Identify eye makeup intensity using AI

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

eye makeup intensity identifier

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Get started

    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("eye-makeup-intensity", "your_image_url", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/eye-makeup-intensity/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/eye-makeup-intensity/invoke
                

How this classifier works

To start, upload your image. Our AI tool will then predict the intensity of eye makeup applied.

This pretrained image model uses a Nyckel-created dataset and has 10 labels, including Bold, Colorful, Glamorous, Heavy, Intense, Light, Medium, Metallic, None and Subtle.

We'll also show a confidence score (the higher the number, the more confident the AI model is around the intensity of eye makeup applied).

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

Need to identify eye makeup intensity at scale?

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



  • E-commerce Product Recommendations: An online makeup store can utilize the eye makeup intensity identifier to analyze customer-uploaded photos and provide personalized recommendations for products that match or enhance their eye makeup style. This could improve cross-selling opportunities and increase customer satisfaction through tailored shopping experiences.

  • Virtual Try-On Applications: Beauty brands can integrate this function into virtual try-on tools, enabling users to see how different eye makeup intensities look on them before purchasing. This enhances customer engagement and reduces return rates by allowing consumers to make more informed purchase decisions.

  • Social Media Marketing: Influencers and brands can employ the identifier to analyze makeup looks in social media posts, helping to curate content that highlights specific eye makeup intensities. This data can inform future marketing strategies and collaborations, ensuring alignment with current beauty trends.

  • Beauty tutorials and Influencer Engagement: Educational platforms can leverage the identifier to tailor makeup tutorials based on users' eye makeup intensity. This personalization can enhance learning experiences and promote products or tips that complement their existing styles.

  • Market Trend Analysis: Beauty brands can aggregate data from the identifier to assess popular eye makeup intensities among different demographics. This analysis can inform product development and marketing strategies by revealing emerging trends in eye makeup, allowing brands to stay ahead of the competition.

  • AI-Powered Beauty Apps: Developers can create apps that suggest eye makeup intensity adjustments based on user inputs and desired looks. By offering real-time feedback and styling advice, the apps can enhance user creativity and confidence in applying makeup.

  • Advertising Content Optimization: Advertising agencies can use the identifier to optimize makeup ad visuals based on the eye makeup intensity favored by target audiences. Adjusting campaigns to reflect popular looks can increase engagement rates and improve overall ad performance, driving sales and brand loyalty.

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