Inference

Training

See the documentation page for Roboflow's one-click training solution.

After training, your model will post to an endpoint for inference.

Inference

There are multiple ways to use your trained model for inference, all of which are accessible with quick links in the web UI after your model has finished training:

• You can POST a base64-encoded image to your endpoint with curl or pass a URL via the query string.

• We have a sample web app you can use as an example for building your endpoint into a custom application.

• We have sample code for making requests to your inference endpoint in a variety of languages.

The Example Web App

The easiest way to familiarize yourself with the inference endpoint is to visit the Example Web App. To use the Web App, simply input your model and access_token. These will be pre-filled for you after training completes if you click through via the web API.

Then select an image via Choose File. After you have chosen the settings you want, click Run Inference.

On the left side of the screen, you will see example JavaScript code for posting a base64-encoded image to the inference endpoint. Within the form portion of the Web App, you can experiment with changing different API parameters when posting to the API.

Obtaining Your Model Endpoint

To use the inference API, you will need your model endpoint and your API key. Your API key can be retrieved from your account page. Your model endpoint is a unique string composed of your individual or team identifier, the model ID, and the version number. The easiest way to retrieve it is via the web UI by clicking the "curl command" link:

{
    "predictions": [{
        "x": 234.0,
        "y": 363.5,
        "width": 160,
        "height": 197,
        "class": "hand",
        "confidence": 0.943
    }, {
        "x": 504.5,
        "y": 363.0,
        "width": 215,
        "height": 172,
        "class": "hand",
        "confidence": 0.917
    }, {
        "x": 1112.5,
        "y": 691.0,
        "width": 139,
        "height": 52,
        "class": "hand",
        "confidence": 0.87
    }, {
        "x": 78.5,
        "y": 700.0,
        "width": 139,
        "height": 34,
        "class": "hand",
        "confidence": 0.404
    }]
}

{
    "Message": "User is not authorized to access this resource"
}

Code Snippets

For your convenience, we've provided code snippets for calling this endpoint in various programming languages. If you need help integrating the inference API into your project don't hesitate to reach out.

All examples upload to an example dataset with a model-endpoint of xx-your-model--1. You can easily find your dataset's identifier by looking at the curl command shown in the Roboflow web interface after your model has finished training.

base64 YOUR_IMAGE.jpg | curl -d @- \
"https://infer.roboflow.com/xx-your-model--1?access_token=YOUR_KEY"

curl -X POST "https://infer.roboflow.com/xx-your-model--1?\
access_token=YOUR_KEY&\
image=https%3A%2F%2Fi.imgur.com%2FPEEvqPN.png"

import requests
import base64
import io
from PIL import Image
​
# Load Image with PIL
image = Image.open("YOUR_IMAGE.jpg").convert("RGB")
​
# Convert to JPEG Buffer
buffered = io.BytesIO()
image.save(buffered, quality=90, format="JPEG")
​
# Base 64 Encode
img_str = base64.b64encode(buffered.getvalue())
img_str = img_str.decode("ascii")
​
# Construct the URL
upload_url = "".join([
    "https://infer.roboflow.com/xx-your-model--1",
    "?access_token=YOUR_KEY",
    "&name=YOUR_IMAGE.jpg"
])
​
# POST to the API
r = requests.post(upload_url, data=img_str, headers={
    "Content-Type": "application/x-www-form-urlencoded"
})
​
# Output result
print(r.json())

import requests
import urllib.parse
​
# Construct the URL
img_url = "https://i.imgur.com/PEEvqPN.png"
upload_url = "".join([
    "https://infer.roboflow.com/xx-your-model--1",
    "?access_token=YOUR_KEY",
    "&image=" + urllib.parse.quote_plus(img_url)
])
​
# POST to the API
r = requests.post(upload_url)
​
# Output result
print(r.json())

const axios = require("axios");
const fs = require("fs");
​
const image = fs.readFileSync("YOUR_IMAGE.jpg", {
    encoding: "base64"
});
​
axios({
    method: "POST",
    url: "https://infer.roboflow.com/xx-your-model--1",
    params: {
        access_token: "YOUR_KEY"
    },
    data: image,
    headers: {
        "Content-Type": "application/x-www-form-urlencoded"
    }
})
.then(function(response) {
    console.log(response.data);
})
.catch(function(error) {
    console.log(error.message);
});

const axios = require("axios");
​
axios({
    method: "POST",
    url: "https://infer.roboflow.com/xx-your-model--1",
    params: {
        access_token: "YOUR_KEY",
        image: "https://i.imgur.com/PEEvqPN.png"
    }
})
.then(function(response) {
    console.log(response.data);
})
.catch(function(error) {
    console.log(error.message);
});

​

​