Identify count of jump ropes using AI

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

API Access


import nyckel

credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("count-of-jump-ropes", "your_image_url", credentials)


fetch('https://www.nyckel.com/v1/functions/count-of-jump-ropes/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-jump-ropes/invoke

How this classifier works

To start, upload your image. Our AI tool will then predict the count of jump ropes in the image.

This pretrained image model uses a Nyckel-created dataset and has 52 labels, including 0, 1, 10, 100+, 11, 12, 13, 14, 15 and 16.

We'll also show a confidence score (the higher the number, the more confident the AI model is around the count of jump ropes in the image).

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

Need to identify count of jump ropes at scale?

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

Inventory Management: This function can be integrated into retail systems to accurately count the number of jump ropes available in stock. By automating this process, businesses can reduce human error, streamline their inventory audits, and optimize restocking processes based on real-time data.

Market Analytics: Sports and fitness companies can use this identifier to analyze consumer trends by monitoring sales and stock levels of jump ropes across various retail outlets. This data can provide insights into peak buying periods, helping businesses tailor their marketing strategies accordingly.

Supply Chain Optimization: Manufacturers can employ this image classification function to monitor jump rope production levels and material usage. By accurately counting jump ropes in production, companies can manage resources more effectively and reduce waste.

Product Quality Control: Implementing this function during the quality assurance process can help manufacturers ensure that every batch of jump ropes meets standards. By counting and inspecting the products in real-time, businesses can quickly address any issues related to production defects.

Customer Feedback Analysis: Retailers can utilize this identifier to gather data on customer returns related to jump ropes. Analyzing the reasons for returns alongside accurate counts can help businesses understand customer dissatisfaction and improve product offerings.

Fitness Trends Reporting: Gyms and fitness studios can use this function to track usage rates of jump ropes in their facilities. Understanding how often equipment is used can inform purchasing decisions and help maintain a well-equipped training environment.

E-commerce Optimization: Online retailers can integrate this image classifier to automate inventory updates for listings of jump ropes. By ensuring the counts are always accurate, businesses can prevent overselling and enhance customer satisfaction through reliable product availability.