Prediction

ID

v28xn7ve3xrj60cn2hvrvfgyc8

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

4m

Created

4 months ago

Input

seed: 42
task: fill
prompt: A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.
num_outputs: 1
control_image: book_masked.jpg?raw=true
output_format: webp
guidance_scale: 3.5
output_quality: 80
num_inference_steps: 8

{
  "seed": 42,
  "task": "fill",
  "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.",
  "num_outputs": 1,
  "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "num_inference_steps": 8
}

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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
  {
    input: {
      seed: 42,
      task: "fill",
      prompt: "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.",
      num_outputs: 1,
      control_image: "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 80,
      num_inference_steps: 8
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

pip install replicate

Import the client:

import replicate

Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    input={
        "seed": 42,
        "task": "fill",
        "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.",
        "num_outputs": 1,
        "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 80,
        "num_inference_steps": 8
    }
)
print(output)

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

Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    "input": {
      "seed": 42,
      "task": "fill",
      "prompt": "A yellow book with the word \'OMINI\' in large font on the cover. The text \'for FLUX\' appears at the bottom.",
      "num_outputs": 1,
      "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "num_inference_steps": 8
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

4.1 seconds

jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0

Prediction

Model

ID

v28xn7ve3xrj60cn2hvrvfgyc8

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

4m

Created

4 months ago

Input

seed: 42
task: fill
prompt: A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.
num_outputs: 1
control_image: book_masked.jpg?raw=true
output_format: webp
guidance_scale: 3.5
output_quality: 80
num_inference_steps: 8

{
  "seed": 42,
  "task": "fill",
  "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.",
  "num_outputs": 1,
  "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "num_inference_steps": 8
}

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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
  {
    input: {
      seed: 42,
      task: "fill",
      prompt: "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.",
      num_outputs: 1,
      control_image: "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 80,
      num_inference_steps: 8
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

pip install replicate

Import the client:

import replicate

Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    input={
        "seed": 42,
        "task": "fill",
        "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.",
        "num_outputs": 1,
        "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 80,
        "num_inference_steps": 8
    }
)
print(output)

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

Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    "input": {
      "seed": 42,
      "task": "fill",
      "prompt": "A yellow book with the word \'OMINI\' in large font on the cover. The text \'for FLUX\' appears at the bottom.",
      "num_outputs": 1,
      "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "num_inference_steps": 8
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

4.1 seconds

jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0

Prediction

Model

ID

g9azsgrz1xrj20cn2n4shsxyn0

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

2.9s

Created

4 months ago

Input

seed: 42
task: coloring
prompt: A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.
num_outputs: 1
control_image
output_format: webp
guidance_scale: 3.5
output_quality: 80
num_inference_steps: 8

{
  "seed": 42,
  "task": "coloring",
  "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.",
  "num_outputs": 1,
  "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "num_inference_steps": 8
}

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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
  {
    input: {
      seed: 42,
      task: "coloring",
      prompt: "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.",
      num_outputs: 1,
      control_image: "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 80,
      num_inference_steps: 8
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

pip install replicate

Import the client:

import replicate

Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    input={
        "seed": 42,
        "task": "coloring",
        "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.",
        "num_outputs": 1,
        "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 80,
        "num_inference_steps": 8
    }
)
print(output)

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

Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    "input": {
      "seed": 42,
      "task": "coloring",
      "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.",
      "num_outputs": 1,
      "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "num_inference_steps": 8
    }
  }' \
  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

jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0

Prediction

Model

ID

9c61tnj8msrj60cn2n4r935em0

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

4.0s

Created

4 months ago

Input

seed: 42
task: canny
prompt: A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.
num_outputs: 1
control_image
output_format: webp
guidance_scale: 3.5
output_quality: 80
num_inference_steps: 8

{
  "seed": 42,
  "task": "canny",
  "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.",
  "num_outputs": 1,
  "control_image": "https://replicate.delivery/pbxt/MW4dM8Ovbefmz957U7hWA1KfTq78jgt4WTBFpBqnCVDnwf1T/coffee.png",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "num_inference_steps": 8
}

