Identify lighting quality using AI

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

lighting quality identifier

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Get started

    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("lighting-quality", "your_image_url", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/lighting-quality/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/lighting-quality/invoke
                

How this classifier works

To start, upload your image. Our AI tool will then predict the lighting quality of your images.

This pretrained image model uses a Nyckel-created dataset and has 16 labels, including Adequate, Artificial Light, Balanced Light, Bright, Dim, Filtered Light, Harsh Light, Mixed Light, Natural Light and Overexposed.

We'll also show a confidence score (the higher the number, the more confident the AI model is around the lighting quality of your images).

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

Need to identify lighting quality at scale?

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



  • Quality Control in Manufacturing: The lighting quality identifier can help manufacturers ensure that products are being produced under optimal lighting conditions. By monitoring lighting quality, companies can spot issues that affect product appearance and quality, leading to fewer defects and rejections.

  • Retail Display Optimization: Retailers can utilize the lighting quality identifier to assess the effectiveness of their display lighting. By analyzing how lighting conditions affect product visibility and customer engagement, stores can optimize their setups to enhance shopper experience and boost sales.

  • Interior Design Enhancement: Interior designers can leverage this function to evaluate lighting in various environments. This helps them select appropriate lighting solutions that enhance aesthetics and function, ensuring spaces are both visually pleasing and usable.

  • Photographic Quality Assessment: Photographers can use the lighting quality identifier to ensure optimal conditions for their shoots. By assessing the lighting in real-time, they can adjust their setups accordingly, resulting in higher-quality images with better color accuracy and detail.

  • Agricultural Monitoring: In agriculture, this function can help assess the lighting conditions in greenhouses or indoor farms. By identifying inadequate lighting, farmers can optimize plant growth and yield, ensuring crops receive the right amount of light for photosynthesis.

  • Event Planning: Event planners can utilize the lighting quality identifier to ensure venues are adequately lit for different types of events. By checking lighting conditions in advance, planners can recommend adjustments or enhancements that improve the overall ambiance and attendee experience.

  • Workplace Productivity Improvement: Companies can implement this identifier to measure lighting quality in office environments. By ensuring optimal lighting conditions, they can enhance employee well-being and productivity, reducing eye strain and improving focus in workspaces.

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