Prediction

ID

6teemj3bmdtn4jzlo2v4hiu3xi

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

76.7s

Created

over 1 year ago

Input

image
model_size: large

{
  "image": "https://replicate.delivery/pbxt/KDMhf8lcgjezRIhDCg8TCJ8S54GN3ugrtnMGAQ1jyMDwSLnx/Ansel%20Adams%20_%20Moore%20Photography.jpeg",
  "model_size": "large"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KDMhf8lcgjezRIhDCg8TCJ8S54GN3ugrtnMGAQ1jyMDwSLnx/Ansel%20Adams%20_%20Moore%20Photography.jpeg",
      model_size: "large"
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    input={
        "image": "https://replicate.delivery/pbxt/KDMhf8lcgjezRIhDCg8TCJ8S54GN3ugrtnMGAQ1jyMDwSLnx/Ansel%20Adams%20_%20Moore%20Photography.jpeg",
        "model_size": "large"
    }
)
print(output)

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

Run piddnad/ddcolor 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": "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    "input": {
      "image": "https://replicate.delivery/pbxt/KDMhf8lcgjezRIhDCg8TCJ8S54GN3ugrtnMGAQ1jyMDwSLnx/Ansel%20Adams%20_%20Moore%20Photography.jpeg",
      "model_size": "large"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

3.1 seconds

piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695

Prediction

Model

ID

4ha65m3b7um3gjoeke6bzkykiu

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1.7s

Created

over 1 year ago

Input

image
model_size: large

{
  "image": "https://replicate.delivery/pbxt/KDMjjY4rQxqkpTvtjEfyLZTKt0wgiSzr3gjT7bLtmxbT0MaG/Abandoned%20Boy%20Holding%20a%20Stuffed%20Toy%20Animal.%20London%201945.jpg",
  "model_size": "large"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KDMjjY4rQxqkpTvtjEfyLZTKt0wgiSzr3gjT7bLtmxbT0MaG/Abandoned%20Boy%20Holding%20a%20Stuffed%20Toy%20Animal.%20London%201945.jpg",
      model_size: "large"
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    input={
        "image": "https://replicate.delivery/pbxt/KDMjjY4rQxqkpTvtjEfyLZTKt0wgiSzr3gjT7bLtmxbT0MaG/Abandoned%20Boy%20Holding%20a%20Stuffed%20Toy%20Animal.%20London%201945.jpg",
        "model_size": "large"
    }
)
print(output)

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

Run piddnad/ddcolor 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": "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    "input": {
      "image": "https://replicate.delivery/pbxt/KDMjjY4rQxqkpTvtjEfyLZTKt0wgiSzr3gjT7bLtmxbT0MaG/Abandoned%20Boy%20Holding%20a%20Stuffed%20Toy%20Animal.%20London%201945.jpg",
      "model_size": "large"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.6 seconds

piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695

Prediction

Model

ID

luv5ewtbuzjyiixctdlqcf5o6m

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1.8s

Created

over 1 year ago

Input

image
model_size: tiny

{
  "image": "https://replicate.delivery/pbxt/KDMjwJo7Gf59GS7m4MfytnHgtdWDBoFLygLy2ZaNherGx8CG/Abandoned%20Boy%20Holding%20a%20Stuffed%20Toy%20Animal.%20London%201945.jpg",
  "model_size": "tiny"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KDMjwJo7Gf59GS7m4MfytnHgtdWDBoFLygLy2ZaNherGx8CG/Abandoned%20Boy%20Holding%20a%20Stuffed%20Toy%20Animal.%20London%201945.jpg",
      model_size: "tiny"
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    input={
        "image": "https://replicate.delivery/pbxt/KDMjwJo7Gf59GS7m4MfytnHgtdWDBoFLygLy2ZaNherGx8CG/Abandoned%20Boy%20Holding%20a%20Stuffed%20Toy%20Animal.%20London%201945.jpg",
        "model_size": "tiny"
    }
)
print(output)