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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
  {
    input: {
      seed: 42,
      task: "canny",
      prompt: "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.",
      num_outputs: 1,
      control_image: "https://replicate.delivery/pbxt/MW4dM8Ovbefmz957U7hWA1KfTq78jgt4WTBFpBqnCVDnwf1T/coffee.png",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 80,
      num_inference_steps: 8
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

pip install replicate

Import the client:

import replicate

Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    input={
        "seed": 42,
        "task": "canny",
        "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.",
        "num_outputs": 1,
        "control_image": "https://replicate.delivery/pbxt/MW4dM8Ovbefmz957U7hWA1KfTq78jgt4WTBFpBqnCVDnwf1T/coffee.png",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 80,
        "num_inference_steps": 8
    }
)
print(output)

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

Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    "input": {
      "seed": 42,
      "task": "canny",
      "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.",
      "num_outputs": 1,
      "control_image": "https://replicate.delivery/pbxt/MW4dM8Ovbefmz957U7hWA1KfTq78jgt4WTBFpBqnCVDnwf1T/coffee.png",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "num_inference_steps": 8
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

3.0 seconds

jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0

Prediction

Model

ID

4vf3k09rr5rj40cn2n4rka179c

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

5.0s

Created

4 months ago

Input

seed: 42
task: depth
prompt: A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.
num_outputs: 1
control_image
output_format: webp
guidance_scale: 3.5
output_quality: 80
num_inference_steps: 8

{
  "seed": 42,
  "task": "depth",
  "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.",
  "num_outputs": 1,
  "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "num_inference_steps": 8
}

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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
  {
    input: {
      seed: 42,
      task: "depth",
      prompt: "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.",
      num_outputs: 1,
      control_image: "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 80,
      num_inference_steps: 8
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

pip install replicate

Import the client:

import replicate

Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    input={
        "seed": 42,
        "task": "depth",
        "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.",
        "num_outputs": 1,
        "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 80,
        "num_inference_steps": 8
    }
)
print(output)

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

Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    "input": {
      "seed": 42,
      "task": "depth",
      "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.",
      "num_outputs": 1,
      "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "num_inference_steps": 8
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

5.0 seconds

jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0

Prediction

Model

ID

r8hrbdx5pnrj60cn2n5ay0pje0

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

4.6s

Created

4 months ago

Input

seed: 42
task: canny
prompt: In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.
num_outputs: 1
control_image
output_format: webp
guidance_scale: 3.5
output_quality: 80
num_inference_steps: 8

{
  "seed": 42,
  "task": "canny",
  "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
  "num_outputs": 1,
  "control_image": "https://replicate.delivery/pbxt/MW4em4udrQkhH3DvCZfuYeCx3foagX6Kfp5BKPtFH9n5gLbZ/coffee.png",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "num_inference_steps": 8
}

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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
  {
    input: {
      seed: 42,
      task: "canny",
      prompt: "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
      num_outputs: 1,
      control_image: "https://replicate.delivery/pbxt/MW4em4udrQkhH3DvCZfuYeCx3foagX6Kfp5BKPtFH9n5gLbZ/coffee.png",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 80,
      num_inference_steps: 8
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

pip install replicate

Import the client:

import replicate

Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    input={
        "seed": 42,
        "task": "canny",
        "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
        "num_outputs": 1,
        "control_image": "https://replicate.delivery/pbxt/MW4em4udrQkhH3DvCZfuYeCx3foagX6Kfp5BKPtFH9n5gLbZ/coffee.png",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 80,
        "num_inference_steps": 8
    }
)
print(output)

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

Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    "input": {
      "seed": 42,
      "task": "canny",
      "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
      "num_outputs": 1,
      "control_image": "https://replicate.delivery/pbxt/MW4em4udrQkhH3DvCZfuYeCx3foagX6Kfp5BKPtFH9n5gLbZ/coffee.png",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "num_inference_steps": 8
    }
  }' \
  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

jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0

Prediction

Model

ID

1x4np2wnsdrj00cn2n5aqzvnw4

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

5.4s

Created

4 months ago

Input

seed: 42
task: depth
prompt: In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.
num_outputs: 1
control_image
output_format: webp
guidance_scale: 3.5
output_quality: 80
num_inference_steps: 8

