Identify tile pattern type using AI

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

tile pattern type identifier

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    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("tile-pattern-type-identifier", "your_image_url", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/tile-pattern-type-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/tile-pattern-type-identifier/invoke
                

How this classifier works

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

This pretrained image model uses a Nyckel-created dataset and has 45 labels, including Abstract, Arabesque, Art Deco, Asian, Baroque, Bohemian, Brick, Celtic, Checkerboard and Classic.

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

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

Related Classifiers

Need to identify tile pattern type at scale?

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



  • Interior Design Trend Analysis: The false image classification function can be utilized to identify and analyze tile patterns in various interior design projects. By categorizing different styles, designers can better understand trending patterns and incorporate them into their designs, ensuring they stay ahead of consumer preferences.

  • Quality Control in Tile Manufacturing: Tile manufacturers can implement this function as part of their quality control process. By automatically classifying tile patterns, it can help in detecting discrepancies or defects in production patterns, leading to higher quality products and reduced waste.

  • Home Renovation Project Planning: Home renovation firms can use the tile pattern identifier to suggest tile options based on the existing decor of a space. By identifying current patterns, companies can recommend complementary designs to homeowners, enhancing the aesthetic appeal of their renovations.

  • Online Tile Retail Analytics: E-commerce platforms selling tiles can leverage this function to analyze customer-generated images on social media and review sites. By identifying popular tile patterns in user photos, retailers can adjust their inventory and marketing strategies to align with consumer interests.

  • Augmented Reality Tile Visualization: Developers of augmented reality applications for home improvement can use the false image classification function to recognize floor or wall tiles in a user’s home. This allows the app to suggest new tile options based on existing styles, enriching the user experience and improving decision-making.

  • Smart Home Integration for Tile Maintenance: Smart home systems can incorporate the identifier to monitor tile patterns for wear and tear. By recognizing specific tile styles, maintenance alerts can be provided to homeowners, ensuring timely care and prolonging the lifespan of their flooring.

  • Cultural Heritage Preservation: Museums and cultural institutions can utilize the tile pattern identifier to categorize and document historical tile designs in their collections. This function can assist researchers and curators in preserving cultural heritage and enhancing educational exhibits that showcase the evolution of tile patterns over time.

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