Pretrained computer vision classifier
Identify if a tree is dying with one API call.
A pretrained if a tree is dying classifier that sorts an image into one of 2 categories. Use the if a tree is dying API immediately, no training required, then adapt it to your own data when you need more.
Try the if a tree is dying classifier
Drop in a photo and get the prediction back. No signup, no setup.
What this if a tree is dying classifier recognizes
A sample of the 2 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 if a tree is dying 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": "Dying Tree",
"labelId": "label_...",
"confidence": 0.92
}Under the hood
Trained on a Nyckel-curated dataset covering 2 if a tree is dying 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 if a tree is dying classification
Urban Forestry Management
Municipalities can use the identifier to monitor the health of trees in urban areas. By identifying dying trees early, city planners can prioritize maintenance and replacement efforts, improving urban biodiversity and reducing risks from falling branches.
Insurance Assessment
Insurance companies can deploy the identifier for evaluating claims related to property damage caused by fallen trees. By accurately identifying dying trees, insurers can determine liability and expedite claims processing, leading to enhanced customer satisfaction.
Environmental Conservation
Non-profit organizations focused on reforestation and conservation can use this tool to assess forest health. By pinpointing dying trees, they can allocate resources more effectively for interventions, increasing the success rate of conservation efforts.
Pest and Disease Monitoring
Agricultural and forestry businesses can utilize the identifier to detect pest infestations and disease spread among trees. By identifying affected specimens, they can implement targeted treatment strategies, thereby safeguarding their timber resources and reducing economic losses.
Landscape Maintenance Services
Landscape maintenance companies can adopt the identifier as part of their tree care services. This tool enables timely detection and communication with clients regarding tree health, leading to enhanced service offerings and improved customer relationships.
Wildfire Risk Assessment
Fire management agencies can use the identifier to locate and assess trees that are dying due to drought or disease, which increases the risk of wildfires. By managing these trees proactively, agencies can lower wildfire hazards and improve community safety.
Climate Change Research
Academic institutions and environmental researchers can use the identifier to study the impacts of climate change on tree health. This data can contribute to larger ecological studies and models, providing insights into forest ecosystems and guiding future conservation strategies.
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 if a tree is dying 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 if a tree is dying 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.