Prediction

remodela-ai/scaling-model-v1:85d9b712e93a86a30b60900fdf23dae1f7ef5836ba102ed26f65c3ed966f2595

Model

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

ID

tlcsrdbbfimdmthymxjugcvkvq

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

6.1s

Created

over 1 year ago

Input

image_path
ref_object: obj 1
ref_measure: height
ref_pattern: 30
select_option: 0

{
  "image_path": "https://replicate.delivery/pbxt/K59gUS5aVHxuKN9JtKkMiaBIMSWAXCv33KHkTw1BPs6VKmdr/image_6.jpg",
  "ref_object": "obj 1",
  "ref_measure": "height",
  "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 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

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.

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

Tweak it Share Report

Prediction

remodela-ai/scaling-model-v1:85d9b712e93a86a30b60900fdf23dae1f7ef5836ba102ed26f65c3ed966f2595

Model

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

ID

v7ilshjb26v4mq2mwxthgwzqrm

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

6.1s

Created

over 1 year ago

Input

image_path
ref_object: obj 12
ref_measure: height
ref_pattern: 10
select_option: 0

{
  "image_path": "https://replicate.delivery/pbxt/K59ijTXGkfGRY1HwxVtXBe9P8J5pDhgxZzGaxEowEPjNk3aP/image_12.jpg",
  "ref_object": "obj 12",
  "ref_measure": "height",
  "ref_pattern": 10,
  "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 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/K59ijTXGkfGRY1HwxVtXBe9P8J5pDhgxZzGaxEowEPjNk3aP/image_12.jpg",
      ref_object: "obj 12",
      ref_measure: "height",
      ref_pattern: 10,
      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 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/K59ijTXGkfGRY1HwxVtXBe9P8J5pDhgxZzGaxEowEPjNk3aP/image_12.jpg",
        "ref_object": "obj 12",
        "ref_measure": "height",
        "ref_pattern": 10,
        "select_option": 0
    }
)

print(output)

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

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/K59ijTXGkfGRY1HwxVtXBe9P8J5pDhgxZzGaxEowEPjNk3aP/image_12.jpg",
      "ref_object": "obj 12",
      "ref_measure": "height",
      "ref_pattern": 10,
      "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/K59ijTXGkfGRY1HwxVtXBe9P8J5pDhgxZzGaxEowEPjNk3aP/image_12.jpg"' \
  -i 'ref_object="obj 12"' \
  -i 'ref_measure="height"' \
  -i 'ref_pattern=10' \
  -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/K59ijTXGkfGRY1HwxVtXBe9P8J5pDhgxZzGaxEowEPjNk3aP/image_12.jpg",
      "ref_object": "obj 12",
      "ref_measure": "height",
      "ref_pattern": 10,
      "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": 64.922, "width": 13.143, "height": 4.94, "perimeter": 36.165 }, "obj 2": { "area": 52.188, "width": 5.066, "height": 10.302, "perimeter": 30.736 }, "obj 3": { "area": 59.974, "width": 5.926, "height": 10.12, "perimeter": 32.093 }, "obj 4": { "area": 54.795, "width": 3.942, "height": 13.9, "perimeter": 35.684 }, "obj 5": { "area": 97.161, "width": 8.478, "height": 11.461, "perimeter": 39.877 }, "obj 6": { "area": 51.056, "width": 4.889, "height": 10.442, "perimeter": 30.663 }, "obj 7": { "area": 27.288, "width": 2.54, "height": 10.742, "perimeter": 26.565 }, "obj 8": { "area": 22.289, "width": 2.141, "height": 10.411, "perimeter": 25.104 }, "obj 9": { "area": 54.515, "width": 5.307, "height": 10.273, "perimeter": 31.159 }, "obj 10": { "area": 25.252, "width": 11.541, "height": 2.188, "perimeter": 27.458 }, "obj 11": { "area": 122.228, "width": 9.889, "height": 12.359, "perimeter": 44.498 }, "obj 12": { "area": 35.785, "width": 3.58, "height": 9.995, "perimeter": 27.15 }, "obj 13": { "area": 16.759, "width": 1.668, "height": 10.045, "perimeter": 23.427 }, "obj 14": { "area": 18.455, "width": 1.751, "height": 10.542, "perimeter": 24.586 }, "obj 15": { "area": 23.1, "width": 2.363, "height": 9.777, "perimeter": 24.28 }, "obj 16": { "area": 26.49, "width": 10.381, "height": 2.552, "perimeter": 25.866 }, "obj 17": { "area": 22.515, "width": 2.148, "height": 10.481, "perimeter": 25.258 }, "obj 18": { "area": 26.255, "width": 11.391, "height": 2.305, "perimeter": 27.391 } } ]