{
  "seed": 42,
  "task": "depth",
  "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
  "num_outputs": 1,
  "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "num_inference_steps": 8
}

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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
  {
    input: {
      seed: 42,
      task: "depth",
      prompt: "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
      num_outputs: 1,
      control_image: "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 80,
      num_inference_steps: 8
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

pip install replicate

Import the client:

import replicate

Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    input={
        "seed": 42,
        "task": "depth",
        "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
        "num_outputs": 1,
        "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 80,
        "num_inference_steps": 8
    }
)
print(output)

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

Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    "input": {
      "seed": 42,
      "task": "depth",
      "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
      "num_outputs": 1,
      "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "num_inference_steps": 8
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

4.9 seconds

jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0

Prediction

Model

ID

we46ex4ahxrj00cn2n5bxnsn40

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

3.3s

Created

4 months ago

Input

seed: 42
task: coloring
prompt: In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.
num_outputs: 1
control_image
output_format: webp
guidance_scale: 3.5
output_quality: 80
num_inference_steps: 8

{
  "seed": 42,
  "task": "coloring",
  "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
  "num_outputs": 1,
  "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "num_inference_steps": 8
}

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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
  {
    input: {
      seed: 42,
      task: "coloring",
      prompt: "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
      num_outputs: 1,
      control_image: "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 80,
      num_inference_steps: 8
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

pip install replicate

Import the client:

import replicate

Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    input={
        "seed": 42,
        "task": "coloring",
        "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
        "num_outputs": 1,
        "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 80,
        "num_inference_steps": 8
    }
)
print(output)

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

Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    "input": {
      "seed": 42,
      "task": "coloring",
      "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
      "num_outputs": 1,
      "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "num_inference_steps": 8
    }
  }' \
  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

jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0

Prediction

Model

ID

x52rx4m0b9rj00cn2n5acw77e0

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

2.9s

Created

4 months ago

Input

seed: 42
task: deblurring
prompt: In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.
num_outputs: 1
control_image
output_format: webp
guidance_scale: 3.5
output_quality: 80
num_inference_steps: 8

{
  "seed": 42,
  "task": "deblurring",
  "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
  "num_outputs": 1,
  "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "num_inference_steps": 8
}

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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
  {
    input: {
      seed: 42,
      task: "deblurring",
      prompt: "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
      num_outputs: 1,
      control_image: "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 80,
      num_inference_steps: 8
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

pip install replicate

Import the client:

import replicate

Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    input={
        "seed": 42,
        "task": "deblurring",
        "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
        "num_outputs": 1,
        "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 80,
        "num_inference_steps": 8
    }
)
print(output)

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

Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0",
    "input": {
      "seed": 42,
      "task": "deblurring",
      "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.",
      "num_outputs": 1,
      "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "num_inference_steps": 8
    }
  }' \
  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

jhorovitz/omini-dev:85dcc269f1e1c5f1258e955b3ec44a0ee663004d19a2122c963ad7bc238514d1

Prediction

Model

jhorovitz/omini-dev:85dcc269

ID

trmh2dbb65rj40cn30cvcfnwtm

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

71.0s

Created

4 months ago

Input

task: fill
prompt: A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.
num_outputs: 1
control_image: book_masked.jpg?raw=true
output_format: webp
guidance_scale: 3.5
output_quality: 80
num_inference_steps: 28

{
  "task": "fill",
  "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.",
  "num_outputs": 1,
  "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "num_inference_steps": 28
}

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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jhorovitz/omini-dev:85dcc269f1e1c5f1258e955b3ec44a0ee663004d19a2122c963ad7bc238514d1",
  {
    input: {
      task: "fill",
      prompt: "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.",
      num_outputs: 1,
      control_image: "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
      output_format: "webp",
      guidance_scale: 3.5,
      output_quality: 80,
      num_inference_steps: 28
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

pip install replicate

Import the client:

import replicate

Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jhorovitz/omini-dev:85dcc269f1e1c5f1258e955b3ec44a0ee663004d19a2122c963ad7bc238514d1",
    input={
        "task": "fill",
        "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.",
        "num_outputs": 1,
        "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
        "output_format": "webp",
        "guidance_scale": 3.5,
        "output_quality": 80,
        "num_inference_steps": 28
    }
)
print(output)

