The General Classification API furnishes a comprehensive report encompassing the most likely object classes present in the analyzed image. Drawing from an expansive repertoire of over a thousand distinct object categories, this API effectively spans a diverse array of potential image contexts, ranging from household implements to an extensive array of animal species, and beyond. This wide-ranging functionality empowers precise and insightful image classification across an extensive spectrum of subjects.

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 General Classification API

Next, visit the General Classification API pricing page at https://rapidapi.com/api4ai-api4ai-default/api/general-classification1/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 General Classification 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://general-classification1.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)

    # Parse response and print top 5 classes.
    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/general-cls or proceed to code examples using direct links:

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

Conclusion

The General Classification API is a crucial tool for swift image analysis, ideal for projects with high image volumes. It accommodates various objects, from everyday items to diverse animals, and it’s easily customizable to suit specific needs. Its versatility and efficiency make it essential for enhancing processes and gaining valuable insights across different industries.