Pretrained computer vision classifier
Identify tree health with one API call.
A pretrained tree health classifier that sorts an image into one of 10 categories — the health status of a tree species. Use the tree health API immediately, no training required, then adapt it to your own data when you need more.
Try the tree health classifier
Drop in a photo and get the prediction back. No signup, no setup.
What this tree health classifier recognizes
A sample of the 29 labels this pretrained classifier chooses between.
Need a label that isn't here? Clone the classifier into your Nyckel console and edit the label set to fit your data.
Call the tree health API
Get your own copy of this classifier behind your own endpoint — callable from any HTTP client:
curl -X POST "https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke" \
-H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"data": "https://example.com/photo.jpg"}'import requests
response = requests.post(
"https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke",
headers={"Authorization": "Bearer YOUR_ACCESS_TOKEN"},
json={"data": "https://example.com/photo.jpg"},
)
print(response.json())const response = await fetch("https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_ACCESS_TOKEN",
"Content-Type": "application/json",
},
body: JSON.stringify({ data: "https://example.com/photo.jpg" }),
});
console.log(await response.json());$ch = curl_init();
curl_setopt($ch, CURLOPT_URL, 'https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke');
curl_setopt($ch, CURLOPT_RETURNTRANSFER, 1);
curl_setopt($ch, CURLOPT_POST, 1);
curl_setopt($ch, CURLOPT_POSTFIELDS, '{"data": "https://example.com/photo.jpg"}');
$headers = array();
$headers[] = 'Authorization: Bearer YOUR_ACCESS_TOKEN';
$headers[] = 'Content-Type: application/json';
curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
$result = curl_exec($ch);
curl_close($ch);
echo $result;Example response
{
"labelName": "Bark Damage",
"labelId": "label_...",
"confidence": 0.92
}Under the hood
Trained on a Nyckel-curated dataset covering 10 tree health categories, served on Nyckel's own infrastructure — your image stays on Nyckel.
Send an image URL or file to the invoke endpoint; the response is a label with a confidence score.
Clone it, then correct predictions and add your own samples in the console — Nyckel retrains automatically, turning this into a custom model tuned to your data.
Where teams use tree health classification
Arborist Assistance
The tree health identifier can be used by arborists to assess the condition of trees before undertaking any maintenance or removal. By using the function to classify images, arborists can quickly identify signs of disease or pest infestation, allowing for informed decision-making.
Urban Forestry Management
Municipalities can utilize the tree health identifier for urban forestry management programs. By analyzing images of street trees and parks, they can monitor overall tree health and prioritize care for those in poor condition, improving urban green spaces and public safety.
Agricultural Monitoring
Farmers and agricultural consultants can employ the identifier to monitor orchards and wooded areas. By regularly assessing tree health through images, they can detect early signs of stress or disease, optimizing yield and minimizing potential losses.
Environmental Research
Researchers studying ecosystems can use the tree health identifier to gather data on forest health and biodiversity. By classifying images of various tree species, they can analyze the impact of environmental factors on tree vitality, contributing to conservation efforts.
Insurance Assessments
Insurance companies can implement the identifier to assess claims related to tree damage or health. By quickly evaluating the condition of trees in photographs submitted by policyholders, insurers can expedite claims processing and determine coverage.
Landscaping Services
Landscaping companies can use the tree health identifier to provide assessments to clients about existing trees on their properties. This functionality allows them to offer tailored recommendations for tree care, replacements, and landscaping designs that enhance property aesthetics and health.
Educational Tools
Schools and educational organizations can implement this technology for environmental science curricula. By using the tree health identifier in hands-on activities, students can learn about botany, ecology, and the importance of tree health while engaging with real-world applications.
Common questions
What's the difference between a zero-shot and a Nyckel-trained classifier?
A zero-shot classifier uses a large foundation model's general knowledge to pick between your labels — no task-specific training, so new or edited labels work immediately. A Nyckel-trained classifier has been trained on labeled examples and runs on Nyckel's own infrastructure, which typically makes it faster, cheaper per call, and more accurate on data that resembles its training set. The "Under the hood" section on this page shows which kind this classifier is, and any classifier can be adapted into a trained one by adding your own examples.
How do I know whether this will work for my application?
Honestly: we can't know in advance — it depends on your data stream and how closely it resembles what this classifier has seen. The reliable way to find out is to measure it on your own data: start invoking the classifier with real traffic, or upload and annotate a set of images in the console — make sure they look like your production data, not idealized examples. Nyckel's evaluation metrics then show you exactly how it performs on that data before you rely on it.
What happens when it makes a mistake?
No classifier is perfect, so Nyckel is built around the correction loop: invokes can be captured for review, you confirm or correct predictions in the console, and corrections become training data. Over time the model adapts to your data distribution — accuracy on your traffic improves with use rather than staying fixed.
Do I need training data to get started?
No. This tree health classifier works out of the box — clone it into your console and you'll have your own API endpoint in under a minute. Training data only enters the picture when you want to adapt it: your corrected predictions and uploaded samples improve the model, and you can also edit the label set to match your needs.
What does it cost to try?
Trying the classifier on this page is free with no signup. Cloning it requires a free account, and the free tier covers your first API calls each month — see nyckel.com/pricing for current limits and paid tiers.
Related classifiers
Ready to classify tree health at scale?
Add this pretrained classifier to your Nyckel console — you'll get a live API endpoint in under a minute, and a path to a custom model when you need one.