Identify park visitors count using AI

Below is a free classifier to identify park visitors count. Just upload your image, and our AI will predict the number of visitors in the park at different times of the day - in just seconds.

park visitors count identifier

API Access


import nyckel

credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("park-visitors-count", "your_image_url", credentials)
            

fetch('https://www.nyckel.com/v1/functions/park-visitors-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/park-visitors-count/invoke
            

How this classifier works

To start, upload your image. Our AI tool will then predict the number of visitors in the park at different times of the day.

This pretrained image model uses a Nyckel-created dataset and has 10 labels, including 1-5, 1001-5000, 101-200, 11-20, 201-500, 21-50, 5000+, 501-1000, 51-100 and 6-10.

We'll also show a confidence score (the higher the number, the more confident the AI model is around the number of visitors in the park at different times of the day).

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

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Need to identify park visitors count at scale?

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



  • Visitor Flow Analysis: This use case involves analyzing the patterns of foot traffic in parks over different times of the year. By classifying real-time images of park visitors, park management can identify peak visiting times and adjust staffing or resources accordingly.

  • Resource Allocation Optimization: By utilizing visitor count data from image classification, parks can optimize their resource allocation. This includes planning for maintenance schedules, ensuring adequate waste disposal, and allocating appropriate space for facilities based on actual visitor usage.

  • Event Planning and Management: Organizers can utilize visitor count insights to plan and manage events more effectively. By analyzing previous visitor data during events, they can determine appropriate scale, safety measures, and marketing strategies for future gatherings.

  • Marketing Campaign Effectiveness: Businesses can deploy targeted marketing campaigns based on park visitor data. By analyzing visitor demographics derived from image classification, marketers can tailor their offerings and promotional efforts to attract park visitors more effectively.

  • Environmental Impact Studies: Conservationists can use the visitor count data to assess environmental impacts. By understanding visitor behaviors and patterns, they can implement strategies to minimize negative effects on park ecosystems and promote sustainable practices.

  • Emergency Response Planning: Accurate visitor counts provide vital information for effective emergency planning in parks. By analyzing high-traffic times and areas, emergency services can proactively strategize evacuation routes and resource deployment during emergencies.

  • Comparative Analysis Across Locations: Parks can benefit from comparing visitor data across multiple locations through image classification. This comparative analysis can help stakeholders identify successful practices and amenities, driving improvements and best practices in park management and visitor experience.

Want this classifier for your business?

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

Get Access