Identify cooking methods using AI

Below is a free classifier to identify cooking methods. Just upload your image, and our AI will predict which cooking method is being used - in just seconds.

cooking methods identifier

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Get started

    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("cooking-methods", "your_image_url", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/cooking-methods/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/cooking-methods/invoke
                

How this classifier works

To start, upload your image. Our AI tool will then predict which cooking method is being used.

This pretrained image model uses a Nyckel-created dataset and has 21 labels, including Baking, Barbecue, Blanching, Boiling, Braising, Charbroiling, Cooking Sous Vide, Deep Frying, Dehydrating and Frying.

We'll also show a confidence score (the higher the number, the more confident the AI model is around which cooking method is being used).

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

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Need to identify cooking methods at scale?

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



  • Recipe Recommendation System: This use case involves a smart cooking application that utilizes the cooking methods identifier to offer users personalized recipe suggestions. By accurately identifying the preferred cooking methods from user-uploaded images, the application can align recipes with users' cooking styles and available kitchen appliances, enhancing their culinary experience.

  • Cooking Training Programs: Educational platforms can integrate the cooking methods identifier to improve their online cooking classes. By analyzing the cooking methods shown in user-submitted videos or images, the platform can provide tailored feedback, suggesting areas for improvement or alternative techniques to enhance skill development.

  • Food Blogging and Content Creation: Food bloggers can use the cooking methods identifier to categorize and tag their content more effectively. By identifying the cooking styles depicted in their photos, they can enhance search engine optimization (SEO) and attract a more targeted audience interested in specific cooking techniques.

  • Smart Kitchen Appliances: Kitchen appliance manufacturers can integrate this function into their smart products, allowing devices to adapt to the user’s preferred cooking methods. For instance, an oven could adjust its settings automatically based on the identified cooking styles, optimizing temperature and timing for each specific method.

  • Menu Personalization for Restaurants: Restaurants can leverage the cooking methods identifier to tailor their menus according to customer preferences. By analyzing images of dishes that customers interact with on social media or their foodie apps, restaurants can gain insights into popular cooking methods, allowing them to create personalized dining experiences.

  • Culinary Competitions and Events: Organizers of culinary competitions can utilize the cooking methods identifier to assess and categorize participants' dishes more efficiently. This technology can help judges identify and rate the methods used, ensuring fair evaluations and inspiring new competition categories focused on specific cooking techniques.

  • Nutrition and Meal Planning Apps: Health-focused meal planning applications can use the cooking methods identifier to provide users with optimized meal suggestions based on their dietary preferences and cooking capabilities. By understanding users' preferred cooking methods, the app can recommend meals that are both healthy and feasible for the user to prepare, ensuring alignment with their lifestyle and health goals.

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