Prediction

ID

nwb1c8xtw9rm80cq1zest2153m

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

7.9s

Created

about 1 month ago by @lucataco

Input

image
dot_scale: 1
grid_size: 24
output_width: 1024
brightness_threshold: 0

{
  "image": "https://replicate.delivery/pbxt/N4zRsaMPgp3JBBcSArOOPKrEkWUVEFvCY3rvJanziMTPYpgs/GraZnzHbAAMX8Nm.jpeg",
  "dot_scale": 1,
  "grid_size": 24,
  "output_width": 1024,
  "brightness_threshold": 0
}

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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
  {
    input: {
      image: "https://replicate.delivery/pbxt/N4zRsaMPgp3JBBcSArOOPKrEkWUVEFvCY3rvJanziMTPYpgs/GraZnzHbAAMX8Nm.jpeg",
      dot_scale: 1,
      grid_size: 24,
      output_width: 1024,
      brightness_threshold: 0
    }
  }
);

// 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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
    input={
        "image": "https://replicate.delivery/pbxt/N4zRsaMPgp3JBBcSArOOPKrEkWUVEFvCY3rvJanziMTPYpgs/GraZnzHbAAMX8Nm.jpeg",
        "dot_scale": 1,
        "grid_size": 24,
        "output_width": 1024,
        "brightness_threshold": 0
    }
)
print(output)

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

Run lucataco/vectorized-dot-grid 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": "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
    "input": {
      "image": "https://replicate.delivery/pbxt/N4zRsaMPgp3JBBcSArOOPKrEkWUVEFvCY3rvJanziMTPYpgs/GraZnzHbAAMX8Nm.jpeg",
      "dot_scale": 1,
      "grid_size": 24,
      "output_width": 1024,
      "brightness_threshold": 0
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

0.2 seconds

lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208

Prediction

Model

ID

khjsz0cte1rme0cq1zg98ren7g

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

0.2s

Created

about 1 month ago

Input

image
dot_scale: 1
grid_size: 20
output_width: 1024
brightness_threshold: 0

{
  "image": "https://replicate.delivery/pbxt/N4zUrCvijPbTTQLGDOEeN4Nmqjlmz2Jz6HNNKWYyDSUBUzTa/David_-_Napoleon_crossing_the_Alps_-_Malmaison2.jpg",
  "dot_scale": 1,
  "grid_size": 20,
  "output_width": 1024,
  "brightness_threshold": 0
}

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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
  {
    input: {
      image: "https://replicate.delivery/pbxt/N4zUrCvijPbTTQLGDOEeN4Nmqjlmz2Jz6HNNKWYyDSUBUzTa/David_-_Napoleon_crossing_the_Alps_-_Malmaison2.jpg",
      dot_scale: 1,
      grid_size: 20,
      output_width: 1024,
      brightness_threshold: 0
    }
  }
);

// 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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
    input={
        "image": "https://replicate.delivery/pbxt/N4zUrCvijPbTTQLGDOEeN4Nmqjlmz2Jz6HNNKWYyDSUBUzTa/David_-_Napoleon_crossing_the_Alps_-_Malmaison2.jpg",
        "dot_scale": 1,
        "grid_size": 20,
        "output_width": 1024,
        "brightness_threshold": 0
    }
)
print(output)

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

Run lucataco/vectorized-dot-grid 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": "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
    "input": {
      "image": "https://replicate.delivery/pbxt/N4zUrCvijPbTTQLGDOEeN4Nmqjlmz2Jz6HNNKWYyDSUBUzTa/David_-_Napoleon_crossing_the_Alps_-_Malmaison2.jpg",
      "dot_scale": 1,
      "grid_size": 20,
      "output_width": 1024,
      "brightness_threshold": 0
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

0.2 seconds

lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208

Prediction

Model

ID

d5nd2bdfysrma0cq1zgspw6qym

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

0.3s

Created

about 1 month ago

Input

image
dot_scale: 1
grid_size: 21
output_width: 1200
brightness_threshold: 0

{
  "image": "https://replicate.delivery/pbxt/N4zVyiww4DRB2g98bn4cIFapazY8q9IFDEJYeSAxiT43aFkc/Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg.webp",
  "dot_scale": 1,
  "grid_size": 21,
  "output_width": 1200,
  "brightness_threshold": 0
}

