Prediction

ID

pr4btwwxfzh4bfxuat5uu67v7q

Status

Succeeded

Source

Web

Hardware

–

Total duration

1m 34s

Created

about 3 years ago

Input

input_image
output_format: Plot
confidence_threshold: 0.9

{
  "input_image": "https://replicate.delivery/mgxm/5bc4c9ed-d97e-4ae8-bb15-4b10614c6040/room.jpg",
  "output_format": "Plot",
  "confidence_threshold": 0.9
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
  {
    input: {
      input_image: "https://replicate.delivery/mgxm/5bc4c9ed-d97e-4ae8-bb15-4b10614c6040/room.jpg",
      output_format: "Plot",
      confidence_threshold: 0.9
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
    input={
        "input_image": "https://replicate.delivery/mgxm/5bc4c9ed-d97e-4ae8-bb15-4b10614c6040/room.jpg",
        "output_format": "Plot",
        "confidence_threshold": 0.9
    }
)

print(output)

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

Run davidgillsjo/srw-net 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": "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
    "input": {
      "input_image": "https://replicate.delivery/mgxm/5bc4c9ed-d97e-4ae8-bb15-4b10614c6040/room.jpg",
      "output_format": "Plot",
      "confidence_threshold": 0.9
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.8 seconds

davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036

Prediction

Model

ID

564cy62b3ff73eo46nnpipaz4q

Status

Succeeded

Source

Web

Hardware

–

Total duration

2.0s

Created

about 3 years ago

Input

input_image
output_format: Plot
confidence_threshold: 0.9

{
  "input_image": "https://replicate.delivery/mgxm/f6dd7d63-e08a-4845-aeb7-652578fc1b0e/corridor.jpg",
  "output_format": "Plot",
  "confidence_threshold": 0.9
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
  {
    input: {
      input_image: "https://replicate.delivery/mgxm/f6dd7d63-e08a-4845-aeb7-652578fc1b0e/corridor.jpg",
      output_format: "Plot",
      confidence_threshold: 0.9
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
    input={
        "input_image": "https://replicate.delivery/mgxm/f6dd7d63-e08a-4845-aeb7-652578fc1b0e/corridor.jpg",
        "output_format": "Plot",
        "confidence_threshold": 0.9
    }
)

print(output)

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

Run davidgillsjo/srw-net 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": "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
    "input": {
      "input_image": "https://replicate.delivery/mgxm/f6dd7d63-e08a-4845-aeb7-652578fc1b0e/corridor.jpg",
      "output_format": "Plot",
      "confidence_threshold": 0.9
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.9 seconds

davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036

Prediction

Model

ID

gqs5ruyj7baozirdnjozf5taum

Status

Succeeded

Source

Web

Hardware

–

Total duration

2.0s

Created

about 3 years ago

Input

input_image
output_format: Plot
confidence_threshold: 0.9

{
  "input_image": "https://replicate.delivery/mgxm/2e98a1de-c271-45ed-8d1d-5df49ee47147/corridor2.jpg",
  "output_format": "Plot",
  "confidence_threshold": 0.9
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
  {
    input: {
      input_image: "https://replicate.delivery/mgxm/2e98a1de-c271-45ed-8d1d-5df49ee47147/corridor2.jpg",
      output_format: "Plot",
      confidence_threshold: 0.9
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
    input={
        "input_image": "https://replicate.delivery/mgxm/2e98a1de-c271-45ed-8d1d-5df49ee47147/corridor2.jpg",
        "output_format": "Plot",
        "confidence_threshold": 0.9
    }
)

print(output)

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

Run davidgillsjo/srw-net 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": "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
    "input": {
      "input_image": "https://replicate.delivery/mgxm/2e98a1de-c271-45ed-8d1d-5df49ee47147/corridor2.jpg",
      "output_format": "Plot",
      "confidence_threshold": 0.9
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.9 seconds

davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036

Prediction

Model

ID

brsvj3gfxjgz3ccacrwjunva5i

Status

Succeeded

Source

Web

Hardware

–

Total duration

5.2s

Created

about 3 years ago

Input

input_image
output_format: Plot
confidence_threshold: 0.95

{
  "input_image": "https://replicate.delivery/mgxm/3cc0d5cf-2746-4d5c-852c-189d2f5453dc/ad3701fe3d568603.jpg",
  "output_format": "Plot",
  "confidence_threshold": 0.95
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
  {
    input: {
      input_image: "https://replicate.delivery/mgxm/3cc0d5cf-2746-4d5c-852c-189d2f5453dc/ad3701fe3d568603.jpg",
      output_format: "Plot",
      confidence_threshold: 0.95
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
    input={
        "input_image": "https://replicate.delivery/mgxm/3cc0d5cf-2746-4d5c-852c-189d2f5453dc/ad3701fe3d568603.jpg",
        "output_format": "Plot",
        "confidence_threshold": 0.95
    }
)

print(output)

