Identify if document has proper lighting using AI

Below is a free classifier to identify if document has proper lighting. Just upload your image, and our AI will predict if the document has proper lighting - in just seconds.

if document has proper lighting identifier

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Get started

    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("if-document-has-proper-lighting", "your_image_url", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/if-document-has-proper-lighting/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/if-document-has-proper-lighting/invoke
                

How this classifier works

To start, upload your image. Our AI tool will then predict if the document has proper lighting.

This pretrained image model uses a Nyckel-created dataset and has 2 labels, including Poorly Lit and Well Lit.

We'll also show a confidence score (the higher the number, the more confident the AI model is around if the document has proper lighting).

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

Need to identify if document has proper lighting at scale?

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



  • Document Quality Assessment: This function can be used by scanning services to ensure that documents are captured with proper lighting before processing. By identifying documents with suboptimal lighting, organizations can optimize their scanning workflow and enhance the quality of results.

  • Automated Photo Editing: Photo editing software can integrate this lighting identifier to automatically assess images and suggest enhancements. If a document is found to have improper lighting, the software can offer corrective measures or automatically adjust the lighting for better visual appeal.

  • Document Verification for Legal Firms: Legal firms can utilize this function to verify that scanned documents adhere to lighting standards before submission. Ensuring proper lighting can minimize disputes over document authenticity and clarity in legal proceedings.

  • Educational Resource Management: Educational institutions can implement this identifier to evaluate the quality of submitted digital assignments. By ensuring that documents are well-lit, they can improve the readability and visual quality of student submissions, aiding in grading and assessment.

  • Insurance Claim Processing: Insurance companies can employ this technology to assess the quality of submitted documentation for claims. Proper lighting can help in accurately reviewing images related to claims and reduce the chances of misinterpretation due to poor image quality.

  • E-commerce Product Listings: E-commerce platforms can integrate this function to ensure that seller-uploaded images of products meet lighting standards. By identifying poorly lit images, platforms can prompt sellers to enhance their photos, leading to better presentation and potentially higher sales.

  • Archiving and Digitization Projects: Libraries and archival institutions can use this identifier to evaluate the quality of digitized documents. Ensuring that documents are scanned with proper lighting can enhance their long-term preservation and make them more accessible to users.

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