Identify lipstick color using AI

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

lipstick color identifier

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Get started

    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("lipstick-color", "your_image_url", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/lipstick-color/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/lipstick-color/invoke
                

How this classifier works

To start, upload your image. Our AI tool will then predict what lipstick color it is.

This pretrained image model uses a Nyckel-created dataset and has 20 labels, including Berry, Brown, Burgundy, Clear, Coral, Fuchsia, Glossy, Lavender, Matte and Mauve.

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

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

Need to identify lipstick color at scale?

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



  • Virtual Makeup Try-On: This function enables users to upload their photos and receive real-time feedback on how different lipstick colors would look on them. Cosmetic brands can integrate this feature into their apps or websites, enhancing customer engagement and reducing return rates for lip products.

  • Personalized Marketing Campaigns: By analyzing user-uploaded images, businesses can identify preferred lipstick shades and target them with tailored marketing. This allows for more effective email campaigns and social media ads that resonate with individual customer preferences.

  • Trend Analysis for Lipstick Colors: Retailers can leverage the function to track popular lipstick colors in user images uploaded across different platforms. This data can inform inventory decisions, ensuring that stores stock trending shades and stay ahead of market demands.

  • Unboxing Experience Enhancement: Brands can include an augmented reality feature that identifies the lipstick shade in videos when influencers or customers unbox products. This adds a layer of interactivity and education to social media marketing efforts, showcasing how specific colors appear on different skin tones.

  • Lipstick Shade Comparison Tool: Users can upload images of multiple lipstick products to receive suggestions on similar shades available in their favorite brands. This function can improve customer satisfaction by simplifying the decision-making process when comparing different lip products.

  • AI Beauty Advisors: Beauty salons or makeup artists can utilize this function in conjunction with virtual consultations to recommend the most suitable lipstick shades based on a customer’s uploaded photo. This can enhance the client experience by providing personalized and expert advice.

  • Product Development Insights: Cosmetic companies can analyze classification data from user images to identify unmet needs or gaps in the market for certain lipstick shades. This insight can drive new product development that is closely aligned with consumer demand.

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