Detect API - Programmatic Object and Subject Detection

API Endpoint Access URL

https://api.pixlab.io/detect

Description

The Detect API endpoint uses advanced machine learning models to detect, classify, and return bounding-box coordinates for objects inside your images. Developers can use these coordinates to crop subjects, moderate content, or build automated media cataloguing pipelines.

HTTP Methods

GET, POST

HTTP Parameters

Required

Fields	Type	Description
`img`	URL	URL to the input image to gain insight from including objects location, and their potential coordinates in the event of a `GET` request. If you want to upload an image directly from your app, then submit a `multipart/form-data` POST request instead. Refer to the POST Request Data section below.
`key`	String	Your PixLab API Key ↗. You can also embed your key in the `WWW-Authenticate:` HTTP header and omit this parameter if you want to.

POST Request Body

This section details the requirements for using a POST request instead of a simple GET request.

Allowed Content-Types:

multipart/form-data
application/json

Use multipart/form-data to directly upload your image from you app (Refer to The PixLab Github Repository↗ for a working example). If you're using JSON, the media file must already be uploaded. Consider calling store to upload an image before invoking this endpoint.

HTTP Response

application/json

This endpoint always returns a JSON object containing image description data. Response fields include:

Fields	Type	Description
`status`	Integer	HTTP 200 indicates success. Any other code indicates failure.
`objects`	Array \| List	An array or list of detected objects, with their name, description, and potential coordinates on the input image or video frame. This data is crucial for further processing and analysis.
`error`	String	Error description when `status` != 200.

Code Samples


import requests
import json

# Gain image insights using the DETECT API endpoint. Identify and locate objects within images
# pinpointing their coordinates or specific regions.

# Target Image: Change to any link or switch to POST if you want to upload your image directly, refer to the REST API code samples for more info.
img = 'https://pixlab.io/assets/images/nature31.jpg' 

key = 'PIXLAB_API_KEY' # Get your API key from https://console.pixlab.io/

req = requests.get('https://api.pixlab.io/detect',params={'img':img,'key':key})
reply = req.json()
if reply['status'] != 200:
	print (reply['error'])
else:
    total = len(reply['objects']) # Total objects detected
    print(f"Total Objects Detected: {total}")
    for object in reply['objects']:
		  print(f"Object: {object['name']} - Coordinates: {object['bbox']}")


// Gain image insights using the DETECT API endpoint. Identify and locate objects within images
// pinpointing their coordinates or specific regions.
// https://pixlab.io/endpoints/detect for more info.

// Target Image: Change to any link or switch to POST if you want to upload your image directly, refer to the REST API code samples for more info.
const img = 'https://pixlab.io/assets/images/nature31.jpg';
// Your PixLab key
const key = 'PIXLAB_API_KEY';

fetch(`https://api.pixlab.io/detect?img=${encodeURIComponent(img)}&key=${encodeURIComponent(key)}`)
    .then(response => response.json())
    .then(reply => {
        if (reply.status !== 200) {
            console.log(reply.error);
        } else {
            const total = reply.objects.length; // Total Objects
            console.log(`Total Detected Objects: ${total}`);
            reply.objects.forEach(object => {
                console.log(`Object: ${object.name} - Coordinates: ${object.bbox}`);
            });
        }
    })
    .catch(error => console.error('Error:', error));

<?php
# Gain image insights using the DETECT API endpoint. Identify and locate objects within images
# pinpointing their coordinates or specific regions.

// Target Image: Change to any link or switch to POST if you want to upload your image directly, refer to the REST API code samples for more info.
$img = 'https://pixlab.io/assets/images/nature31.jpg';
$key = 'PIXLAB_API_KEY';

$ch = curl_init();
curl_setopt($ch, CURLOPT_URL, 'https://api.pixlab.io/detect?img=' . urlencode($img) . '&key=' . urlencode($key));
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
$response = curl_exec($ch);
curl_close($ch);

$reply = json_decode($response, true);

if ($reply['status'] != 200) {
    echo $reply['error'];
} else {
    $total = count($reply['objects']); # Total number of detected objects
    echo "Total Objects: " . $total . "\n";
    foreach ($reply['objects'] as $object) {
        echo "Object: " . $object['object'] . " - Coordinates: " . $object['bbox'] . "\n";
    }
}


require 'net/http'
require 'uri'
require 'json'

# Gain image insights using the DETECT API endpoint. Identify and locate objects within images
# pinpointing their coordinates or specific regions.
# https://pixlab.io/endpoints/detect for more info.

# Target Image: Change to any link or switch to POST if you want to upload your image directly, refer to the REST API code samples for more info.
img = 'https://pixlab.io/assets/images/nature31.jpg'
# Your PixLab key
key = 'PIXLAB_API_KEY'

uri = URI.parse('https://api.pixlab.io/detect')
params = { img: img, key: key }
uri.query = URI.encode_www_form(params)

response = Net::HTTP.get_response(uri)
reply = JSON.parse(response.body)

if reply['status'] != 200
  puts reply['error']
else
  total = reply['objects'].length
  puts "Total Detected Objects: #{total}"
  reply['objects'].each do |obj|
    puts "Object: #{obj['name']} - Coordinates: #{obj['bbox']}"
  end
end

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objectimg, nsfw, img-embed, docscan, chat, text-embed, crop, mogrify, facelookup ↗, faceverify ↗, query

Detect API Endpoint