API Access


import nyckel

credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("frozen-meal-brands", "your_image_url", credentials)


fetch('https://www.nyckel.com/v1/functions/frozen-meal-brands/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/frozen-meal-brands/invoke

How this classifier works

To start, upload your image. Our AI tool will then predict what frozen meal brand it is.

This pretrained image model uses a Nyckel-created dataset and has 20 labels, including Amy's Kitchen, Banquet, Birds Eye, Bistromd, Bloom's, Caitlin's, Devour, Dinnerly, Evol and Healthy Choice.

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

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

Need to identify frozen meal brands at scale?

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

Brand Detection for Retail Analytics: The false image classification function can analyze pictures of frozen meal products to identify brands, enabling retailers to gather sales performance and inventory data. This information aids in making informed decisions about stock levels, promotions, and pricing strategies.

Market Trend Analysis: Food industry analysts can utilize this function to collect data on various frozen meal brands and their market presence over time. By analyzing brand performance through image classification, they can spot emerging trends in consumer preferences and adjust marketing strategies accordingly.

Competitive Benchmarking: Companies can use this function to monitor competitor brands within the frozen meal sector, analyzing how their products stack up against others in terms of packaging design and visual appeal. This benchmarking helps inform product development and marketing campaign strategies.

Quality Control in Production: Frozen meal manufacturers can implement this function at various points in their production line to ensure consistent branding and packaging. By identifying package anomalies or misbranding, companies can maintain high quality and reduce the risk of consumer backlash.

E-commerce Product Tagging: Online grocery platforms can leverage image classification to automatically tag frozen meal products accurately by brand. This ensures that customers can easily find and filter products, improving the overall shopping experience and potentially increasing sales conversions.

Brand Affinity Research: Marketing teams can use the function to analyze social media imagery and user-generated content featuring frozen meal brands. This data can reveal customer preferences and sentiment, aiding in the development of targeted marketing campaigns.

Fraud Detection in Food Distribution: Distributors can employ this function to verify the authenticity of frozen meal products as they are received and dispatched. By ensuring that the right brands are being distributed, businesses can prevent loss from counterfeit products and maintain brand integrity.

Identify frozen meal brands using AI

API Access

How this classifier works

Need to identify frozen meal brands at scale?