Prediction

tencentarc/gfpgan:297a243ce8643961d52f745f9b6c8c1bd96850a51c92be5f43628a0d3e08321a

Model

tencentarc/gfpgan:297a243c

ID

ffu2e6aw4barxliwxu23ydgbnu

Status

Succeeded

Source

Web

Hardware

–

Total duration

2.0s

Created

almost 3 years ago by @xinntao

Input

img
scale: 2
version: v1.4

{
  "img": "https://replicate.delivery/mgxm/59d9390c-b415-47e0-a907-f81b0d9920f1/187400315-87a90ac9-d231-45d6-b377-38702bd1838f.jpg",
  "scale": 2,
  "version": "v1.4"
}

Install Replicate’s Node.js client library:

npm install replicate

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

const output = await replicate.run(
  "tencentarc/gfpgan:297a243ce8643961d52f745f9b6c8c1bd96850a51c92be5f43628a0d3e08321a",
  {
    input: {
      img: "https://replicate.delivery/mgxm/59d9390c-b415-47e0-a907-f81b0d9920f1/187400315-87a90ac9-d231-45d6-b377-38702bd1838f.jpg",
      scale: 2,
      version: "v1.4"
    }
  }
);

// 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

Import the client:

import replicate

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

output = replicate.run(
    "tencentarc/gfpgan:297a243ce8643961d52f745f9b6c8c1bd96850a51c92be5f43628a0d3e08321a",
    input={
        "img": "https://replicate.delivery/mgxm/59d9390c-b415-47e0-a907-f81b0d9920f1/187400315-87a90ac9-d231-45d6-b377-38702bd1838f.jpg",
        "scale": 2,
        "version": "v1.4"
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

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

Run tencentarc/gfpgan 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": "tencentarc/gfpgan:297a243ce8643961d52f745f9b6c8c1bd96850a51c92be5f43628a0d3e08321a",
    "input": {
      "img": "https://replicate.delivery/mgxm/59d9390c-b415-47e0-a907-f81b0d9920f1/187400315-87a90ac9-d231-45d6-b377-38702bd1838f.jpg",
      "scale": 2,
      "version": "v1.4"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/tencentarc/gfpgan@sha256:297a243ce8643961d52f745f9b6c8c1bd96850a51c92be5f43628a0d3e08321a \
  -i 'img="https://replicate.delivery/mgxm/59d9390c-b415-47e0-a907-f81b0d9920f1/187400315-87a90ac9-d231-45d6-b377-38702bd1838f.jpg"' \
  -i 'scale=2' \
  -i 'version="v1.4"'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/tencentarc/gfpgan@sha256:297a243ce8643961d52f745f9b6c8c1bd96850a51c92be5f43628a0d3e08321a
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "img": "https://replicate.delivery/mgxm/59d9390c-b415-47e0-a907-f81b0d9920f1/187400315-87a90ac9-d231-45d6-b377-38702bd1838f.jpg",
      "scale": 2,
      "version": "v1.4"
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

We were unable to load these images. Please make sure the URLs are valid.

{
  "input": "https://replicate.delivery/mgxm/59d9390c-b415-47e0-a907-f81b0d9920f1/187400315-87a90ac9-d231-45d6-b377-38702bd1838f.jpg",
  "outut": "https://replicate.delivery/mgxm/85f53415-0dc7-4703-891f-1e6f912119ad/output.png"
}

Generated in

1.7 seconds

Tweak it ShareReport

Prediction

tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694

Model

tencentarc/gfpgan:ae80bbe1

ID

wdj2fedsczdtzeflmvzyu4hata

Status

Succeeded

Source

Web

Hardware

–

Total duration

2.9s

Created

almost 3 years ago by @xinntao

Input

img
scale: 2
version: v1.3

{
  "img": "https://replicate.delivery/mgxm/9227bd4f-a945-44d7-956a-dee33c6f389f/%E4%B8%8B%E8%BD%BD.jpg",
  "scale": 2,
  "version": "v1.3"
}

Install Replicate’s Node.js client library:

npm install replicate

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

const output = await replicate.run(
  "tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694",
  {
    input: {
      img: "https://replicate.delivery/mgxm/9227bd4f-a945-44d7-956a-dee33c6f389f/%E4%B8%8B%E8%BD%BD.jpg",
      scale: 2,
      version: "v1.3"
    }
  }
);

// 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

Import the client:

import replicate

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

output = replicate.run(
    "tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694",
    input={
        "img": "https://replicate.delivery/mgxm/9227bd4f-a945-44d7-956a-dee33c6f389f/%E4%B8%8B%E8%BD%BD.jpg",
        "scale": 2,
        "version": "v1.3"
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

