Identify dormitory residents count using AI

Below is a free classifier to identify dormitory residents count. Just upload your image, and our AI will predict the number of residents in each dormitory. - in just seconds.

dormitory residents count identifier

API Access


import nyckel

credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("dormitory-residents-count", "your_image_url", credentials)
            

fetch('https://www.nyckel.com/v1/functions/dormitory-residents-count/invoke', {
    method: 'POST',
    headers: {
        'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
        'Content-Type': 'application/json',
    },
    body: JSON.stringify(
        {"data": "your_image_url"}
    )
})
.then(response => response.json())
.then(data => console.log(data));
            

curl -X POST \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer YOUR_BEARER_TOKEN" \
    -d '{"data": "your_image_url"}' \
    https://www.nyckel.com/v1/functions/dormitory-residents-count/invoke
            

How this classifier works

To start, upload your image. Our AI tool will then predict the number of residents in each dormitory..

This pretrained image model uses a Nyckel-created dataset and has 13 labels, including 1-5, 1000+, 101-200, 11-20, 201-300, 21-30, 301-400, 31-40, 401-500 and 41-50.

We'll also show a confidence score (the higher the number, the more confident the AI model is around the number of residents in each dormitory.).

Whether you're just curious or building dormitory residents count detection into your application, we hope our classifier proves helpful.

Recommended Classifiers

Need to identify dormitory residents count at scale?

Get API or Zapier access to this classifier for free. It's perfect for:



  • Occupancy Management: This function can be utilized by university housing departments to accurately count the number of residents in dormitories. By identifying false images, the system can ensure that occupancy data is reliable, aiding in resource allocation and facility management.

  • Safety Compliance: Dormitory managers can implement this function to verify that the number of residents aligns with safety regulations and fire codes. By detecting inaccuracies caused by false images, they can maintain compliance and ensure student safety.

  • Tenant Verification: Property management companies can use this function to authenticate the identities and presence of dormitory residents through image analysis. This can help prevent unauthorized tenants from accessing facilities, enhancing security and accountability.

  • Maintenance Requests: Maintenance teams can leverage this technology to focus their efforts on dormitories with higher occupancy rates. By ensuring accurate resident counts, they can prioritize service requests, improving overall resident satisfaction.

  • Event Planning and Resource Allocation: Student organizations can access accurate resident counts for event planning purposes. Knowing the exact number of dormitory occupants will help streamline resource allocation for campus-wide events and activities.

  • Health and Safety Monitoring: Health officials can use this function to monitor dormitory populations during health crises, such as pandemics. By detecting and managing false images, authorities can implement targeted health interventions based on accurate resident numbers.

  • Data Analytics and Insights: Schools can analyze the collected data on dormitory occupation trends over time. By avoiding inaccuracies from false images, administrators can make informed decisions regarding housing policy changes, renovations, and future expansion needs.

Want this classifier for your business?

In just minutes you can automate a manual process or validate your proof-of-concept.

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