Prediction

ID

apkjznnwgsrgp0cga58b2rgpgm

Status

Succeeded

Source

Web

Hardware

A40

Total duration

2.3s

Created

about 1 year ago

Input

image
task_input: Object Detection

{
  "image": "https://replicate.delivery/pbxt/L9zDhV2KiVnudUyRiNjt9P18LZ98Hrqq5GGdx9szmBCAyEhP/car.jpg",
  "task_input": "Object Detection"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run lucataco/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
  {
    input: {
      image: "https://replicate.delivery/pbxt/L9zDhV2KiVnudUyRiNjt9P18LZ98Hrqq5GGdx9szmBCAyEhP/car.jpg",
      task_input: "Object Detection"
    }
  }
);

console.log(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/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    input={
        "image": "https://replicate.delivery/pbxt/L9zDhV2KiVnudUyRiNjt9P18LZ98Hrqq5GGdx9szmBCAyEhP/car.jpg",
        "task_input": "Object Detection"
    }
)

print(output)

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

Run lucataco/florence-2-large 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/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    "input": {
      "image": "https://replicate.delivery/pbxt/L9zDhV2KiVnudUyRiNjt9P18LZ98Hrqq5GGdx9szmBCAyEhP/car.jpg",
      "task_input": "Object Detection"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

img

text

{'<OD>': {'bboxes': [[34.23999786376953, 160.0800018310547, 597.4400024414062, 371.7599792480469], [456.0, 97.68000030517578, 580.1599731445312, 261.8399963378906], [450.8800048828125, 276.7200012207031, 554.5599975585938, 370.79998779296875], [95.68000030517578, 280.55999755859375, 198.72000122070312, 371.2799987792969]], 'labels': ['car', 'door', 'wheel', 'wheel']}}

Generated in

2.3 seconds

lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595

Prediction

Model

ID

p9vn496sqnrgg0cga58b20bmk4

Status

Succeeded

Source

Web

Hardware

A40

Total duration

0.7s

Created

about 1 year ago

Input

image
task_input: Caption

{
  "image": "https://replicate.delivery/pbxt/L9zDpELNFFAwSbhwbv4ZgjAtcpaq7QYMb1XMRqjrIRtFwB6t/car.jpg",
  "task_input": "Caption"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run lucataco/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
  {
    input: {
      image: "https://replicate.delivery/pbxt/L9zDpELNFFAwSbhwbv4ZgjAtcpaq7QYMb1XMRqjrIRtFwB6t/car.jpg",
      task_input: "Caption"
    }
  }
);

console.log(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/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    input={
        "image": "https://replicate.delivery/pbxt/L9zDpELNFFAwSbhwbv4ZgjAtcpaq7QYMb1XMRqjrIRtFwB6t/car.jpg",
        "task_input": "Caption"
    }
)

print(output)

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

Run lucataco/florence-2-large 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/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    "input": {
      "image": "https://replicate.delivery/pbxt/L9zDpELNFFAwSbhwbv4ZgjAtcpaq7QYMb1XMRqjrIRtFwB6t/car.jpg",
      "task_input": "Caption"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{'<CAPTION>': 'A green car parked in front of a yellow building.'}

Generated in

0.7 seconds

lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595

Prediction

Model

ID

vyzgpdzjz5rgp0cga588t5d61w

Status

Succeeded

Source

Web

Hardware

A40

Total duration

1.0s

Created

about 1 year ago

Input

image
task_input: Detailed Caption

{
  "image": "https://replicate.delivery/pbxt/L9zDujwtc72pHN0MjwSx5O8megTelbxhCFnuV2hhwR56rfDG/car.jpg",
  "task_input": "Detailed Caption"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run lucataco/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
  {
    input: {
      image: "https://replicate.delivery/pbxt/L9zDujwtc72pHN0MjwSx5O8megTelbxhCFnuV2hhwR56rfDG/car.jpg",
      task_input: "Detailed Caption"
    }
  }
);

console.log(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/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    input={
        "image": "https://replicate.delivery/pbxt/L9zDujwtc72pHN0MjwSx5O8megTelbxhCFnuV2hhwR56rfDG/car.jpg",
        "task_input": "Detailed Caption"
    }
)

print(output)