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

Run tencentarc/gfpgan 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": "tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694",
    "input": {
      "img": "https://replicate.delivery/mgxm/9227bd4f-a945-44d7-956a-dee33c6f389f/%E4%B8%8B%E8%BD%BD.jpg",
      "scale": 2,
      "version": "v1.3"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/tencentarc/gfpgan@sha256:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694 \
  -i 'img="https://replicate.delivery/mgxm/9227bd4f-a945-44d7-956a-dee33c6f389f/%E4%B8%8B%E8%BD%BD.jpg"' \
  -i 'scale=2' \
  -i 'version="v1.3"'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/tencentarc/gfpgan@sha256:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "img": "https://replicate.delivery/mgxm/9227bd4f-a945-44d7-956a-dee33c6f389f/%E4%B8%8B%E8%BD%BD.jpg",
      "scale": 2,
      "version": "v1.3"
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

We were unable to load these images. Please make sure the URLs are valid.

{
  "input": "https://replicate.delivery/mgxm/9227bd4f-a945-44d7-956a-dee33c6f389f/%E4%B8%8B%E8%BD%BD.jpg",
  "outut": "https://replicate.delivery/mgxm/25b4bcb2-3029-4417-8689-e5997f217ea0/output.png"
}

Generated in

0 milliseconds

Tweak it ShareReport

Prediction

tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694

Model

tencentarc/gfpgan:ae80bbe1

ID

ya2he2bwmjdaxb2mg2fwj4ejn4

Status

Succeeded

Source

Web

Hardware

–

Total duration

7.4s

Created

almost 3 years ago by @xinntao

Input

img
scale: 2
version: v1.3

{
  "img": "https://replicate.delivery/mgxm/6c1f5af2-825c-4ded-a4c1-339a58a0347c/187400981-8a58f7a4-ef61-42d9-af80-bc6234cef860.jpg",
  "scale": 2,
  "version": "v1.3"
}

Install Replicate’s Node.js client library:

npm install replicate

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

const output = await replicate.run(
  "tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694",
  {
    input: {
      img: "https://replicate.delivery/mgxm/6c1f5af2-825c-4ded-a4c1-339a58a0347c/187400981-8a58f7a4-ef61-42d9-af80-bc6234cef860.jpg",
      scale: 2,
      version: "v1.3"
    }
  }
);

// 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

Import the client:

import replicate

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

output = replicate.run(
    "tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694",
    input={
        "img": "https://replicate.delivery/mgxm/6c1f5af2-825c-4ded-a4c1-339a58a0347c/187400981-8a58f7a4-ef61-42d9-af80-bc6234cef860.jpg",
        "scale": 2,
        "version": "v1.3"
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

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

Run tencentarc/gfpgan 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": "tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694",
    "input": {
      "img": "https://replicate.delivery/mgxm/6c1f5af2-825c-4ded-a4c1-339a58a0347c/187400981-8a58f7a4-ef61-42d9-af80-bc6234cef860.jpg",
      "scale": 2,
      "version": "v1.3"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/tencentarc/gfpgan@sha256:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694 \
  -i 'img="https://replicate.delivery/mgxm/6c1f5af2-825c-4ded-a4c1-339a58a0347c/187400981-8a58f7a4-ef61-42d9-af80-bc6234cef860.jpg"' \
  -i 'scale=2' \
  -i 'version="v1.3"'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/tencentarc/gfpgan@sha256:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "img": "https://replicate.delivery/mgxm/6c1f5af2-825c-4ded-a4c1-339a58a0347c/187400981-8a58f7a4-ef61-42d9-af80-bc6234cef860.jpg",
      "scale": 2,
      "version": "v1.3"
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

We were unable to load these images. Please make sure the URLs are valid.

{
  "input": "https://replicate.delivery/mgxm/6c1f5af2-825c-4ded-a4c1-339a58a0347c/187400981-8a58f7a4-ef61-42d9-af80-bc6234cef860.jpg",
  "outut": "https://replicate.delivery/mgxm/abab834a-81ec-42f1-a415-7035ae55707a/output.png"
}

Generated in

0.6 seconds

Tweak it ShareReport

Prediction

tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694

Model

tencentarc/gfpgan:ae80bbe1

ID

xpyncbsrhzavpdjjpwzwi5cf5q

Status

Succeeded

Source

Web

Hardware

–

Total duration

9.6s

Created

almost 3 years ago by @xinntao

Input

img
scale: 2
version: v1.3

{
  "img": "https://replicate.delivery/mgxm/26d87fc6-3843-4680-9f92-9970de2e5a61/187401133-8a3bf269-5b4d-4432-b2f0-6d26ee1d3307.png",
  "scale": 2,
  "version": "v1.3"
}

Install Replicate’s Node.js client library:

npm install replicate

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

const output = await replicate.run(
  "tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694",
  {
    input: {
      img: "https://replicate.delivery/mgxm/26d87fc6-3843-4680-9f92-9970de2e5a61/187401133-8a3bf269-5b4d-4432-b2f0-6d26ee1d3307.png",
      scale: 2,
      version: "v1.3"
    }
  }
);