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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
  {
    input: {
      image: "https://replicate.delivery/pbxt/N4zVyiww4DRB2g98bn4cIFapazY8q9IFDEJYeSAxiT43aFkc/Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg.webp",
      dot_scale: 1,
      grid_size: 21,
      output_width: 1200,
      brightness_threshold: 0
    }
  }
);

// 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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
    input={
        "image": "https://replicate.delivery/pbxt/N4zVyiww4DRB2g98bn4cIFapazY8q9IFDEJYeSAxiT43aFkc/Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg.webp",
        "dot_scale": 1,
        "grid_size": 21,
        "output_width": 1200,
        "brightness_threshold": 0
    }
)
print(output)

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

Run lucataco/vectorized-dot-grid 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": "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
    "input": {
      "image": "https://replicate.delivery/pbxt/N4zVyiww4DRB2g98bn4cIFapazY8q9IFDEJYeSAxiT43aFkc/Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg.webp",
      "dot_scale": 1,
      "grid_size": 21,
      "output_width": 1200,
      "brightness_threshold": 0
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

0.3 seconds

lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208

Prediction

Model

ID

banearr6c9rmc0cq1zps0by20g

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

0.1s

Created

about 1 month ago

Input

image
dot_scale: 1
grid_size: 20
output_width: 1024
brightness_threshold: 0.05

{
  "image": "https://replicate.delivery/pbxt/N4zhijOOWTPm92Pm4dTpGDTlQ8zH9QHyE69uWNNyI3PhxZL4/replicate-prediction-x7kq15rygnrmc0cq1zpbysbyt4.webp",
  "dot_scale": 1,
  "grid_size": 20,
  "output_width": 1024,
  "brightness_threshold": 0.05
}

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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
  {
    input: {
      image: "https://replicate.delivery/pbxt/N4zhijOOWTPm92Pm4dTpGDTlQ8zH9QHyE69uWNNyI3PhxZL4/replicate-prediction-x7kq15rygnrmc0cq1zpbysbyt4.webp",
      dot_scale: 1,
      grid_size: 20,
      output_width: 1024,
      brightness_threshold: 0.05
    }
  }
);

// 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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
    input={
        "image": "https://replicate.delivery/pbxt/N4zhijOOWTPm92Pm4dTpGDTlQ8zH9QHyE69uWNNyI3PhxZL4/replicate-prediction-x7kq15rygnrmc0cq1zpbysbyt4.webp",
        "dot_scale": 1,
        "grid_size": 20,
        "output_width": 1024,
        "brightness_threshold": 0.05
    }
)
print(output)

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

Run lucataco/vectorized-dot-grid 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": "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
    "input": {
      "image": "https://replicate.delivery/pbxt/N4zhijOOWTPm92Pm4dTpGDTlQ8zH9QHyE69uWNNyI3PhxZL4/replicate-prediction-x7kq15rygnrmc0cq1zpbysbyt4.webp",
      "dot_scale": 1,
      "grid_size": 20,
      "output_width": 1024,
      "brightness_threshold": 0.05
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

0.1 seconds

lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208

Prediction

Model

ID

3b5keevdehrm80cq1zvvdn1sk8

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

0.2s

Created

about 1 month ago

Input

image
dot_scale: 1
grid_size: 24
output_width: 1024
brightness_threshold: 0.1

{
  "image": "https://replicate.delivery/pbxt/N4zsSxYsIsgfxwz00NkHQKo3AXHd2XgpgxifwqmQYiAvo7Gb/girl-with-pearl.png",
  "dot_scale": 1,
  "grid_size": 24,
  "output_width": 1024,
  "brightness_threshold": 0.1
}

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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
  {
    input: {
      image: "https://replicate.delivery/pbxt/N4zsSxYsIsgfxwz00NkHQKo3AXHd2XgpgxifwqmQYiAvo7Gb/girl-with-pearl.png",
      dot_scale: 1,
      grid_size: 24,
      output_width: 1024,
      brightness_threshold: 0.1
    }
  }
);