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

Run davidgillsjo/srw-net 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": "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
    "input": {
      "input_image": "https://replicate.delivery/mgxm/3cc0d5cf-2746-4d5c-852c-189d2f5453dc/ad3701fe3d568603.jpg",
      "output_format": "Plot",
      "confidence_threshold": 0.95
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

5.0 seconds

davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036

Prediction

Model

ID

upfjjmt2azhinnzmtjzyelltwu

Status

Succeeded

Source

Web

Hardware

–

Total duration

4m 34s

Created

about 3 years ago by @vccheng2001

Input

input_image
output_format: Plot
confidence_threshold: 0.7

{
  "input_image": "https://replicate.delivery/mgxm/d8453982-b2c0-443c-b136-35928e3a63b1/master-bedroom-in-new-luxury-home-with-chandelier-and-larg.jpeg",
  "output_format": "Plot",
  "confidence_threshold": 0.7
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
  {
    input: {
      input_image: "https://replicate.delivery/mgxm/d8453982-b2c0-443c-b136-35928e3a63b1/master-bedroom-in-new-luxury-home-with-chandelier-and-larg.jpeg",
      output_format: "Plot",
      confidence_threshold: 0.7
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
    input={
        "input_image": "https://replicate.delivery/mgxm/d8453982-b2c0-443c-b136-35928e3a63b1/master-bedroom-in-new-luxury-home-with-chandelier-and-larg.jpeg",
        "output_format": "Plot",
        "confidence_threshold": 0.7
    }
)

print(output)

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

Run davidgillsjo/srw-net 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": "davidgillsjo/srw-net:7a3b45aa4a8be5c30a79184da92d7ad6d5b9ac185c26ebcbed3708cf707da036",
    "input": {
      "input_image": "https://replicate.delivery/mgxm/d8453982-b2c0-443c-b136-35928e3a63b1/master-bedroom-in-new-luxury-home-with-chandelier-and-larg.jpeg",
      "output_format": "Plot",
      "confidence_threshold": 0.7
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

6.5 seconds

davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c

Prediction

Model

ID

r3x4plyrjzbezel3zf6ilvpdi4

Status

Succeeded

Source

Web

Hardware

–

Total duration

1m 34s

Created

about 3 years ago

Input

input_image
output_format: Json
confidence_threshold: 0.9

{
  "input_image": "https://replicate.delivery/mgxm/5bc4c9ed-d97e-4ae8-bb15-4b10614c6040/room.jpg",
  "output_format": "Json",
  "confidence_threshold": 0.9
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c",
  {
    input: {
      input_image: "https://replicate.delivery/mgxm/5bc4c9ed-d97e-4ae8-bb15-4b10614c6040/room.jpg",
      output_format: "Json",
      confidence_threshold: 0.9
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c",
    input={
        "input_image": "https://replicate.delivery/mgxm/5bc4c9ed-d97e-4ae8-bb15-4b10614c6040/room.jpg",
        "output_format": "Json",
        "confidence_threshold": 0.9
    }
)

print(output)

