remodela-ai/scaling-model-v1:85d9b712 | Run with an API on Replicate

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remodela-ai /scaling-model-v1:85d9b712

Playground API

Input

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

npx create-replicate --model=remodela-ai/scaling-model-v1

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 remodela-ai/scaling-model-v1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "remodela-ai/scaling-model-v1:85d9b712e93a86a30b60900fdf23dae1f7ef5836ba102ed26f65c3ed966f2595",
  {
    input: {
      image_path: "https://replicate.delivery/pbxt/K59gUS5aVHxuKN9JtKkMiaBIMSWAXCv33KHkTw1BPs6VKmdr/image_6.jpg",
      ref_object: "obj 1",
      ref_measure: "height",
      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

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 remodela-ai/scaling-model-v1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "remodela-ai/scaling-model-v1:85d9b712e93a86a30b60900fdf23dae1f7ef5836ba102ed26f65c3ed966f2595",
    input={
        "image_path": "https://replicate.delivery/pbxt/K59gUS5aVHxuKN9JtKkMiaBIMSWAXCv33KHkTw1BPs6VKmdr/image_6.jpg",
        "ref_object": "obj 1",
        "ref_measure": "height",
        "ref_pattern": 30,
        "select_option": 0
    }
)

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 remodela-ai/scaling-model-v1 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": "remodela-ai/scaling-model-v1:85d9b712e93a86a30b60900fdf23dae1f7ef5836ba102ed26f65c3ed966f2595",
    "input": {
      "image_path": "https://replicate.delivery/pbxt/K59gUS5aVHxuKN9JtKkMiaBIMSWAXCv33KHkTw1BPs6VKmdr/image_6.jpg",
      "ref_object": "obj 1",
      "ref_measure": "height",
      "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/remodela-ai/scaling-model-v1@sha256:85d9b712e93a86a30b60900fdf23dae1f7ef5836ba102ed26f65c3ed966f2595 \
  -i 'image_path="https://replicate.delivery/pbxt/K59gUS5aVHxuKN9JtKkMiaBIMSWAXCv33KHkTw1BPs6VKmdr/image_6.jpg"' \
  -i 'ref_object="obj 1"' \
  -i 'ref_measure="height"' \
  -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/remodela-ai/scaling-model-v1@sha256:85d9b712e93a86a30b60900fdf23dae1f7ef5836ba102ed26f65c3ed966f2595
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "image_path": "https://replicate.delivery/pbxt/K59gUS5aVHxuKN9JtKkMiaBIMSWAXCv33KHkTw1BPs6VKmdr/image_6.jpg",
      "ref_object": "obj 1",
      "ref_measure": "height",
      "ref_pattern": 30,
      "select_option": 0
    }
  }' \
  http://localhost:5000/predictions

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

Output

[ "Scaling of spaces in centimetres: ", { "obj 1": { "area": 924.62, "width": 30.901, "height": 29.922, "perimeter": 121.646 }, "obj 2": { "area": 929.298, "width": 30.857, "height": 30.116, "perimeter": 121.947 }, "obj 3": { "area": 39.046, "width": 4.419, "height": 8.836, "perimeter": 26.51 }, "obj 4": { "area": 73.272, "width": 6, "height": 12.212, "perimeter": 36.424 } } ]

Generated in

5.9 seconds

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