// 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

Import the client:

import replicate

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

output = replicate.run(
    "tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694",
    input={
        "img": "https://replicate.delivery/mgxm/26d87fc6-3843-4680-9f92-9970de2e5a61/187401133-8a3bf269-5b4d-4432-b2f0-6d26ee1d3307.png",
        "scale": 2,
        "version": "v1.3"
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

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

Run tencentarc/gfpgan 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": "tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694",
    "input": {
      "img": "https://replicate.delivery/mgxm/26d87fc6-3843-4680-9f92-9970de2e5a61/187401133-8a3bf269-5b4d-4432-b2f0-6d26ee1d3307.png",
      "scale": 2,
      "version": "v1.3"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/tencentarc/gfpgan@sha256:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694 \
  -i 'img="https://replicate.delivery/mgxm/26d87fc6-3843-4680-9f92-9970de2e5a61/187401133-8a3bf269-5b4d-4432-b2f0-6d26ee1d3307.png"' \
  -i 'scale=2' \
  -i 'version="v1.3"'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/tencentarc/gfpgan@sha256:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "img": "https://replicate.delivery/mgxm/26d87fc6-3843-4680-9f92-9970de2e5a61/187401133-8a3bf269-5b4d-4432-b2f0-6d26ee1d3307.png",
      "scale": 2,
      "version": "v1.3"
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

We were unable to load these images. Please make sure the URLs are valid.

{
  "input": "https://replicate.delivery/mgxm/26d87fc6-3843-4680-9f92-9970de2e5a61/187401133-8a3bf269-5b4d-4432-b2f0-6d26ee1d3307.png",
  "outut": "https://replicate.delivery/mgxm/4fbbce6e-daa9-45c0-bdf1-1c14ade7fdeb/output.png"
}

Generated in

5.3 seconds

Tweak it ShareReport

Prediction

tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694

Model

tencentarc/gfpgan:ae80bbe1

ID

2j4duq3vbfbblgd7jqx5xrcngi

Status

Succeeded

Source

Web

Hardware

–

Total duration

3.4s

Created

almost 3 years ago by @xinntao

Input

img
scale: 2
version: v1.3

{
  "img": "https://replicate.delivery/mgxm/57dae5a1-f11b-4f41-83ec-a2c9ac190c69/AAA9hAAAPYQGoP6dpAAAKT2lD.png",
  "scale": 2,
  "version": "v1.3"
}

Install Replicate’s Node.js client library:

npm install replicate

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

const output = await replicate.run(
  "tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694",
  {
    input: {
      img: "https://replicate.delivery/mgxm/57dae5a1-f11b-4f41-83ec-a2c9ac190c69/AAA9hAAAPYQGoP6dpAAAKT2lD.png",
      scale: 2,
      version: "v1.3"
    }
  }
);

// 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

Import the client:

import replicate

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

output = replicate.run(
    "tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694",
    input={
        "img": "https://replicate.delivery/mgxm/57dae5a1-f11b-4f41-83ec-a2c9ac190c69/AAA9hAAAPYQGoP6dpAAAKT2lD.png",
        "scale": 2,
        "version": "v1.3"
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

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

Run tencentarc/gfpgan 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": "tencentarc/gfpgan:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694",
    "input": {
      "img": "https://replicate.delivery/mgxm/57dae5a1-f11b-4f41-83ec-a2c9ac190c69/AAA9hAAAPYQGoP6dpAAAKT2lD.png",
      "scale": 2,
      "version": "v1.3"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/tencentarc/gfpgan@sha256:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694 \
  -i 'img="https://replicate.delivery/mgxm/57dae5a1-f11b-4f41-83ec-a2c9ac190c69/AAA9hAAAPYQGoP6dpAAAKT2lD.png"' \
  -i 'scale=2' \
  -i 'version="v1.3"'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/tencentarc/gfpgan@sha256:ae80bbe1adce7d616b8a96ba88a91d3556838d4f2f4da76327638b8e95ea4694
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "img": "https://replicate.delivery/mgxm/57dae5a1-f11b-4f41-83ec-a2c9ac190c69/AAA9hAAAPYQGoP6dpAAAKT2lD.png",
      "scale": 2,
      "version": "v1.3"
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

We were unable to load these images. Please make sure the URLs are valid.

{
  "input": "https://replicate.delivery/mgxm/57dae5a1-f11b-4f41-83ec-a2c9ac190c69/AAA9hAAAPYQGoP6dpAAAKT2lD.png",
  "outut": "https://replicate.delivery/mgxm/9788da2f-4f0c-4107-b6de-6c9332cc3af2/output.png"
}

Generated in

1.8 seconds

Tweak it ShareReport