{
  "image_path": "https://replicate.delivery/pbxt/K4YmNrlSZH7muNDkvgwAtR81souWyCAueHkz7sEETzww2o8Z/image_6.jpg",
  "ref_object": "obj 1",
  "ref_measure": "width",
  "ref_pattern": 30,
  "select_option": 0
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run carcruz97/scaling-model-v3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "carcruz97/scaling-model-v3:137e715208bdc97e7cf3a5abb7715909c58100b5818179b409d8ea82da1e31d2",
  {
    input: {
      image_path: "https://replicate.delivery/pbxt/K4YmNrlSZH7muNDkvgwAtR81souWyCAueHkz7sEETzww2o8Z/image_6.jpg",
      ref_object: "obj 1",
      ref_measure: "width",
      ref_pattern: 30,
      select_option: 0
    }
  }
);

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

Import the client:

import replicate

Run carcruz97/scaling-model-v3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "carcruz97/scaling-model-v3:137e715208bdc97e7cf3a5abb7715909c58100b5818179b409d8ea82da1e31d2",
    input={
        "image_path": "https://replicate.delivery/pbxt/K4YmNrlSZH7muNDkvgwAtR81souWyCAueHkz7sEETzww2o8Z/image_6.jpg",
        "ref_object": "obj 1",
        "ref_measure": "width",
        "ref_pattern": 30,
        "select_option": 0
    }
)

print(output)

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

Run carcruz97/scaling-model-v3 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": "carcruz97/scaling-model-v3:137e715208bdc97e7cf3a5abb7715909c58100b5818179b409d8ea82da1e31d2",
    "input": {
      "image_path": "https://replicate.delivery/pbxt/K4YmNrlSZH7muNDkvgwAtR81souWyCAueHkz7sEETzww2o8Z/image_6.jpg",
      "ref_object": "obj 1",
      "ref_measure": "width",
      "ref_pattern": 30,
      "select_option": 0
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

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

Run this to download the model and run it in your local environment:

cog predict r8.im/carcruz97/scaling-model-v3@sha256:137e715208bdc97e7cf3a5abb7715909c58100b5818179b409d8ea82da1e31d2 \
  -i 'image_path="https://replicate.delivery/pbxt/K4YmNrlSZH7muNDkvgwAtR81souWyCAueHkz7sEETzww2o8Z/image_6.jpg"' \
  -i 'ref_object="obj 1"' \
  -i 'ref_measure="width"' \
  -i 'ref_pattern=30' \
  -i 'select_option=0'

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

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 r8.im/carcruz97/scaling-model-v3@sha256:137e715208bdc97e7cf3a5abb7715909c58100b5818179b409d8ea82da1e31d2
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "image_path": "https://replicate.delivery/pbxt/K4YmNrlSZH7muNDkvgwAtR81souWyCAueHkz7sEETzww2o8Z/image_6.jpg",
      "ref_object": "obj 1",
      "ref_measure": "width",
      "ref_pattern": 30,
      "select_option": 0
    }
  }' \
  http://localhost:5000/predictions

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

Output

{ "obj 1": { "area": 876.282, "width": 30.083, "height": 29.129, "perimeter": 8.704 }, "obj 2": { "area": 880.716, "width": 30.04, "height": 29.319, "perimeter": 8.726 }, "obj 3": { "area": 37.005, "width": 4.302, "height": 8.602, "perimeter": 1.897 }, "obj 4": { "area": 69.441, "width": 5.841, "height": 11.888, "perimeter": 2.606 } }

Generated in

3.4 seconds

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