{
  "completed_at": "2023-12-20T14:51:49.611249Z",
  "created_at": "2023-12-20T14:51:43.527054Z",
  "data_removed": false,
  "error": null,
  "id": "v7ilshjb26v4mq2mwxthgwzqrm",
  "input": {
    "image_path": "https://replicate.delivery/pbxt/K59ijTXGkfGRY1HwxVtXBe9P8J5pDhgxZzGaxEowEPjNk3aP/image_12.jpg",
    "ref_object": "obj 12",
    "ref_measure": "height",
    "ref_pattern": 10,
    "select_option": 0
  },
  "logs": null,
  "metrics": {
    "predict_time": 5.914815,
    "total_time": 6.084195
  },
  "output": [
    "Scaling of spaces in centimetres: ",
    {
      "obj 1": {
        "area": 64.922,
        "width": 13.143,
        "height": 4.94,
        "perimeter": 36.165
      },
      "obj 2": {
        "area": 52.188,
        "width": 5.066,
        "height": 10.302,
        "perimeter": 30.736
      },
      "obj 3": {
        "area": 59.974,
        "width": 5.926,
        "height": 10.12,
        "perimeter": 32.093
      },
      "obj 4": {
        "area": 54.795,
        "width": 3.942,
        "height": 13.9,
        "perimeter": 35.684
      },
      "obj 5": {
        "area": 97.161,
        "width": 8.478,
        "height": 11.461,
        "perimeter": 39.877
      },
      "obj 6": {
        "area": 51.056,
        "width": 4.889,
        "height": 10.442,
        "perimeter": 30.663
      },
      "obj 7": {
        "area": 27.288,
        "width": 2.54,
        "height": 10.742,
        "perimeter": 26.565
      },
      "obj 8": {
        "area": 22.289,
        "width": 2.141,
        "height": 10.411,
        "perimeter": 25.104
      },
      "obj 9": {
        "area": 54.515,
        "width": 5.307,
        "height": 10.273,
        "perimeter": 31.159
      },
      "obj 10": {
        "area": 25.252,
        "width": 11.541,
        "height": 2.188,
        "perimeter": 27.458
      },
      "obj 11": {
        "area": 122.228,
        "width": 9.889,
        "height": 12.359,
        "perimeter": 44.498
      },
      "obj 12": {
        "area": 35.785,
        "width": 3.58,
        "height": 9.995,
        "perimeter": 27.15
      },
      "obj 13": {
        "area": 16.759,
        "width": 1.668,
        "height": 10.045,
        "perimeter": 23.427
      },
      "obj 14": {
        "area": 18.455,
        "width": 1.751,
        "height": 10.542,
        "perimeter": 24.586
      },
      "obj 15": {
        "area": 23.1,
        "width": 2.363,
        "height": 9.777,
        "perimeter": 24.28
      },
      "obj 16": {
        "area": 26.49,
        "width": 10.381,
        "height": 2.552,
        "perimeter": 25.866
      },
      "obj 17": {
        "area": 22.515,
        "width": 2.148,
        "height": 10.481,
        "perimeter": 25.258
      },
      "obj 18": {
        "area": 26.255,
        "width": 11.391,
        "height": 2.305,
        "perimeter": 27.391
      }
    }
  ],
  "started_at": "2023-12-20T14:51:43.696434Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/v7ilshjb26v4mq2mwxthgwzqrm",
    "cancel": "https://api.replicate.com/v1/predictions/v7ilshjb26v4mq2mwxthgwzqrm/cancel"
  },
  "version": "85d9b712e93a86a30b60900fdf23dae1f7ef5836ba102ed26f65c3ed966f2595"
}

Generated in

5.9 seconds

Tweak it Share Report

Prediction

remodela-ai/scaling-model-v1:85d9b712e93a86a30b60900fdf23dae1f7ef5836ba102ed26f65c3ed966f2595

Model

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

ID

btugqsbbrifl2hl65tkjf6clxi

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

5.7s

Created

over 1 year ago

Input

image_path
ref_object: obj 2
ref_measure: height
ref_pattern: 60
select_option: 0

{
  "image_path": "https://replicate.delivery/pbxt/K5AgrRIooaVJzQBgkNhh4c8nOFDZauLY70kZyIt3FRdwx9Qw/image_4.jpg",
  "ref_object": "obj 2",
  "ref_measure": "height",
  "ref_pattern": 60,
  "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 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/K5AgrRIooaVJzQBgkNhh4c8nOFDZauLY70kZyIt3FRdwx9Qw/image_4.jpg",
      ref_object: "obj 2",
      ref_measure: "height",
      ref_pattern: 60,
      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 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/K5AgrRIooaVJzQBgkNhh4c8nOFDZauLY70kZyIt3FRdwx9Qw/image_4.jpg",
        "ref_object": "obj 2",
        "ref_measure": "height",
        "ref_pattern": 60,
        "select_option": 0
    }
)

print(output)

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

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/K5AgrRIooaVJzQBgkNhh4c8nOFDZauLY70kZyIt3FRdwx9Qw/image_4.jpg",
      "ref_object": "obj 2",
      "ref_measure": "height",
      "ref_pattern": 60,
      "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/K5AgrRIooaVJzQBgkNhh4c8nOFDZauLY70kZyIt3FRdwx9Qw/image_4.jpg"' \
  -i 'ref_object="obj 2"' \
  -i 'ref_measure="height"' \
  -i 'ref_pattern=60' \
  -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/K5AgrRIooaVJzQBgkNhh4c8nOFDZauLY70kZyIt3FRdwx9Qw/image_4.jpg",
      "ref_object": "obj 2",
      "ref_measure": "height",
      "ref_pattern": 60,
      "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": 1782.084, "width": 40.077, "height": 44.467, "perimeter": 169.087 }, "obj 2": { "area": 4051.516, "width": 67.529, "height": 59.996, "perimeter": 255.051 } } ]

Generated in

5.5 seconds

Tweak it Share Report

Prediction

Input

Output

Prediction

Input

Output

Prediction

Input

Output

Logs (tlcsrdbbfimdmthymxjugcvkvq)

Logs (v7ilshjb26v4mq2mwxthgwzqrm)

Logs (btugqsbbrifl2hl65tkjf6clxi)