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

Run davidgillsjo/srw-net 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": "davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c",
    "input": {
      "input_image": "https://replicate.delivery/mgxm/5bc4c9ed-d97e-4ae8-bb15-4b10614c6040/room.jpg",
      "output_format": "Json",
      "confidence_threshold": 0.9
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{ "Lines": [ { "type": "floor", "x1": 82.52734375, "y1": 1037.5133056640625, "x2": 922.1691284179688, "y2": 915.3350830078125 }, { "type": "wall", "x1": 82.52734375, "y1": 1037.5133056640625, "x2": 86.00208282470703, "y2": 220.39064025878906 }, { "type": "floor", "x1": 82.52734375, "y1": 1037.5133056640625, "x2": 0.019237995147705078, "y2": 1210.5810546875 }, { "type": "window", "x1": 2047.9981689453125, "y1": 90.39749145507812, "x2": 1542.742431640625, "y2": 257.729736328125 }, { "type": "window", "x1": 2047.9989013671875, "y1": 891.8460083007812, "x2": 1530.9671630859375, "y2": 841.6561889648438 }, { "type": "window", "x1": 475.5211486816406, "y1": 394.607421875, "x2": 477.1760559082031, "y2": 783.86328125 }, { "type": "window", "x1": 475.5211486816406, "y1": 394.607421875, "x2": 88.05802154541016, "y2": 337.3016662597656 }, { "type": "window", "x1": 477.1760559082031, "y1": 783.86328125, "x2": 72.5675048828125, "y2": 804.9552001953125 }, { "type": "floor", "x1": 2047.99365234375, "y1": 1317.217041015625, "x2": 922.1691284179688, "y2": 915.3350830078125 }, { "type": "floor", "x1": 2047.99365234375, "y1": 1317.217041015625, "x2": 1511.9517822265625, "y2": 1099.5526123046875 }, { "type": "window", "x1": 1542.742431640625, "y1": 257.729736328125, "x2": 1530.9671630859375, "y2": 841.6561889648438 }, { "type": "wall", "x1": 922.1929931640625, "y1": 360.14544677734375, "x2": 922.1691284179688, "y2": 915.3350830078125 }, { "type": "floor", "x1": 922.1691284179688, "y1": 915.3350830078125, "x2": 0.0810084342956543, "y2": 1040.91796875 } ], "Junctions": [ { "type": "proper", "x": 82.52734375, "y": 1037.5133056640625 }, { "type": "false", "x": 2047.9981689453125, "y": 90.39749145507812 }, { "type": "false", "x": 2047.9989013671875, "y": 891.8460083007812 }, { "type": "proper", "x": 475.5211486816406, "y": 394.607421875 }, { "type": "proper", "x": 477.1760559082031, "y": 783.86328125 }, { "type": "false", "x": 2047.99365234375, "y": 1317.217041015625 }, { "type": "proper", "x": 88.05802154541016, "y": 337.3016662597656 }, { "type": "proper", "x": 1542.742431640625, "y": 257.729736328125 }, { "type": "proper", "x": 922.1929931640625, "y": 360.14544677734375 }, { "type": "proper", "x": 922.1691284179688, "y": 915.3350830078125 }, { "type": "proper", "x": 1530.9671630859375, "y": 841.6561889648438 }, { "type": "proper", "x": 86.00208282470703, "y": 220.39064025878906 }, { "type": "proper", "x": 72.5675048828125, "y": 804.9552001953125 }, { "type": "false", "x": 0.019237995147705078, "y": 1210.5810546875 }, { "type": "false", "x": 0.0810084342956543, "y": 1040.91796875 }, { "type": "proper", "x": 1511.9517822265625, "y": 1099.5526123046875 } ] }