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

Run lucataco/florence-2-large 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/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    "input": {
      "image": "https://replicate.delivery/pbxt/L9zDujwtc72pHN0MjwSx5O8megTelbxhCFnuV2hhwR56rfDG/car.jpg",
      "task_input": "Detailed Caption"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{'<DETAILED_CAPTION>': 'The image shows a blue Volkswagen Beetle parked in front of a yellow building with two brown doors, surrounded by trees and a clear blue sky.'}

Generated in

1.0 second

lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595

Prediction

Model

ID

28dsk3g8a5rgp0cga58tbe5vzm

Status

Succeeded

Source

Web

Hardware

A40

Total duration

1.7s

Created

about 1 year ago

Input

image
task_input: More Detailed Caption

{
  "image": "https://replicate.delivery/pbxt/L9zE0k7IFWYlMGdsSg2Ua5Kbi8Jo3FsALg4pPVOMf2jUKvwM/car.jpg",
  "task_input": "More Detailed Caption"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run lucataco/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
  {
    input: {
      image: "https://replicate.delivery/pbxt/L9zE0k7IFWYlMGdsSg2Ua5Kbi8Jo3FsALg4pPVOMf2jUKvwM/car.jpg",
      task_input: "More Detailed Caption"
    }
  }
);

console.log(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/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    input={
        "image": "https://replicate.delivery/pbxt/L9zE0k7IFWYlMGdsSg2Ua5Kbi8Jo3FsALg4pPVOMf2jUKvwM/car.jpg",
        "task_input": "More Detailed Caption"
    }
)

print(output)

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

Run lucataco/florence-2-large 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/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    "input": {
      "image": "https://replicate.delivery/pbxt/L9zE0k7IFWYlMGdsSg2Ua5Kbi8Jo3FsALg4pPVOMf2jUKvwM/car.jpg",
      "task_input": "More Detailed Caption"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{'<MORE_DETAILED_CAPTION>': 'The image shows a vintage Volkswagen Beetle car parked on a cobblestone street in front of a yellow building with two wooden doors. The car is painted in a bright turquoise color and has a white stripe running along the side. It has two doors on either side of the car, one on top of the other, and a small window on the front. The building appears to be old and dilapidated, with peeling paint and crumbling walls. The sky is blue and there are trees in the background.'}

Generated in

1.6 seconds

lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595

Prediction

Model

ID

mkv9v3tg8nrgj0cga58t9tewcg

Status

Succeeded

Source

Web

Hardware

A40

Total duration

2.3s

Created

about 1 year ago

Input

image
task_input: Caption to Phrase Grounding
text_input: A green car parked in front of a yellow building.

{
  "image": "https://replicate.delivery/pbxt/L9zEIjeWave7f5eBQLzX7wi0OdhdboK148R3y3v23cvKItsS/car.jpg",
  "task_input": "Caption to Phrase Grounding",
  "text_input": "A green car parked in front of a yellow building."
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run lucataco/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
  {
    input: {
      image: "https://replicate.delivery/pbxt/L9zEIjeWave7f5eBQLzX7wi0OdhdboK148R3y3v23cvKItsS/car.jpg",
      task_input: "Caption to Phrase Grounding",
      text_input: "A green car parked in front of a yellow building."
    }
  }
);

console.log(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/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    input={
        "image": "https://replicate.delivery/pbxt/L9zEIjeWave7f5eBQLzX7wi0OdhdboK148R3y3v23cvKItsS/car.jpg",
        "task_input": "Caption to Phrase Grounding",
        "text_input": "A green car parked in front of a yellow building."
    }
)

print(output)

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

Run lucataco/florence-2-large 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/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    "input": {
      "image": "https://replicate.delivery/pbxt/L9zEIjeWave7f5eBQLzX7wi0OdhdboK148R3y3v23cvKItsS/car.jpg",
      "task_input": "Caption to Phrase Grounding",
      "text_input": "A green car parked in front of a yellow building."
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

img

text

{'<CAPTION_TO_PHRASE_GROUNDING>': {'bboxes': [[34.880001068115234, 158.63999938964844, 583.3599853515625, 374.6399841308594], [0.3199999928474426, 4.079999923706055, 639.0399780273438, 305.03997802734375]], 'labels': ['A green car', 'a yellow building']}}

