Identify the color of a skirt using AI

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

the color of a skirt identifier

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Get started

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

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

How this classifier works

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

This pretrained image model uses a Nyckel-created dataset and has 26 labels, including Beige, Black, Blue, Brown, Burgundy, Coral, Cyan, Gray, Green and Ivory.

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

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

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Need to identify the color of a skirt at scale?

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



  • Fashion Retail Inventory Management: The 'color of a skirt' identifier can be integrated into retail management systems to automate inventory categorization. This function can help retailers quickly identify and organize skirts by color, enhancing the efficiency of stock management and online listings.

  • Personalized Shopping Experience: E-commerce platforms can use this identifier to recommend skirts based on customer preferences and browsing history. By analyzing color trends and customer choices, the system can suggest similar items in the desired color, leading to a more tailored shopping experience.

  • Trend Analysis for Designers: Fashion designers can utilize the color identification function to analyze market trends and color popularity over time. By examining the data on skirt colors, designers can make informed decisions on color selections for their upcoming collections.

  • Social Media Marketing Optimization: Brands can leverage this technology to analyze user-generated content on social media platforms, identifying the most popular skirt colors among their audience. This insight can help in optimizing marketing strategies and targeted advertising campaigns.

  • Ethical Fashion Initiatives: Organizations focused on sustainable fashion can use this identifier to track and promote color diversity within ethical collections. By identifying the colors of skirts made from sustainable materials, these organizations can create campaigns that highlight eco-friendly fashion choices.

  • Virtual Try-Ons and Augmented Reality: Retailers offering virtual try-on features can integrate the color recognition function to enhance user interaction. The identifier can allow customers to see how different skirt colors look on them, driving engagement and reducing return rates.

  • Color-based Analytics for Customer Feedback: Businesses can analyze customer reviews and feedback based on skirt color preferences. This function enables them to identify potential issues or popular features related to specific colors, streamlining product development and customer satisfaction efforts.

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