bfirsh/resnet – Run with an API on Replicate

bfirsh / resnet

Classifies images with ResNet-50

Cold

Public
183 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=bfirsh/resnet

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

const output = await replicate.run(
  "bfirsh/resnet:95e39377647de76447883edf86f5a3e17fd5fc6e08c58e68e9d725f9d1af1930",
  {
    input: {
      image: "https://replicate.delivery/mgxm/c2739d5f-9932-4823-8cf7-8e55cb912ab5/cat.jpg"
    }
  }
);

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

output = replicate.run(
    "bfirsh/resnet:95e39377647de76447883edf86f5a3e17fd5fc6e08c58e68e9d725f9d1af1930",
    input={
        "image": "https://replicate.delivery/mgxm/c2739d5f-9932-4823-8cf7-8e55cb912ab5/cat.jpg"
    }
)
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/resnet 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/resnet:95e39377647de76447883edf86f5a3e17fd5fc6e08c58e68e9d725f9d1af1930",
    "input": {
      "image": "https://replicate.delivery/mgxm/c2739d5f-9932-4823-8cf7-8e55cb912ab5/cat.jpg"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

[ [ "n02123597", "Siamese_cat", 0.8829365372657776 ], [ "n02123394", "Persian_cat", 0.09810517728328705 ], [ "n02123045", "tabby", 0.005758064799010754 ] ]

Generated in

5.6 seconds

Tweak it Report

Run time and cost

This model costs approximately $0.0021 to run on Replicate, or 476 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 22 seconds. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.