Identify vegetable health using AI

Below is a free classifier to identify vegetable health. Just upload your image, and our AI will predict the health status of various vegetables - in just seconds.

API Access


import nyckel

credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("vegetable-health", "your_image_url", credentials)


fetch('https://www.nyckel.com/v1/functions/vegetable-health/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/vegetable-health/invoke

How this classifier works

To start, upload your image. Our AI tool will then predict the health status of various vegetables.

This pretrained image model uses a Nyckel-created dataset and has 26 labels, including Bruised, Damaged, Dead, Decaying, Discolored, Diseased, Dry, Faded, Fresh and Frozen.

We'll also show a confidence score (the higher the number, the more confident the AI model is around the health status of various vegetables).

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

Need to identify vegetable health at scale?

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

Crop Monitoring: This function can be utilized by farmers to assess the health of their vegetable crops in real-time. By accurately classifying images of vegetables, farmers can quickly identify unhealthy plants and take necessary actions to improve crop productivity.

Quality Control in Supply Chains: Retailers and distributors can use the false image classification function to monitor the quality of vegetables during transportation and storage. By identifying anomalies in vegetable health, businesses can ensure that only high-quality produce reaches the market, reducing waste and returns.

Pest and Disease Detection: Agricultural experts and consultants can leverage this function to detect early signs of pest infestations or diseases in vegetable crops. By analyzing images, they can provide actionable insights to farmers, facilitating timely interventions and preventing extensive damage.

Agricultural Research: Research institutions can use this classifier to study various vegetable species and their responses to environmental stressors. By analyzing health data from classified images, researchers can gain critical insights into plant physiology and improve breeding programs for healthier crops.

Smart Farming Solutions: Technology companies developing smart farming solutions can integrate this image classification function into their platforms. This would enable farmers to automate vegetable health assessments, optimize resource use, and increase overall efficiency in farm management.

Education and Training: Agronomy schools and training programs can employ this function to educate students about vegetable health assessment techniques. Hands-on experience with image analysis can enhance learning outcomes and prepare future agricultural professionals for industry demands.

Consumer Transparency: Food businesses can use the health identifier to assure consumers of the quality of vegetables they purchase. By providing evidence and reports on the health classification of produce, companies can build trust and differentiate themselves in a competitive market.