{
  "completed_at": "2022-06-25T19:27:24.614428Z",
  "created_at": "2022-06-25T19:25:50.806890Z",
  "data_removed": false,
  "error": null,
  "id": "r3x4plyrjzbezel3zf6ilvpdi4",
  "input": {
    "input_image": "https://replicate.delivery/mgxm/5bc4c9ed-d97e-4ae8-bb15-4b10614c6040/room.jpg",
    "output_format": "Json",
    "confidence_threshold": 0.9
  },
  "logs": "/root/.pyenv/versions/3.8.13/lib/python3.8/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at  ../aten/src/ATen/native/TensorShape.cpp:2157.)\n  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]",
  "metrics": {
    "predict_time": 1.481367,
    "total_time": 93.807538
  },
  "output": {
    "Json": "{\n    \"Lines\": [\n        {\n            \"type\": \"floor\",\n            \"x1\": 82.52734375,\n            \"y1\": 1037.5133056640625,\n            \"x2\": 922.1691284179688,\n            \"y2\": 915.3350830078125\n        },\n        {\n            \"type\": \"wall\",\n            \"x1\": 82.52734375,\n            \"y1\": 1037.5133056640625,\n            \"x2\": 86.00208282470703,\n            \"y2\": 220.39064025878906\n        },\n        {\n            \"type\": \"floor\",\n            \"x1\": 82.52734375,\n            \"y1\": 1037.5133056640625,\n            \"x2\": 0.019237995147705078,\n            \"y2\": 1210.5810546875\n        },\n        {\n            \"type\": \"window\",\n            \"x1\": 2047.9981689453125,\n            \"y1\": 90.39749145507812,\n            \"x2\": 1542.742431640625,\n            \"y2\": 257.729736328125\n        },\n        {\n            \"type\": \"window\",\n            \"x1\": 2047.9989013671875,\n            \"y1\": 891.8460083007812,\n            \"x2\": 1530.9671630859375,\n            \"y2\": 841.6561889648438\n        },\n        {\n            \"type\": \"window\",\n            \"x1\": 475.5211486816406,\n            \"y1\": 394.607421875,\n            \"x2\": 477.1760559082031,\n            \"y2\": 783.86328125\n        },\n        {\n            \"type\": \"window\",\n            \"x1\": 475.5211486816406,\n            \"y1\": 394.607421875,\n            \"x2\": 88.05802154541016,\n            \"y2\": 337.3016662597656\n        },\n        {\n            \"type\": \"window\",\n            \"x1\": 477.1760559082031,\n            \"y1\": 783.86328125,\n            \"x2\": 72.5675048828125,\n            \"y2\": 804.9552001953125\n        },\n        {\n            \"type\": \"floor\",\n            \"x1\": 2047.99365234375,\n            \"y1\": 1317.217041015625,\n            \"x2\": 922.1691284179688,\n            \"y2\": 915.3350830078125\n        },\n        {\n            \"type\": \"floor\",\n            \"x1\": 2047.99365234375,\n            \"y1\": 1317.217041015625,\n            \"x2\": 1511.9517822265625,\n            \"y2\": 1099.5526123046875\n        },\n        {\n            \"type\": \"window\",\n            \"x1\": 1542.742431640625,\n            \"y1\": 257.729736328125,\n            \"x2\": 1530.9671630859375,\n            \"y2\": 841.6561889648438\n        },\n        {\n            \"type\": \"wall\",\n            \"x1\": 922.1929931640625,\n            \"y1\": 360.14544677734375,\n            \"x2\": 922.1691284179688,\n            \"y2\": 915.3350830078125\n        },\n        {\n            \"type\": \"floor\",\n            \"x1\": 922.1691284179688,\n            \"y1\": 915.3350830078125,\n            \"x2\": 0.0810084342956543,\n            \"y2\": 1040.91796875\n        }\n    ],\n    \"Junctions\": [\n        {\n            \"type\": \"proper\",\n            \"x\": 82.52734375,\n            \"y\": 1037.5133056640625\n        },\n        {\n            \"type\": \"false\",\n            \"x\": 2047.9981689453125,\n            \"y\": 90.39749145507812\n        },\n        {\n            \"type\": \"false\",\n            \"x\": 2047.9989013671875,\n            \"y\": 891.8460083007812\n        },\n        {\n            \"type\": \"proper\",\n            \"x\": 475.5211486816406,\n            \"y\": 394.607421875\n        },\n        {\n            \"type\": \"proper\",\n            \"x\": 477.1760559082031,\n            \"y\": 783.86328125\n        },\n        {\n            \"type\": \"false\",\n            \"x\": 2047.99365234375,\n            \"y\": 1317.217041015625\n        },\n        {\n            \"type\": \"proper\",\n            \"x\": 88.05802154541016,\n            \"y\": 337.3016662597656\n        },\n        {\n            \"type\": \"proper\",\n            \"x\": 1542.742431640625,\n            \"y\": 257.729736328125\n        },\n        {\n            \"type\": \"proper\",\n            \"x\": 922.1929931640625,\n            \"y\": 360.14544677734375\n        },\n        {\n            \"type\": \"proper\",\n            \"x\": 922.1691284179688,\n            \"y\": 915.3350830078125\n        },\n        {\n            \"type\": \"proper\",\n            \"x\": 1530.9671630859375,\n            \"y\": 841.6561889648438\n        },\n        {\n            \"type\": \"proper\",\n            \"x\": 86.00208282470703,\n            \"y\": 220.39064025878906\n        },\n        {\n            \"type\": \"proper\",\n            \"x\": 72.5675048828125,\n            \"y\": 804.9552001953125\n        },\n        {\n            \"type\": \"false\",\n            \"x\": 0.019237995147705078,\n            \"y\": 1210.5810546875\n        },\n        {\n            \"type\": \"false\",\n            \"x\": 0.0810084342956543,\n            \"y\": 1040.91796875\n        },\n        {\n            \"type\": \"proper\",\n            \"x\": 1511.9517822265625,\n            \"y\": 1099.5526123046875\n        }\n    ]\n}"
  },
  "started_at": "2022-06-25T19:27:23.133061Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/r3x4plyrjzbezel3zf6ilvpdi4",
    "cancel": "https://api.replicate.com/v1/predictions/r3x4plyrjzbezel3zf6ilvpdi4/cancel"
  },
  "version": "a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c"
}

