Prediction

Model

kjjk10/lotus-diffusion-dense-prediction:9f9fa3ac

fgk9zbprxxrmc0cm9bcvg2cjcw

Status

Succeeded

Source

Web

Hardware

L40S

Total duration

0.9s

Created

11 months ago

Webhook

–

Input

image: https://replicate.delivery/pbxt/MI7Y55NgzZF7SddYf5V945wD38HkxrXaj9HEJsLzenwYW4Dp/5w3lt2f6zlr61.png
output_type: color
resample_method: bicubic
processing_resolution: 0
disparity: true

{
  "disparity": true,
  "image": "https://replicate.delivery/pbxt/MI7Y55NgzZF7SddYf5V945wD38HkxrXaj9HEJsLzenwYW4Dp/5w3lt2f6zlr61.png",
  "output_type": "color",
  "processing_resolution": 0,
  "resample_method": "bicubic"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_MJ9**********************************

This is your API token. Keep it to yourself.

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 kjjk10/lotus-diffusion-dense-prediction using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "kjjk10/lotus-diffusion-dense-prediction:9f9fa3ac2f263ba1551e6ae84a0fbd724c7bc166e5e416d132809c75f5ebb391",
  {
    input: {
      disparity: true,
      image: "https://replicate.delivery/pbxt/MI7Y55NgzZF7SddYf5V945wD38HkxrXaj9HEJsLzenwYW4Dp/5w3lt2f6zlr61.png",
      output_type: "color",
      processing_resolution: 0,
      resample_method: "bicubic"
    }
  }
);

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

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

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

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_MJ9**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run kjjk10/lotus-diffusion-dense-prediction using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "kjjk10/lotus-diffusion-dense-prediction:9f9fa3ac2f263ba1551e6ae84a0fbd724c7bc166e5e416d132809c75f5ebb391",
    input={
        "disparity": True,
        "image": "https://replicate.delivery/pbxt/MI7Y55NgzZF7SddYf5V945wD38HkxrXaj9HEJsLzenwYW4Dp/5w3lt2f6zlr61.png",
        "output_type": "color",
        "processing_resolution": 0,
        "resample_method": "bicubic"
    }
)

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

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

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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_MJ9**********************************

This is your API token. Keep it to yourself.

Run kjjk10/lotus-diffusion-dense-prediction 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": "kjjk10/lotus-diffusion-dense-prediction:9f9fa3ac2f263ba1551e6ae84a0fbd724c7bc166e5e416d132809c75f5ebb391",
    "input": {
      "disparity": true,
      "image": "https://replicate.delivery/pbxt/MI7Y55NgzZF7SddYf5V945wD38HkxrXaj9HEJsLzenwYW4Dp/5w3lt2f6zlr61.png",
      "output_type": "color",
      "processing_resolution": 0,
      "resample_method": "bicubic"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

0.9 seconds

Tweak it Report