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

Run piddnad/ddcolor 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": "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    "input": {
      "image": "https://replicate.delivery/pbxt/KDMjwJo7Gf59GS7m4MfytnHgtdWDBoFLygLy2ZaNherGx8CG/Abandoned%20Boy%20Holding%20a%20Stuffed%20Toy%20Animal.%20London%201945.jpg",
      "model_size": "tiny"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.7 seconds

piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695

Prediction

Model

ID

pwgfkwtb7itmoyazvzn2vb7chy

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1.8s

Created

over 1 year ago

Input

image
model_size: large

{
  "image": "https://replicate.delivery/pbxt/KDMkSU717zMUfrWrFHjTdmC2bAMSpUtHhpZbIDKVS9FiGwba/Audrey%20Hepburn.jpg",
  "model_size": "large"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KDMkSU717zMUfrWrFHjTdmC2bAMSpUtHhpZbIDKVS9FiGwba/Audrey%20Hepburn.jpg",
      model_size: "large"
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    input={
        "image": "https://replicate.delivery/pbxt/KDMkSU717zMUfrWrFHjTdmC2bAMSpUtHhpZbIDKVS9FiGwba/Audrey%20Hepburn.jpg",
        "model_size": "large"
    }
)
print(output)

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

Run piddnad/ddcolor 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": "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    "input": {
      "image": "https://replicate.delivery/pbxt/KDMkSU717zMUfrWrFHjTdmC2bAMSpUtHhpZbIDKVS9FiGwba/Audrey%20Hepburn.jpg",
      "model_size": "large"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.8 seconds

piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695

Prediction

Model

ID

pkxytzdbkuach644xwzyouk5fu

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

3.0s

Created

over 1 year ago

Input

image
model_size: large

{
  "image": "https://replicate.delivery/pbxt/KDMkjS4SpsGieAxMdkBUNWT5zFI8BvAU4XjiyI2xmLny3skZ/Buffalo%20Bank%20Buffalo%2C%20New%20York%2C%20circa%201908.%20Erie%20County%20Savings%20Bank%2C%20Niagara%20Street.jpg",
  "model_size": "large"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KDMkjS4SpsGieAxMdkBUNWT5zFI8BvAU4XjiyI2xmLny3skZ/Buffalo%20Bank%20Buffalo%2C%20New%20York%2C%20circa%201908.%20Erie%20County%20Savings%20Bank%2C%20Niagara%20Street.jpg",
      model_size: "large"
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    input={
        "image": "https://replicate.delivery/pbxt/KDMkjS4SpsGieAxMdkBUNWT5zFI8BvAU4XjiyI2xmLny3skZ/Buffalo%20Bank%20Buffalo%2C%20New%20York%2C%20circa%201908.%20Erie%20County%20Savings%20Bank%2C%20Niagara%20Street.jpg",
        "model_size": "large"
    }
)
print(output)

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

Run piddnad/ddcolor 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": "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    "input": {
      "image": "https://replicate.delivery/pbxt/KDMkjS4SpsGieAxMdkBUNWT5zFI8BvAU4XjiyI2xmLny3skZ/Buffalo%20Bank%20Buffalo%2C%20New%20York%2C%20circa%201908.%20Erie%20County%20Savings%20Bank%2C%20Niagara%20Street.jpg",
      "model_size": "large"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.9 seconds

piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695

Prediction

Model

ID

2c43bmdbqx4e65v57jr53ahdjy

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1.8s

Created

over 1 year ago

Input

image
model_size: large

{
  "image": "https://replicate.delivery/pbxt/KDMlP32TacO7kGUrnR1DCM0nVfXDrkbe8gnRqSmgYMLHQVqh/Einstein%2C%20Rejection%2C%20and%20Crafting%20a%20Future.jpeg",
  "model_size": "large"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KDMlP32TacO7kGUrnR1DCM0nVfXDrkbe8gnRqSmgYMLHQVqh/Einstein%2C%20Rejection%2C%20and%20Crafting%20a%20Future.jpeg",
      model_size: "large"
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    input={
        "image": "https://replicate.delivery/pbxt/KDMlP32TacO7kGUrnR1DCM0nVfXDrkbe8gnRqSmgYMLHQVqh/Einstein%2C%20Rejection%2C%20and%20Crafting%20a%20Future.jpeg",
        "model_size": "large"
    }
)
print(output)

