Identify car maker by roof line using AI

Below is a free classifier to identify car maker by roof line. Just upload your image, and our AI will predict what car maker it is - in just seconds.

car maker by roof line identifier

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Get started

    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("car-maker-by-roof-line", "your_image_url", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/car-maker-by-roof-line/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/car-maker-by-roof-line/invoke
                

How this classifier works

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

This pretrained image model uses a Nyckel-created dataset and has 20 labels, including Audi, Bmw, Chevrolet, Fiat, Ford, Honda, Hyundai, Jaguar, Kia and Land Rover.

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

Whether you're just curious or building car maker by roof line detection into your application, we hope our classifier proves helpful.

Recommended Classifiers

Need to identify car maker by roof line at scale?

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



  • Automotive Market Research: Researchers can utilize the roof line classification function to analyze car designs and trends within specific manufacturers. By automatically categorizing vehicles based on roof contours, they can compile data on design preferences across different car makers and target markets.

  • Insurance Risk Assessment: Insurance companies can leverage this function to assess vehicles for risk evaluation more accurately. By identifying the manufacturer using the roof line, insurers can reference historical claim data related to specific brands and models, allowing for more tailored premium pricing.

  • Automotive Parts Compatibility: Parts manufacturers can use the roof line identification to determine compatibility of after-market parts with specific car models. This aids in streamlining inventory management and production processes by ensuring that only relevant parts are created for popular vehicle lines.

  • Automotive Marketing Campaigns: Marketers can harness the image classification to reach targeted audiences based on car manufacturers identified by roof lines. Campaigns can highlight specific models or features, optimizing advertising budgets by focusing on relevant consumer interests.

  • Fleet Management Optimization: Companies managing vehicle fleets can apply this function for better tracking and managing vehicles based on their manufacturer. By understanding which cars are in their fleet, they can implement manufacturer-specific maintenance schedules and protocols.

  • Vehicle Theft Recovery: Law enforcement agencies can utilize roof line classification technology to enhance vehicle identification in theft recovery efforts. By quickly identifying car manufacturers from images, they can expedite the process of returning stolen vehicles to their rightful owners.

  • Consumer Product Reviews: Online review platforms can incorporate this classification function to improve the accuracy of car reviews and comparisons based on manufacturers. By analyzing various models through roof line identification, they can provide consumers with detailed insights into design, safety, and functionality associated with each automaker.

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