marckohlbrugge/face-detect – Run with an API on Replicate

marckohlbrugge / face-detect

Detects faces and returns coordinates

Cold

Public
310 runs
L40S

Run with an API

Playground API Examples README Versions

Input

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

npx create-replicate --model=marckohlbrugge/face-detect

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";

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

Run marckohlbrugge/face-detect using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "marckohlbrugge/face-detect:8932afc017cd4f63d97693ce6f82de5daff86b54b6deae5629726510ca7ce191",
  {
    input: {}
  }
);
console.log(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 marckohlbrugge/face-detect using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "marckohlbrugge/face-detect:8932afc017cd4f63d97693ce6f82de5daff86b54b6deae5629726510ca7ce191",
    input={}
)
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 marckohlbrugge/face-detect 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": "8932afc017cd4f63d97693ce6f82de5daff86b54b6deae5629726510ca7ce191",
    "input": {}
  }' \
  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.

Run time and cost

This model costs approximately $0.00098 to run on Replicate, or 1020 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 1 seconds. The predict time for this model varies significantly based on the inputs.

Readme

Works the same Replicate’s SDXL Dreambooth does. So this allows you to quickly check whether certain images are appropriate for training with.