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AI Virtual Outfit Try On API

A clothing visualization API provides users with an immersive online shopping experience. Integrate a virtual dressing room into your app or website where users can picture how clothing items would look on them.

uploaded photos of dresses being virtually tried on by a model using ai outfit try on for realistic previews.

Catering to various startups and businesses

If you have an online clothing store, then easily plug in this API so your users can see how your clothes will look on them.

Easy Integration with Popular Frameworks
Easily integrate our API with CSS, React, Tailwind, JS, and Python for versatile and powerful applications.
import requests

url = 'https://api.lightxeditor.com/external/api/v2/aivirtualtryon'
headers = {
'Content-Type': 'application/json',
'x-api-key': '<Insert your API Key>'  # Replace with your actual API key
}

data = {
"imageUrl": "https://example.com/your-image.jpg",  # Replace with the URL of your input image
"styleImageUrl": "https://example.com/your-style-image.jpg"  # Replace with the URL of your input style image
}

response = requests.post(url, headers=headers, json=data)

# Check if the request was successful
if response.status_code == 200:
print("Request was successful!")
print(response.json())
else:
print(f"Request failed with status code: {response.status_code}")
print(response.text)
const fetch = require('node-fetch');  // Only needed if you are using Node.js

const url = 'https://api.lightxeditor.com/external/api/v2/aivirtualtryon';
const apiKey = '<Insert your API Key>';  // Replace with your actual API key

const data = {
"imageUrl": "https://example.com/your-image.jpg",  // Replace with the URL of your input image
"styleImageUrl": "https://example.com/your-style-image.jpg"  // Replace with the URL of your input style image
};

const options = {
method: 'POST',
headers: {
    'Content-Type': 'application/json',
    'x-api-key': apiKey
},
body: JSON.stringify(data)
};

fetch(url, options)
.then(response => {
    if (!response.ok) {
        throw new Error(`Request failed with status code ${response.status}`);
    }
    return response.json();
})
.then(data => {
    console.log('Request was successful!');
    console.log(data);
})
.catch(error => {
    console.error('Error:', error);
});

}
import Foundation

// Define the URL and API key
let url = URL(string: "https://api.lightxeditor.com/external/api/v2/aivirtualtryon")!
let apiKey = "<Insert your API Key>"  // Replace with your actual API key

// Define the request body
let requestBody: [String: Any] = [
"imageUrl": "https://example.com/your-image.jpg",  // Replace with the URL of your input image
"styleImageUrl": "https://example.com/your-style-image.jpg"  // Replace with the URL of your input style image
]

// Convert request body to JSON data
let jsonData = try! JSONSerialization.data(withJSONObject: requestBody, options: [])

// Create the URLRequest object
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.setValue(apiKey, forHTTPHeaderField: "x-api-key")
request.httpBody = jsonData

// Create the URLSession data task
let task = URLSession.shared.dataTask(with: request) { data, response, error in
// Handle the response
if let error = error {
    print("Error: \(error)")
    return
}

guard let httpResponse = response as? HTTPURLResponse, (200...299).contains(httpResponse.statusCode) else {
    print("Unexpected response")
    return
}

if let data = data {
    do {
        // Parse and print the JSON response
        let jsonResponse = try JSONSerialization.jsonObject(with: data, options: [])
        print("Response: \(jsonResponse)")
    } catch {
        print("Error parsing JSON: \(error)")
    }
}
}

// Start the task
task.resume()
import okhttp3.MediaType.Companion.toMediaType
import okhttp3.OkHttpClient
import okhttp3.Request
import okhttp3.RequestBody.Companion.toRequestBody
import okhttp3.Response
import org.json.JSONObject

fun main() {
// Define the URL and API key
val url = "https://api.lightxeditor.com/external/api/v2/aivirtualtryon"
val apiKey = "<Insert your API Key>"  // Replace with your actual API key

// Define the request body
val requestBody = JSONObject().apply {
    put("imageUrl", "https://example.com/your-image.jpg")  // Replace with the URL of your input image
    put("styleImageUrl", "https://example.com/your-style-image.jpg")  // Replace with the URL of your input style image
}.toString()

// Create OkHttpClient
val client = OkHttpClient()

// Create the request
val request = Request.Builder()
    .url(url)
    .post(requestBody.toRequestBody("application/json; charset=utf-8".toMediaType()))
    .addHeader("x-api-key", apiKey)
    .build()

// Make the request
client.newCall(request).execute().use { response ->
    if (!response.isSuccessful) {
        throw IOException("Unexpected code $response")
    }

    // Print the response
    val responseData = response.body?.string()
    println("Response: $responseData")
}
}
  Method- Post
curl --location 'https://api.lightxeditor.com/external/api/v2/aivirtualtryon' \
--header 'Content-Type: application/json' \
--header 'x-api-key: <Insert your API Key>' \

--data '{
"imageUrl": "https://example.com/your-image.jpg",  // Replace with the URL of your input image
"styleImageUrl": "https://example.com/your-style-image.jpg"  // Replace with the URL of your input style image
}'

Choose your plan

Explore a variety of pricing plans designed to meet your unique requirements. Find the perfect fit and start today.

Supports on-person clothing, flatlays, and ghost mannequins

This API features a two-way input system: upload a photo of a person and a photo of an outfit item (can be a mockup, a photo of someone wearing it, a mannequin, or a flat lay). In mere seconds, the tool will give a final output.

lightX api supporting flat lay, on-person, and model photos to apply clothes on users' images with realistic fitting.

Improve conversions, reduce return rates

This API will significantly streamline your workflow. You no longer need to organize countless photoshoots for every clothing item on models. Simply upload your product photos and a model photo (in any angle, pose, or body size), and the tool will generate images of the model wearing your outfits, saving you both time and money. You can then list these images, which allow the customers to virtually try those clothes on themselves.

users trying on clothes virtually on a clothing website leading to reduced return rates and increased customer satisfaction.

Realistic generations — Not just overlaid

The tool doesn’t just superimpose the outfit onto a person — it uses generative AI to recreate any body parts that should be visible in a certain outfit design, making it more realistic and practical.

comparison of LightX vs other virtual try-on tools: LightX offers exposed body parts while others simply layer outfits on existing photos.

Pricing plans that fit your requirements

LightX’s AI Virtual Try-On API is one of the most affordable that you might find in the market.
You benefit from flexible credit options tailored to your specific business needs and only pay for what you use—nothing more. Choose between a subscription with auto-renewal or purchasing just the credits you need.
Visit our pricing page for more details.

api pricing plans available for both small-scale users and large-volume commercial use with competitive rates.

Prioritizing data privacy above anything

User privacy is of our utmost importance! That’s why we do not store any data or use it for training purposes. All user inputs are automatically deleted after 24 hours, and the generated outputs are never saved.

privacy and encryption features included in the ai outfit try on api to protect user data and maintain secure experiences.

Start with Free Credits

Get started with LightX APIs today! Receive 25 free credits instantly on API signup – no credit card required

Frequently Asked Questions

All you have to do is generate the API key, follow the API Documentation, and integrate.

Still Unsure? Allow Us To Assist You!

Write to us and we'd love to understand your requirements

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