Generated in

2.2 seconds

lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595

Prediction

Model

ID

31xdc72d4srgm0cga59b26fvwg

Status

Succeeded

Source

Web

Hardware

A40

Total duration

2.4s

Created

about 1 year ago

Input

image
task_input: Region Proposal

{
  "image": "https://replicate.delivery/pbxt/L9zDhV2KiVnudUyRiNjt9P18LZ98Hrqq5GGdx9szmBCAyEhP/car.jpg",
  "task_input": "Region Proposal"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run lucataco/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
  {
    input: {
      image: "https://replicate.delivery/pbxt/L9zDhV2KiVnudUyRiNjt9P18LZ98Hrqq5GGdx9szmBCAyEhP/car.jpg",
      task_input: "Region Proposal"
    }
  }
);

console.log(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/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    input={
        "image": "https://replicate.delivery/pbxt/L9zDhV2KiVnudUyRiNjt9P18LZ98Hrqq5GGdx9szmBCAyEhP/car.jpg",
        "task_input": "Region Proposal"
    }
)

print(output)

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

Run lucataco/florence-2-large 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/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    "input": {
      "image": "https://replicate.delivery/pbxt/L9zDhV2KiVnudUyRiNjt9P18LZ98Hrqq5GGdx9szmBCAyEhP/car.jpg",
      "task_input": "Region Proposal"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

img

text

{'<REGION_PROPOSAL>': {'bboxes': [[33.599998474121094, 160.0800018310547, 596.7999877929688, 371.7599792480469], [455.3599853515625, 97.68000030517578, 579.5199584960938, 261.8399963378906], [450.8800048828125, 276.7200012207031, 553.2799682617188, 370.79998779296875], [95.04000091552734, 280.55999755859375, 198.0800018310547, 371.2799987792969], [226.87998962402344, 88.55999755859375, 332.47998046875, 164.39999389648438], [65.5999984741211, 266.6399841308594, 86.72000122070312, 295.91998291015625], [271.67999267578125, 241.67999267578125, 302.3999938964844, 246.95999145507812], [408.0, 308.3999938964844, 413.7599792480469, 320.8800048828125]], 'labels': ['', '', '', '', '', '', '', '']}}

Generated in

2.3 seconds

lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595

Prediction

Model

ID

dtm0z83cr9rgg0cga599v4793r

Status

Succeeded

Source

Web

Hardware

A40

Total duration

2.2s

Created

about 1 year ago

Input

image
task_input: Dense Region Caption

{
  "image": "https://replicate.delivery/pbxt/L9zDhV2KiVnudUyRiNjt9P18LZ98Hrqq5GGdx9szmBCAyEhP/car.jpg",
  "task_input": "Dense Region Caption"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run lucataco/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
  {
    input: {
      image: "https://replicate.delivery/pbxt/L9zDhV2KiVnudUyRiNjt9P18LZ98Hrqq5GGdx9szmBCAyEhP/car.jpg",
      task_input: "Dense Region Caption"
    }
  }
);

console.log(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/florence-2-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    input={
        "image": "https://replicate.delivery/pbxt/L9zDhV2KiVnudUyRiNjt9P18LZ98Hrqq5GGdx9szmBCAyEhP/car.jpg",
        "task_input": "Dense Region Caption"
    }
)

print(output)

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

Run lucataco/florence-2-large 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/florence-2-large:da53547e17d45b9cfb48174b2f18af8b83ca020fa76db62136bf9c6616762595",
    "input": {
      "image": "https://replicate.delivery/pbxt/L9zDhV2KiVnudUyRiNjt9P18LZ98Hrqq5GGdx9szmBCAyEhP/car.jpg",
      "task_input": "Dense Region Caption"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

img

text

{'<DENSE_REGION_CAPTION>': {'bboxes': [[33.599998474121094, 160.0800018310547, 596.7999877929688, 371.7599792480469], [450.8800048828125, 276.7200012207031, 553.2799682617188, 370.79998779296875], [95.04000091552734, 280.55999755859375, 197.44000244140625, 371.2799987792969]], 'labels': ['turquoise Volkswagen Beetle', 'wheel', 'wheel']}}

Generated in

2.1 seconds