ai powered

Image recognition
& visual search API
for your business

Video introduction Check it out — it’s easy

Visual AI That Helps in Many Areas

Ximilar Basics in 2 minutes

Find the Ideal Solution For Your Business

Object Detection

Train your custom automatic object detection able to spot, mark & count objects of different types.

Image Classification

Train your own AI to categorize, tag and organize images automatically. Combine it with other services & use it via API or deploy offline.

Annotate

Advanced image annotation tool for detailed and quick annotation of large collections in a team. Draw boxes & polygons, and get automatic annotating suggestions. Work in a team and track progress on the jobs.

Fashion Tagging

Auto-tagging of fashion items, such as footwear, accessories, jewellery, clothing and underwear. Extract all attributes from the picture and recommend the best products.

Flows

Chain & combine categorization, tagging, object detection, image similarity tasks, and ready-to-use services. Re-train, add or remove any part anytime.

Visual Search Solutions

Bring relevant and personalized product recommendations with true visual & similarity search. Match identical photos, eliminate duplicates & enrich galleries.

Stock Photo Search

All-in-one solutions for image search powered by AI. Text-to-image search based on language processing, reverse image search and similar image recommendations based on true visual search.

Find your Visual AI solution See them all

Trusted by companies worldwide

The Ximilar technology has been working reliably for many years on our collection of 100M+ creative photos.

Pavel MackůCEO of Profimedia

Way better similar results in our 10 million stock images. Customers can find visual similars by uploading a photo. The integration was fast. We recommend it!

Amos Struckco-founder at StockPhotos

Babyndex uses Annotate, which is excellent, and Image Recognition. This is the service that I could easily set up myself. Ximilar has helped in improving accuracy and from that day on, it works.

Zajzon Bodóco-founder at Babyndex

Developers First

We take care of the complexity behind and wrap it in a few lines of code.

full documentation

curl -H "Content-Type: application/json" -H "authorization: Token __API_TOKEN__" https://api.ximilar.com/recognition/v2/classify -d '{"task_id": "__TASK_ID__", "version": 2, "records": [ {"_url": "https://bit.ly/2IymQJv" } ] }'

# pip install ximilar-client
from ximilar.client import RecognitionClient

client = RecognitionClient(token="__API_TOKEN__")
task, status = client.get_task(task_id="__ID_TASK__")

# you can send image in _file, _url or _base64 format
# the _file format is intenally converted to _base64 as rgb image
result = task.classify([{"_url": "__URL_PATH_TO_IMG__"}, {"_file", "__LOCAL_FILE_PATH__"}, {"_base64": "__BASE64_DATA__"}])

import requests 
import json 
import base64 
 
endpoint = 'https://api.ximilar.com/recognition/v2/classify/' 
headers = { 
    'Authorization': "Token __API_TOKEN__", 
    'Content-Type': 'application/json' 
} 
with open(__IMAGE_PATH__, "rb") as image_file: 
    encoded_string = base64.b64encode(image_file.read()).decode('utf-8') 
 
data = { 
    'task_id': __TASK_ID__, 
    'records': [ {'_url': __IMAGE_URL__ }, {"_base64": encoded_string } ] 
} 
 
response = requests.post(endpoint, headers=headers, data=json.dumps(data))

$curl_handle = curl_init("https://api.ximilar.com/recognition/v2/classify");

$data = [
    'task_id' => __TASK_ID__,
    'records' => [
        [ '_url' => 'https://bit.ly/2IymQJv' ],
        [ '_base64' => base64_encode(file_get_contents(__PATH_TO_IMAGE__)) ]
    ]
];

curl_setopt($curl_handle, CURLOPT_CUSTOMREQUEST, "POST");
curl_setopt($curl_handle, CURLOPT_POSTFIELDS, json_encode($data));
curl_setopt($curl_handle, CURLOPT_RETURNTRANSFER, true);
curl_setopt($curl_handle, CURLOPT_FAILONERROR, true);
curl_setopt($curl_handle, CURLOPT_HTTPHEADER, array(
        "Content-Type: application/json",
        "Authorization: Token __API_TOKEN__",
        "cache-control: no-cache",)
);

$response = curl_exec($curl_handle);
$error_msg = curl_error($curl_handle);

if ($error_msg) { // Handle error
    print_r($error_msg);
} else { // Handle response
    print_r($response);
}
curl_close ($curl_handle);