The Fashion API conducts a comprehensive analysis of images, generating a curated inventory of potential clothing articles and accessories that may be discerned within the visual content. This technology facilitates the identification of various fashion elements, contributing to informed assessments and enriched insights within the realm of style and attire.

Acquiring the key through Rapid API

Step 1. Logging in to Rapid API

To begin, navigate to the login page of Rapid API at https://rapidapi.com/auth/login and enter your account credentials.

If you are a first-time user of Rapid API, it will prompt you to provide some information about yourself.

Step 2. Subscribing to Fashion API

Next, visit the Fashion API pricing page at https://rapidapi.com/api4ai-api4ai-default/api/fashion4/pricing. Choose the subscription plan that best suits your requirements.

Once you have selected a plan, click on the subscribe button. You will receive a confirmation message stating “Subscription Created Successfully.”

Step 3. Retrieving the API Key from the Dashboard

Access your Rapid API dashboard by either clicking on “Manage And View Usage” under your subscribed plan or visiting https://rapidapi.com/developer/dashboard.

Expand one of your applications within the dashboard and click on the “Authorization” tab.

You will find a list of authorization keys. Simply copy one of them, and voilà! You now have your Face Detection API key.

Step 4. Test API

To evaluate the functionality of the API, execute the provided Python code snippet.
It is important to remember to replace API_KEY with your actual API key before running the code.

import sys

import requests
from requests.adapters import Retry, HTTPAdapter

API_URL = 'https://fashion4.p.rapidapi.com'
API_KEY = 'YOUR_RAPIDAPI_KEY'  # Place your API key here

if __name__ == '__main__':
    # We strongly recommend you use exponential backoff.
    error_statuses = (408, 409, 429, 500, 502, 503, 504)
    s = requests.Session()
    retries = Retry(backoff_factor=1.5, status_forcelist=error_statuses)

    s.mount('https://', HTTPAdapter(max_retries=retries))

    url = f'{API_URL}/v1/results'
    with open('img.jpg', 'rb') as f:
        api_res = s.post(url, headers={'X-RapidAPI-Key': API_KEY},
                         files={'image': f}, timeout=20)
    api_res_json = api_res.json()

    # Handle processing failure.
    if (api_res.status_code != 200 or
            api_res_json['results'][0]['status']['code'] == 'failure'):
        print('Image processing failed.')
        sys.exit(1)

    top5 = sorted(
        api_res_json['results'][0]['entities'][0]['classes'].items(),
        key=lambda i: -i[1]
    )[:5]

    print(f'? Top 5 classes:\n{top5}\n')

More code examples

Our repository with code example have more example for different languages.
Visit it at https://gitlab.com/api4ai/examples/fashion or proceed to code examples using direct links:

• Bash
• C#
• JavaScript
• NodeJS
• PHP
• Python
• Swift

Conclusion

The Fashion API, as an advanced apparel recognition algorithm, caters to a diverse spectrum of businesses, spanning across both social and corporate domains. This algorithm expeditiously and proficiently procures and furnishes comprehensive attire and accessory data, encapsulated within concise responses for each individual image. By seamlessly integrating this technology, enterprises can attain valuable insights into fashion preferences, thereby facilitating strategic decision-making and enhancing customer engagement across various sectors.