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

Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:85dcc269f1e1c5f1258e955b3ec44a0ee663004d19a2122c963ad7bc238514d1",
    "input": {
      "task": "fill",
      "prompt": "A yellow book with the word \'OMINI\' in large font on the cover. The text \'for FLUX\' appears at the bottom.",
      "num_outputs": 1,
      "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2025-02-18T08:09:04.853106Z",
  "created_at": "2025-02-18T08:07:53.905000Z",
  "data_removed": false,
  "error": null,
  "id": "trmh2dbb65rj40cn30cvcfnwtm",
  "input": {
    "task": "fill",
    "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.",
    "num_outputs": 1,
    "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true",
    "output_format": "webp",
    "guidance_scale": 3.5,
    "output_quality": 80,
    "num_inference_steps": 28
  },
  "logs": "Using seed: 10479\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:10,  2.59it/s]\n  7%|▋         | 2/28 [00:00<00:08,  3.05it/s]\n 11%|█         | 3/28 [00:00<00:08,  3.09it/s]\n 14%|█▍        | 4/28 [00:01<00:07,  3.10it/s]\n 18%|█▊        | 5/28 [00:01<00:07,  3.11it/s]\n 21%|██▏       | 6/28 [00:01<00:07,  3.12it/s]\n 25%|██▌       | 7/28 [00:02<00:06,  3.12it/s]\n 29%|██▊       | 8/28 [00:02<00:06,  3.13it/s]\n 32%|███▏      | 9/28 [00:02<00:06,  3.13it/s]\n 36%|███▌      | 10/28 [00:03<00:05,  3.13it/s]\n 39%|███▉      | 11/28 [00:03<00:05,  3.13it/s]\n 43%|████▎     | 12/28 [00:03<00:05,  3.13it/s]\n 46%|████▋     | 13/28 [00:04<00:04,  3.13it/s]\n 50%|█████     | 14/28 [00:04<00:04,  3.13it/s]\n 54%|█████▎    | 15/28 [00:04<00:04,  3.13it/s]\n 57%|█████▋    | 16/28 [00:05<00:03,  3.13it/s]\n 61%|██████    | 17/28 [00:05<00:03,  3.13it/s]\n 64%|██████▍   | 18/28 [00:05<00:03,  3.13it/s]\n 68%|██████▊   | 19/28 [00:06<00:02,  3.13it/s]\n 71%|███████▏  | 20/28 [00:06<00:02,  3.13it/s]\n 75%|███████▌  | 21/28 [00:06<00:02,  3.13it/s]\n 79%|███████▊  | 22/28 [00:07<00:01,  3.13it/s]\n 82%|████████▏ | 23/28 [00:07<00:01,  3.13it/s]\n 86%|████████▌ | 24/28 [00:07<00:01,  3.13it/s]\n 89%|████████▉ | 25/28 [00:08<00:00,  3.13it/s]\n 93%|█████████▎| 26/28 [00:08<00:00,  3.13it/s]\n 96%|█████████▋| 27/28 [00:08<00:00,  3.13it/s]\n100%|██████████| 28/28 [00:08<00:00,  3.13it/s]\n100%|██████████| 28/28 [00:08<00:00,  3.12it/s]",
  "metrics": {
    "predict_time": 10.53011346,
    "total_time": 70.948106
  },
  "output": [
    "https://replicate.delivery/yhqm/smr6RYHT2kpQCxmh094zuMeAVr0Acnqrpdif1JA6mLvgIfgoA/out-0.webp"
  ],
  "started_at": "2025-02-18T08:08:54.322992Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/yswh-ff4ijjglrur2k542vwoyirv7gb3tosqvaop4tr4zhsotwimgrnea",
    "get": "https://api.replicate.com/v1/predictions/trmh2dbb65rj40cn30cvcfnwtm",
    "cancel": "https://api.replicate.com/v1/predictions/trmh2dbb65rj40cn30cvcfnwtm/cancel"
  },
  "version": "85dcc269f1e1c5f1258e955b3ec44a0ee663004d19a2122c963ad7bc238514d1"
}

Generated in

10.5 seconds