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

Run piddnad/ddcolor 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": "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    "input": {
      "image": "https://replicate.delivery/pbxt/KDMlP32TacO7kGUrnR1DCM0nVfXDrkbe8gnRqSmgYMLHQVqh/Einstein%2C%20Rejection%2C%20and%20Crafting%20a%20Future.jpeg",
      "model_size": "large"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.7 seconds

piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695

Prediction

Model

ID

vzmhyc3bojyk4mzencetp75o64

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

2.2s

Created

over 1 year ago

Input

image
model_size: large

{
  "image": "https://replicate.delivery/pbxt/KDMmX8nggvoH7C7hgqCKpMf87q2w83pNVT32ak14L8DVXfIw/New%20York%20Riverfront%20December%2015%2C%201931.jpg",
  "model_size": "large"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KDMmX8nggvoH7C7hgqCKpMf87q2w83pNVT32ak14L8DVXfIw/New%20York%20Riverfront%20December%2015%2C%201931.jpg",
      model_size: "large"
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    input={
        "image": "https://replicate.delivery/pbxt/KDMmX8nggvoH7C7hgqCKpMf87q2w83pNVT32ak14L8DVXfIw/New%20York%20Riverfront%20December%2015%2C%201931.jpg",
        "model_size": "large"
    }
)
print(output)

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

Run piddnad/ddcolor 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": "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    "input": {
      "image": "https://replicate.delivery/pbxt/KDMmX8nggvoH7C7hgqCKpMf87q2w83pNVT32ak14L8DVXfIw/New%20York%20Riverfront%20December%2015%2C%201931.jpg",
      "model_size": "large"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.1 seconds

piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695

Prediction

Model

ID

fszvpelbcd6cdhbt526lw4ewku

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1.8s

Created

over 1 year ago

Input

image
model_size: large

{
  "image": "https://replicate.delivery/pbxt/KDMl1O3YVSpG1Wa5HSaeCoQLVvGn3BjbY6yfXgWtESHyqmmz/colorized-historical-photos-vintage-photography-39.jpg",
  "model_size": "large"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KDMl1O3YVSpG1Wa5HSaeCoQLVvGn3BjbY6yfXgWtESHyqmmz/colorized-historical-photos-vintage-photography-39.jpg",
      model_size: "large"
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    input={
        "image": "https://replicate.delivery/pbxt/KDMl1O3YVSpG1Wa5HSaeCoQLVvGn3BjbY6yfXgWtESHyqmmz/colorized-historical-photos-vintage-photography-39.jpg",
        "model_size": "large"
    }
)
print(output)

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

Run piddnad/ddcolor 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": "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    "input": {
      "image": "https://replicate.delivery/pbxt/KDMl1O3YVSpG1Wa5HSaeCoQLVvGn3BjbY6yfXgWtESHyqmmz/colorized-historical-photos-vintage-photography-39.jpg",
      "model_size": "large"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.7 seconds

piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695

Prediction

Model

ID

dfxvuntb6puc2he4i3awsgjxbi

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1.7s

Created

over 1 year ago

Input

image
model_size: large

{
  "image": "https://replicate.delivery/pbxt/KDMlDKth6W9m9OErZOR5pj1tRSkiCO5BBQZZu67cp6zeTExp/Detroit%20circa%201915.jpg",
  "model_size": "large"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KDMlDKth6W9m9OErZOR5pj1tRSkiCO5BBQZZu67cp6zeTExp/Detroit%20circa%201915.jpg",
      model_size: "large"
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    input={
        "image": "https://replicate.delivery/pbxt/KDMlDKth6W9m9OErZOR5pj1tRSkiCO5BBQZZu67cp6zeTExp/Detroit%20circa%201915.jpg",
        "model_size": "large"
    }
)
print(output)

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

Run piddnad/ddcolor 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": "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    "input": {
      "image": "https://replicate.delivery/pbxt/KDMlDKth6W9m9OErZOR5pj1tRSkiCO5BBQZZu67cp6zeTExp/Detroit%20circa%201915.jpg",
      "model_size": "large"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.7 seconds

piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695

Prediction

Model

ID

byol2wlbjfzssekgioogvedtoq

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

2.0s

Created

over 1 year ago

Input

image
model_size: large

{
  "image": "https://replicate.delivery/pbxt/KDMlchLrL7jF0BeXyfrKtCow4rn6wtXqHxTxdDk05fbEkjz3/February%201936.%20Nipomo%2C%20Calif.%20Destitute%20pea%20pickers%20living%20in%20tent%20in%20migrant%20camp.%20Mother%20of%20seven%20children.%20Age%2032.jpg",
  "model_size": "large"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KDMlchLrL7jF0BeXyfrKtCow4rn6wtXqHxTxdDk05fbEkjz3/February%201936.%20Nipomo%2C%20Calif.%20Destitute%20pea%20pickers%20living%20in%20tent%20in%20migrant%20camp.%20Mother%20of%20seven%20children.%20Age%2032.jpg",
      model_size: "large"
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    input={
        "image": "https://replicate.delivery/pbxt/KDMlchLrL7jF0BeXyfrKtCow4rn6wtXqHxTxdDk05fbEkjz3/February%201936.%20Nipomo%2C%20Calif.%20Destitute%20pea%20pickers%20living%20in%20tent%20in%20migrant%20camp.%20Mother%20of%20seven%20children.%20Age%2032.jpg",
        "model_size": "large"
    }
)
print(output)

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

Run piddnad/ddcolor 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": "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    "input": {
      "image": "https://replicate.delivery/pbxt/KDMlchLrL7jF0BeXyfrKtCow4rn6wtXqHxTxdDk05fbEkjz3/February%201936.%20Nipomo%2C%20Calif.%20Destitute%20pea%20pickers%20living%20in%20tent%20in%20migrant%20camp.%20Mother%20of%20seven%20children.%20Age%2032.jpg",
      "model_size": "large"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.0 seconds

piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695

Prediction

Model

ID

5vpxi2tbc3iivzbkepuqfegyvi

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1.7s

Created

over 1 year ago

Input

image
model_size: large

{
  "image": "https://replicate.delivery/pbxt/KDMm3A38KvZtaapCLRWevICaAzArSZ9A63563vvoNMEXhef8/Helen%20Keller%20meeting%20Charlie%20Chaplin%20in%201919.jpg",
  "model_size": "large"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KDMm3A38KvZtaapCLRWevICaAzArSZ9A63563vvoNMEXhef8/Helen%20Keller%20meeting%20Charlie%20Chaplin%20in%201919.jpg",
      model_size: "large"
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    input={
        "image": "https://replicate.delivery/pbxt/KDMm3A38KvZtaapCLRWevICaAzArSZ9A63563vvoNMEXhef8/Helen%20Keller%20meeting%20Charlie%20Chaplin%20in%201919.jpg",
        "model_size": "large"
    }
)
print(output)

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

Run piddnad/ddcolor 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": "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    "input": {
      "image": "https://replicate.delivery/pbxt/KDMm3A38KvZtaapCLRWevICaAzArSZ9A63563vvoNMEXhef8/Helen%20Keller%20meeting%20Charlie%20Chaplin%20in%201919.jpg",
      "model_size": "large"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.7 seconds

piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695

Prediction

Model

ID

47b2hflby5nbx4nyg5eew42g2e

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1.7s

Created

over 1 year ago

Input

image
model_size: large

{
  "image": "https://replicate.delivery/pbxt/KDMmIT1zjDcvGuoat83iSHzN7tGr1ZZJt0jG5jcRZ9ULbToS/Louis%20Armstrong%20practicing%20in%20his%20dressing%20room%2C%20ca%201946.jpg",
  "model_size": "large"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KDMmIT1zjDcvGuoat83iSHzN7tGr1ZZJt0jG5jcRZ9ULbToS/Louis%20Armstrong%20practicing%20in%20his%20dressing%20room%2C%20ca%201946.jpg",
      model_size: "large"
    }
  }
);

// 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.

pip install replicate

Import the client:

import replicate

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

output = replicate.run(
    "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    input={
        "image": "https://replicate.delivery/pbxt/KDMmIT1zjDcvGuoat83iSHzN7tGr1ZZJt0jG5jcRZ9ULbToS/Louis%20Armstrong%20practicing%20in%20his%20dressing%20room%2C%20ca%201946.jpg",
        "model_size": "large"
    }
)
print(output)

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

Run piddnad/ddcolor 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": "piddnad/ddcolor:ca494ba129e44e45f661d6ece83c4c98a9a7c774309beca01429b58fce8aa695",
    "input": {
      "image": "https://replicate.delivery/pbxt/KDMmIT1zjDcvGuoat83iSHzN7tGr1ZZJt0jG5jcRZ9ULbToS/Louis%20Armstrong%20practicing%20in%20his%20dressing%20room%2C%20ca%201946.jpg",
      "model_size": "large"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.6 seconds