hyuse202/sef – Run with an API on Replicate

hyuse202 / sef

Chest X ray

Cold

Public
2.6K runs
CPU
GitHub

Run with an API

Playground API Examples README Versions

Input

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

npx create-replicate --model=hyuse202/sef

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 hyuse202/sef using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "hyuse202/sef:c03f78a9e7220d772d2d5729c4b3e9ce83b381491660a2a4468eb5044bb147a7",
  {
    input: {
      image: "https://replicate.delivery/pbxt/K0aFIm4aMJ95I2bWny4koiq4H7XHwvLGQbDmpRCIZKWbV9tJ/01eb30a37b6f5fed8a8d3ab2d1c0a7d6.png"
    }
  }
);

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 hyuse202/sef using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "hyuse202/sef:c03f78a9e7220d772d2d5729c4b3e9ce83b381491660a2a4468eb5044bb147a7",
    input={
        "image": "https://replicate.delivery/pbxt/K0aFIm4aMJ95I2bWny4koiq4H7XHwvLGQbDmpRCIZKWbV9tJ/01eb30a37b6f5fed8a8d3ab2d1c0a7d6.png"
    }
)
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 hyuse202/sef 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": "hyuse202/sef:c03f78a9e7220d772d2d5729c4b3e9ce83b381491660a2a4468eb5044bb147a7",
    "input": {
      "image": "https://replicate.delivery/pbxt/K0aFIm4aMJ95I2bWny4koiq4H7XHwvLGQbDmpRCIZKWbV9tJ/01eb30a37b6f5fed8a8d3ab2d1c0a7d6.png"
    }
  }' \
  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/hyuse202/sef@sha256:c03f78a9e7220d772d2d5729c4b3e9ce83b381491660a2a4468eb5044bb147a7 \
  -i 'image="https://replicate.delivery/pbxt/K0aFIm4aMJ95I2bWny4koiq4H7XHwvLGQbDmpRCIZKWbV9tJ/01eb30a37b6f5fed8a8d3ab2d1c0a7d6.png"'

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/hyuse202/sef@sha256:c03f78a9e7220d772d2d5729c4b3e9ce83b381491660a2a4468eb5044bb147a7
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "image": "https://replicate.delivery/pbxt/K0aFIm4aMJ95I2bWny4koiq4H7XHwvLGQbDmpRCIZKWbV9tJ/01eb30a37b6f5fed8a8d3ab2d1c0a7d6.png"
    }
  }' \
  http://localhost:5000/predictions

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

Output

{"xmin":{"0":333.8423156738,"1":177.0129852295,"2":436.6292114258,"3":445.0075073242,"4":656.2774047852,"5":362.7706604004},"ymin":{"0":514.2503662109,"1":205.7272491455,"2":218.7043914795,"3":220.0065917969,"4":108.9106292725,"5":102.462600708},"xmax":{"0":912.68359375,"1":333.5083618164,"2":692.5001220703,"3":695.9617919922,"4":677.8083496094,"5":467.6805114746},"ymax":{"0":815.1019287109,"1":338.6361694336,"2":446.4266662598,"3":442.3133239746,"4":131.563583374,"5":352.4076538086},"confidence":{"0":0.6015235186,"1":0.4484250247,"2":0.4443016648,"3":0.3965222239,"4":0.3159525096,"5":0.2883091569},"class":{"0":3,"1":2,"2":0,"3":2,"4":8,"5":9},"name":{"0":"Cardiomegaly","1":"Calcification","2":"Aortic enlargement","3":"Calcification","4":"Nodule\/Mass","5":"Other lesion"}}

Generated in

1.1 seconds

Tweak it Report

This output was created using a different version of the model, hyuse202/sef:72ac5e55.

Run time and cost

This model costs approximately $0.00011 to run on Replicate, or 9090 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 CPU hardware. Predictions typically complete within 2 seconds.

Readme

This model doesn't have a readme.