A pretrained aerial views of rivers classifier that sorts an image into one of 2 categories. Use the aerial views of rivers API immediately, no training required, then adapt it to your own data when you need more.
Drop in a photo and get the prediction back. No signup, no setup.
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.
Once you've added this classifier to your console, you get your own copy of it behind your own endpoint. Invoke it with any HTTP client:
curl
curl -X POST "https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke" \
-H "Authorization: Bearer $NYCKEL_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"data": "https://example.com/photo.jpg"}'Python
import requests
# Get an access token: https://www.nyckel.com/docs/api/overview/authentication/
token = "YOUR_ACCESS_TOKEN"
response = requests.post(
"https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke",
headers={"Authorization": "Bearer " + token},
json={"data": "https://example.com/photo.jpg"},
)
print(response.json())Example response
{
"labelName": "Clear Water River",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 2 aerial views of rivers 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.
This use case focuses on detecting changes in river ecosystems over time. By analyzing aerial views, organizations can assess the health of aquatic habitats, identify pollution sources, and monitor biodiversity, ultimately aiding in conservation efforts.
Aerial image classification can help identify river patterns and surrounding topographies to evaluate flood risks. This information is crucial for urban planning, emergency response strategies, and implementing preventative measures in flood-prone areas.
City planners can utilize aerial views to determine ideal locations for infrastructure projects near rivers. The classification function aids in ensuring developments are sustainable and do not negatively impact river ecosystems or floodplains.
By classifying aerial images of rivers, water resource managers can track water flow and assess water availability. This data is essential for efficient water allocation, particularly in agriculture and urban areas reliant on river systems.
This use case involves evaluating river access points for recreational activities such as kayaking or fishing. Aerial views can help identify suitable access locations while considering environmental conservation and public safety.
Aerial image classification can assist in monitoring the condition of bridges, dams, and levees situated over rivers. This proactive approach allows for timely maintenance or repairs, improving infrastructure safety and longevity.
Researchers can use aerial views to study the impact of climate change on river systems. By classifying changes in river flow, vegetation, and surrounding landscapes, they can better understand how climate shifts influence these vital ecosystems.
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.
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.
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.
No. This aerial views of rivers 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.
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.
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.