chigozienri/densepose:e2466793 | Run with an API on Replicate

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chigozienri /densepose:e2466793

Playground API

Input

input

*file

Input image or video

model

string

DensePose model. Read about the available models: https://github.com/facebookresearch/detectron2/blob/main/projects/DensePose/doc/DENSEPOSE_IUV.md

Default: "R_50_FPN_s1x"

overlay

boolean

Overlay the segmentation on the input image

Default: false

visualizer

string

Visualizer to use

Default: "FineSegmentation"

Run this model in Node.js with one line of code:

npx create-replicate --model=chigozienri/densepose

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

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

const output = await replicate.run(
  "chigozienri/densepose:e2466793b9a60a3891202f1b93527c5db7bbcd7dbb181c11958b50e25f2d55c3",
  {
    input: {
      model: "R_50_FPN_s1x",
      overlay: false,
      visualizer: "FineSegmentation"
    }
  }
);

// 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=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

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

output = replicate.run(
    "chigozienri/densepose:e2466793b9a60a3891202f1b93527c5db7bbcd7dbb181c11958b50e25f2d55c3",
    input={
        "model": "R_50_FPN_s1x",
        "overlay": False,
        "visualizer": "FineSegmentation"
    }
)
print(output)

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=<paste-your-token-here>

Find your API token in your account settings.

Run chigozienri/densepose 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": "chigozienri/densepose:e2466793b9a60a3891202f1b93527c5db7bbcd7dbb181c11958b50e25f2d55c3",
    "input": {
      "model": "R_50_FPN_s1x",
      "overlay": false,
      "visualizer": "FineSegmentation"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

No output yet! Press "Submit" to start a prediction.