.jpg",
  "model": "celeb"
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run yunjey/stargan-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yunjey/stargan-v2:fd6a430c610c91bae70b628065fcf64f66d41e69a1c5d0d53c763dded606ef91",
  {
    input: {
      ref: "https://replicate.delivery/mgxm/e01b4f20-43f3-4494-8268-83ca0529a926/069067.jpg",
      src: "https://replicate.delivery/mgxm/786f0ae8-fa77-44b8-a367-f6ca6c288139/030321.jpg",
      model: "celeb"
    }
  }
);

console.log(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

Import the client:

import replicate

Run yunjey/stargan-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yunjey/stargan-v2:fd6a430c610c91bae70b628065fcf64f66d41e69a1c5d0d53c763dded606ef91",
    input={
        "ref": "https://replicate.delivery/mgxm/e01b4f20-43f3-4494-8268-83ca0529a926/069067.jpg",
        "src": "https://replicate.delivery/mgxm/786f0ae8-fa77-44b8-a367-f6ca6c288139/030321.jpg",
        "model": "celeb"
    }
)

# The yunjey/stargan-v2 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/yunjey/stargan-v2/api#output-schema
    print(item)

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

Run yunjey/stargan-v2 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": "yunjey/stargan-v2:fd6a430c610c91bae70b628065fcf64f66d41e69a1c5d0d53c763dded606ef91",
    "input": {
      "ref": "https://replicate.delivery/mgxm/e01b4f20-43f3-4494-8268-83ca0529a926/069067.jpg",
      "src": "https://replicate.delivery/mgxm/786f0ae8-fa77-44b8-a367-f6ca6c288139/030321.jpg",
      "model": "celeb"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Tweak it Share Report

Prediction

yunjey/stargan-v2:fd6a430c610c91bae70b628065fcf64f66d41e69a1c5d0d53c763dded606ef91

Model

yunjey/stargan-v2:fd6a430c

evstsjorgjaell2svu3246yszy

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

over 3 years ago

Input

ref
src
model: animal

{
  "ref": "https://replicate.delivery/mgxm/c7197a24-e511-454a-b691-06fff7e6c022/pixabay_cat_001699.jpg",
  "src": "https://replicate.delivery/mgxm/15550487-92e0-4901-a240-d681684ba8b0/flickr_cat_000253.jpg",
  "model": "animal"
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run yunjey/stargan-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yunjey/stargan-v2:fd6a430c610c91bae70b628065fcf64f66d41e69a1c5d0d53c763dded606ef91",
  {
    input: {
      ref: "https://replicate.delivery/mgxm/c7197a24-e511-454a-b691-06fff7e6c022/pixabay_cat_001699.jpg",
      src: "https://replicate.delivery/mgxm/15550487-92e0-4901-a240-d681684ba8b0/flickr_cat_000253.jpg",
      model: "animal"
    }
  }
);

console.log(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

Import the client:

import replicate

Run yunjey/stargan-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yunjey/stargan-v2:fd6a430c610c91bae70b628065fcf64f66d41e69a1c5d0d53c763dded606ef91",
    input={
        "ref": "https://replicate.delivery/mgxm/c7197a24-e511-454a-b691-06fff7e6c022/pixabay_cat_001699.jpg",
        "src": "https://replicate.delivery/mgxm/15550487-92e0-4901-a240-d681684ba8b0/flickr_cat_000253.jpg",
        "model": "animal"
    }
)

# The yunjey/stargan-v2 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/yunjey/stargan-v2/api#output-schema
    print(item)

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

Run yunjey/stargan-v2 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": "yunjey/stargan-v2:fd6a430c610c91bae70b628065fcf64f66d41e69a1c5d0d53c763dded606ef91",
    "input": {
      "ref": "https://replicate.delivery/mgxm/c7197a24-e511-454a-b691-06fff7e6c022/pixabay_cat_001699.jpg",
      "src": "https://replicate.delivery/mgxm/15550487-92e0-4901-a240-d681684ba8b0/flickr_cat_000253.jpg",
      "model": "animal"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Tweak it Share Report

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yunjey / stargan-v2

Prediction

Input

Output

Prediction

Input

Output

Logs (x5dhidfspbgjzbiueb22bjkgfq)

Logs (evstsjorgjaell2svu3246yszy)