bfirsh/segformer-b0-finetuned-ade-512-512 | Run with an API on Replicate

Input

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

npx create-replicate --model=bfirsh/segformer-b0-finetuned-ade-512-512

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 bfirsh/segformer-b0-finetuned-ade-512-512 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "bfirsh/segformer-b0-finetuned-ade-512-512:dd2a716c1acef7c4c69926b17cdd054fa64dd56628e9edb8c9234af3840a064e",
  {
    input: {
      image: "https://replicate.delivery/mgxm/8b0ccb6f-f124-43a2-b7c2-9687b09d1e78/Fe5FTEPXgAEXTFY.jpeg"
    }
  }
);

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 bfirsh/segformer-b0-finetuned-ade-512-512 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "bfirsh/segformer-b0-finetuned-ade-512-512:dd2a716c1acef7c4c69926b17cdd054fa64dd56628e9edb8c9234af3840a064e",
    input={
        "image": "https://replicate.delivery/mgxm/8b0ccb6f-f124-43a2-b7c2-9687b09d1e78/Fe5FTEPXgAEXTFY.jpeg"
    }
)

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 bfirsh/segformer-b0-finetuned-ade-512-512 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": "bfirsh/segformer-b0-finetuned-ade-512-512:dd2a716c1acef7c4c69926b17cdd054fa64dd56628e9edb8c9234af3840a064e",
    "input": {
      "image": "https://replicate.delivery/mgxm/8b0ccb6f-f124-43a2-b7c2-9687b09d1e78/Fe5FTEPXgAEXTFY.jpeg"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

mask

label

wall

mask

label

floor

mask

label

ceiling

mask

label

windowpane

mask

label

door

mask

label

lamp

mask

label

chandelier

Generated in

7.5 seconds

Tweak itReport View full prediction

Examples

View more examples

Run time and cost

This model costs approximately $0.010 to run on Replicate, or 100 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia T4 GPU hardware. Predictions typically complete within 45 seconds. The predict time for this model varies significantly based on the inputs.

Readme

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Model description

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Intended use

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Ethical considerations

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Caveats and recommendations

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