shreejalmaharjan-27/anime-face-detector:126f3db0

Version

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shreejalmaharjan-27 /anime-face-detector:126f3db0

Playground API

Input

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

npx create-replicate --model=shreejalmaharjan-27/anime-face-detector

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 shreejalmaharjan-27/anime-face-detector using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "shreejalmaharjan-27/anime-face-detector:126f3db0a62edf5e013299cc0b0fb4c3568acd4b9ea02b6eea07edc2721ead1e",
  {
    input: {
      iou: 0.5,
      size: 640,
      confidence: 0.4
    }
  }
);
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 shreejalmaharjan-27/anime-face-detector using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "shreejalmaharjan-27/anime-face-detector:126f3db0a62edf5e013299cc0b0fb4c3568acd4b9ea02b6eea07edc2721ead1e",
    input={
        "iou": 0.5,
        "size": 640,
        "confidence": 0.4
    }
)
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 shreejalmaharjan-27/anime-face-detector 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": "126f3db0a62edf5e013299cc0b0fb4c3568acd4b9ea02b6eea07edc2721ead1e",
    "input": {
      "iou": 0.5,
      "size": 640,
      "confidence": 0.4
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Install Cog

brew install cog

If you don’t have Homebrew, there are other installation options available.

Pull and run shreejalmaharjan-27/anime-face-detector using Cog (this will download the full model and run it in your local environment):

cog predict r8.im/shreejalmaharjan-27/anime-face-detector@sha256:126f3db0a62edf5e013299cc0b0fb4c3568acd4b9ea02b6eea07edc2721ead1e \
  -i 'iou=0.5' \
  -i 'size=640' \
  -i 'confidence=0.4'

To learn more, take a look at the Cog documentation.

Pull and run shreejalmaharjan-27/anime-face-detector using Docker (this will download the full model and run it in your local environment):

docker run -d -p 5000:5000 --gpus=all r8.im/shreejalmaharjan-27/anime-face-detector@sha256:126f3db0a62edf5e013299cc0b0fb4c3568acd4b9ea02b6eea07edc2721ead1e
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "iou": 0.5,
      "size": 640,
      "confidence": 0.4
    }
  }' \
  http://localhost:5000/predictions

Output

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