The Face Detection API is a powerful tool that accurately identifies human faces in images. It not only detects the location of the face within the image but also provides a “confidence” percentage indicating the reliability of the detected face.

Furthermore, this API goes beyond simple detection by automatically identifying five key points on a human face: the left and right eyes, nose, and left and right lip corners. This feature enables precise facial analysis and opens up possibilities for various applications such as facial recognition and emotion detection.

Additionally, the API utilizes advanced embedding techniques to determine whether faces from different images belong to the same individual. By calculating unique embeddings, the algorithm can establish connections between faces, facilitating tasks like face matching and identity verification.

With its robust face detection, key point analysis, and face matching capabilities, the Face Detection API empowers developers to create innovative applications in areas such as biometrics, security systems, and personalized user experiences.

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 Face Detection API

Next, visit the Face Detection API pricing page at https://rapidapi.com/api4ai-api4ai-default/api/face-detection14/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://face-detection14.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)

    faces_count = len(
        api_res_json['results'][0]['entities'][0]['objects'])

    print(f'? Faces detected: {faces_count}')

More code examples

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

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

Conclusion

The Face Detection API has a wide range of applications, spanning from customer service to basic and advanced security measures. With its face recognition capabilities, this API serves as an invaluable solution in numerous human-centric industries, offering a multitude of purposes and benefits.