Identify count of people in the spin class using AI

Below is a free classifier to identify count of people in the spin class. Just upload your image, and our AI will predict the count of people participating in the spin class - in just seconds.

count of people in the spin class identifier

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Get started

    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("count-of-people-in-the-spin-class", "your_image_url", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/count-of-people-in-the-spin-class/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/count-of-people-in-the-spin-class/invoke
                

How this classifier works

To start, upload your image. Our AI tool will then predict the count of people participating in the spin class.

This pretrained image model uses a Nyckel-created dataset and has 18 labels, including 1, 10, 11-15, 16-20, 2, 21-25, 26-30, 3, 31-35 and 36-40.

We'll also show a confidence score (the higher the number, the more confident the AI model is around the count of people participating in the spin class).

Whether you're just curious or building count of people in the spin class detection into your application, we hope our classifier proves helpful.

Recommended Classifiers

Need to identify count of people in the spin class at scale?

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



  • Class Capacity Management: This function can help gym operators monitor attendance in real-time, ensuring that spin classes do not exceed their maximum capacity. By analyzing the data, gyms can optimize scheduling and enhance member experience by balancing class sizes.

  • Demand Forecasting: By tracking attendance trends over time, gym managers can forecast demand for spin classes based on historical data. This insight allows for better decision-making regarding class offerings and instructor allocations, potentially boosting enrollment and revenue.

  • Promotional Campaign Effectiveness: The count of individuals attending spin classes can be integrated with marketing data to evaluate the success of promotional campaigns. By comparing attendance before and after promotions, gyms can assess what strategies work best to attract new members.

  • Member Engagement Analysis: Understanding the number of participants in a spin class can help assess member engagement levels and preferences. This data can inform clubs about which classes to promote or enhance and how to engage members more effectively.

  • Resource Allocation Optimization: Gyms can use attendance information to optimize resource allocation such as bikes, instructors, and facilities. With accurate counts, managers can reduce waste and improve service delivery by adjusting resources according to actual class attendance.

  • Health and Safety Compliance: Accurate counting of attendees in spin classes ensures compliance with health and safety regulations related to occupancy limits. This function can help mitigate risks associated with overcrowding, ensuring a safe environment for participants.

  • Personalization of Class Experience: By analyzing attendance data, gyms can personalize the spin class experience for their members. Insights gleaned from participant counts can inform decisions about class types, formats, or music preferences to cater to the audience better and enhance satisfaction.

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