Generated in

1.5 seconds

davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c

Prediction

Model

ID

weikvuzuxnfy7hh6kdzvtupk3m

Status

Succeeded

Source

Web

Hardware

–

Total duration

70.9s

Created

about 3 years ago

Input

input_image
output_format: Plot
confidence_threshold: 0.9

{
  "input_image": "https://replicate.delivery/mgxm/5e1dde05-b3ac-4275-9dca-d518cbcd41e8/S03252R687593P0.png",
  "output_format": "Plot",
  "confidence_threshold": 0.9
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c",
  {
    input: {
      input_image: "https://replicate.delivery/mgxm/5e1dde05-b3ac-4275-9dca-d518cbcd41e8/S03252R687593P0.png",
      output_format: "Plot",
      confidence_threshold: 0.9
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c",
    input={
        "input_image": "https://replicate.delivery/mgxm/5e1dde05-b3ac-4275-9dca-d518cbcd41e8/S03252R687593P0.png",
        "output_format": "Plot",
        "confidence_threshold": 0.9
    }
)

print(output)

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

Run davidgillsjo/srw-net 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": "davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c",
    "input": {
      "input_image": "https://replicate.delivery/mgxm/5e1dde05-b3ac-4275-9dca-d518cbcd41e8/S03252R687593P0.png",
      "output_format": "Plot",
      "confidence_threshold": 0.9
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

0 milliseconds

davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c

Prediction

Model

ID

uwtkzahdargxpm5gfswupbdem4

Status

Succeeded

Source

Web

Hardware

–

Total duration

24.7s

Created

about 3 years ago by @davidgillsjo

Input

input_image
output_format: Plot
confidence_threshold: 0.9

{
  "input_image": "https://replicate.delivery/mgxm/b56de6bc-ec1f-4298-8b22-9fc79678f0c1/S03302R877178P2.png",
  "output_format": "Plot",
  "confidence_threshold": 0.9
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c",
  {
    input: {
      input_image: "https://replicate.delivery/mgxm/b56de6bc-ec1f-4298-8b22-9fc79678f0c1/S03302R877178P2.png",
      output_format: "Plot",
      confidence_threshold: 0.9
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c",
    input={
        "input_image": "https://replicate.delivery/mgxm/b56de6bc-ec1f-4298-8b22-9fc79678f0c1/S03302R877178P2.png",
        "output_format": "Plot",
        "confidence_threshold": 0.9
    }
)

print(output)

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

Run davidgillsjo/srw-net 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": "davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c",
    "input": {
      "input_image": "https://replicate.delivery/mgxm/b56de6bc-ec1f-4298-8b22-9fc79678f0c1/S03302R877178P2.png",
      "output_format": "Plot",
      "confidence_threshold": 0.9
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.4 seconds

davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c

Prediction

Model

ID

6s32e7nadjelvpn45eutud54yq

Status

Succeeded

Source

Web

Hardware

–

Total duration

3.5s

Created

about 3 years ago

Input

input_image
output_format: Plot
confidence_threshold: 0.9

{
  "input_image": "https://replicate.delivery/mgxm/ea469c8a-37f9-4680-bac4-43d93561371a/S03256R352325P1.png",
  "output_format": "Plot",
  "confidence_threshold": 0.9
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c",
  {
    input: {
      input_image: "https://replicate.delivery/mgxm/ea469c8a-37f9-4680-bac4-43d93561371a/S03256R352325P1.png",
      output_format: "Plot",
      confidence_threshold: 0.9
    }
  }
);

console.log(output);

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

pip install replicate

Import the client:

import replicate

Run davidgillsjo/srw-net using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c",
    input={
        "input_image": "https://replicate.delivery/mgxm/ea469c8a-37f9-4680-bac4-43d93561371a/S03256R352325P1.png",
        "output_format": "Plot",
        "confidence_threshold": 0.9
    }
)

print(output)

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

Run davidgillsjo/srw-net 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": "davidgillsjo/srw-net:a3b8d86433a774113ebc48b1b853897dda957a0ff792c7bfb1d6b9781081994c",
    "input": {
      "input_image": "https://replicate.delivery/mgxm/ea469c8a-37f9-4680-bac4-43d93561371a/S03256R352325P1.png",
      "output_format": "Plot",
      "confidence_threshold": 0.9
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

3.3 seconds