// 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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
    input={
        "image": "https://replicate.delivery/pbxt/N4zsSxYsIsgfxwz00NkHQKo3AXHd2XgpgxifwqmQYiAvo7Gb/girl-with-pearl.png",
        "dot_scale": 1,
        "grid_size": 24,
        "output_width": 1024,
        "brightness_threshold": 0.1
    }
)
print(output)

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

Run lucataco/vectorized-dot-grid 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": "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
    "input": {
      "image": "https://replicate.delivery/pbxt/N4zsSxYsIsgfxwz00NkHQKo3AXHd2XgpgxifwqmQYiAvo7Gb/girl-with-pearl.png",
      "dot_scale": 1,
      "grid_size": 24,
      "output_width": 1024,
      "brightness_threshold": 0.1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

0.1 seconds

lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208

Prediction

Model

ID

a2k8yppav9rmc0cq1zw8j17ygg

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

0.2s

Created

about 1 month ago

Input

image
dot_scale: 1
grid_size: 10
output_width: 1024
brightness_threshold: 0

{
  "image": "https://replicate.delivery/pbxt/N4zttBghmSKOmtCJce44MJDBJPJ8PfKSlKllGrl0fBce944w/saint-jerome-paintings.jpg",
  "dot_scale": 1,
  "grid_size": 10,
  "output_width": 1024,
  "brightness_threshold": 0
}

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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
  {
    input: {
      image: "https://replicate.delivery/pbxt/N4zttBghmSKOmtCJce44MJDBJPJ8PfKSlKllGrl0fBce944w/saint-jerome-paintings.jpg",
      dot_scale: 1,
      grid_size: 10,
      output_width: 1024,
      brightness_threshold: 0
    }
  }
);

// 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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
    input={
        "image": "https://replicate.delivery/pbxt/N4zttBghmSKOmtCJce44MJDBJPJ8PfKSlKllGrl0fBce944w/saint-jerome-paintings.jpg",
        "dot_scale": 1,
        "grid_size": 10,
        "output_width": 1024,
        "brightness_threshold": 0
    }
)
print(output)

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

Run lucataco/vectorized-dot-grid 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": "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
    "input": {
      "image": "https://replicate.delivery/pbxt/N4zttBghmSKOmtCJce44MJDBJPJ8PfKSlKllGrl0fBce944w/saint-jerome-paintings.jpg",
      "dot_scale": 1,
      "grid_size": 10,
      "output_width": 1024,
      "brightness_threshold": 0
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

0.2 seconds

lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208

Prediction

Model

ID

d3841wmqn1rm80cq1zxthrygmr

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

0.2s

Created

about 1 month ago

Input

image
dot_scale: 1
grid_size: 14
output_width: 1024
brightness_threshold: 0.1

{
  "image": "https://replicate.delivery/pbxt/N4zwmKQKWPgxm1HjLJWXAhgIRwUj5g3aNeNyDPvMTAsKg2mN/Artist-in-a-very-entertaining-way-shows-what-could-happen-behind-the-scenes-of-famous-paintings-5c3b2d8ba65c4__880.jpg",
  "dot_scale": 1,
  "grid_size": 14,
  "output_width": 1024,
  "brightness_threshold": 0.1
}

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 lucataco/vectorized-dot-grid using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/vectorized-dot-grid:a5b8700fc30c78475b838305ed9e8f1a582d96f31da6d4233443bb89a9bb1208",
  {
    input: {
      image: "https://replicate.delivery/pbxt/N4zwmKQKWPgxm1HjLJWXAhgIRwUj5g3aNeNyDPvMTAsKg2mN/Artist-in-a-very-entertaining-way-shows-what-could-happen-behind-the-scenes-of-famous-paintings-5c3b2d8ba65c4__880.jpg",
      dot_scale: 1,
      grid_size: 14,
      output_width: 1024,
      brightness_threshold: 0.1
    }
  }
);

// 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.