Identify the color of an earring using AI

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

the color of an earring identifier

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    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("the-color-of-an-earring", "your_image_url", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/the-color-of-an-earring/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/the-color-of-an-earring/invoke
                

How this classifier works

To start, upload your image. Our AI tool will then predict the color of an earring.

This pretrained image model uses a Nyckel-created dataset and has 21 labels, including Beige, Black, Blue, Brown, Crimson, Gold, Gray, Green, Lavender and Multi-Color.

We'll also show a confidence score (the higher the number, the more confident the AI model is around the color of an earring).

Whether you're just curious or building the color of an earring detection into your application, we hope our classifier proves helpful.

Recommended Classifiers

Need to identify the color of an earring at scale?

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



  • E-commerce Product Listings: This function can be integrated into online retail platforms to automatically tag earring listings with their color. By ensuring accurate color classification, customers can refine their searches and find products that match their preferences more easily.

  • Inventory Management: Retailers can utilize this function to streamline their inventory management by categorizing earrings based on color. This helps businesses track stock levels more effectively, ensuring that popular colors are adequately stocked and reducing excess inventory of less desired options.

  • Color Trend Analysis: Fashion brands can use this function to analyze sales data and identify color trends over time. By understanding which earring colors are popular among customers, brands can better tailor their product offerings and marketing strategies to align with consumer preferences.

  • Personalized Marketing: Marketers can leverage this function to create personalized email campaigns targeting customers based on their color preferences. By showing customers earrings in their favored colors, businesses can enhance engagement and drive sales through targeted promotions.

  • Ethical Sourcing Verification: Companies can use this classification function to ensure that the colors of earrings listed online or in stores match the ethical sourcing claims of materials. This adds transparency to product descriptions, reinforcing customer trust in the brand's commitment to ethical practices.

  • Augmented Reality Try-On: Fashion tech companies can integrate this function into AR applications that simulate how different colored earrings look on potential buyers. By providing accurate color classifications, the customer experience is enhanced, leading to increased conversion rates.

  • Customer Feedback Analysis: Businesses can implement this function to automatically categorize customer feedback and reviews based on the color of earrings purchased. This assists in identifying potential issues related to color discrepancies and aids in improving product quality and customer satisfaction.

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