Identify musical instruments using AI

Below is a free classifier to identify musical instruments. Just upload your image, and our AI will predict what type of musical instrument it is - in just seconds.

musical instruments identifier

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Get started

    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("musical-instruments-identifier", "your_image_url", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/musical-instruments-identifier/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/musical-instruments-identifier/invoke
                

How this classifier works

To start, upload your image. Our AI tool will then predict what type of musical instrument it is.

This pretrained image model uses a Nyckel-created dataset and has 46 labels, including Acoustic Guitar and Electric Guitar.

We'll also show a confidence score (the higher the number, the more confident the AI model is around what type of musical instrument it is).

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

Recommended Classifiers

Need to identify musical instruments at scale?

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



  • Online Music Store Inventory Classification: This function can automatically classify images of musical instruments in an online music store, tagging items like guitars, violins, drums, and keyboards. By streamlining the organization and searchability of products, customers can find their desired instruments more efficiently.

  • Augmented Reality Shopping Experience: Retailers can use this multilabel classification to enhance an augmented reality shopping app where users can visualize different musical instruments in their environment. The app can dynamically categorize and present instruments based on user preferences and recognition of real-life contexts.

  • Educational Resource Development: Educational platforms can implement this function to categorize images used in music theory and instrument training courses. By identifying various instruments visually, students can better engage with content, especially in interactive learning environments.

  • Social Media Content Moderation: Social media platforms could use this image classification to filter and categorize posts featuring musical instruments. By ensuring that content aligns with community standards and can be categorized, the platform can enhance user experience and content discovery.

  • Music Event Promotion: Event organizers can use this function to analyze and categorize promotional images from concerts and festivals featuring specific musical instruments. By understanding the prevalent instruments associated with particular events, organizers can better target their promotional efforts toward relevant audiences.

  • Music Therapy Programs: Music therapy providers can utilize this classification to curate visual materials tailored to specific therapeutic goals. Recognizing and categorizing instruments can help therapists select appropriate instruments to facilitate targeted therapeutic activities for diverse client needs.

  • Art and Culture Exhibitions: Museums and cultural institutions can implement this function for the classification of images in exhibitions showcasing various musical instruments. By providing accurate categorizations, they can enhance visitor engagement and offer interactive digital guides that educate attendees about the instruments on display.

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