A pretrained cargo ship make classifier that sorts an image into one of 10 categories — what type of cargo ship it is. Use the cargo ship make 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 19 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": "A.P. Moller",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 10 cargo ship make 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.
The cargo ship make identifier can assist fleet managers in tracking and categorizing their vessels. This information can enhance resource allocation and ensure compliance with shipping regulations by managing fleet composition effectively.
Insurance companies can leverage the cargo ship make identifier to streamline risk assessment for marine vessel insurance policies. By accurately identifying the make of the cargo ships, insurers can adjust premiums based on the vessel's specifications and historical performance data.
Ports can use the cargo ship make identifier to optimize dock management and scheduling. By knowing which types of vessels are arriving, ports can allocate resources more efficiently and reduce congestion during peak times.
Shipping companies can use the cargo ship make identifier to ensure compliance with international maritime regulations. This identifier can help verify that vessels meet safety and environmental standards by cross-referencing with a database of approved ship makes.
Analysts and researchers can utilize the cargo ship make identifier to conduct market studies on shipping trends and vessel types in different regions. This data can inform strategic decisions for shipbuilding companies and shipping lines.
Maintenance teams can benefit from the cargo ship make identifier by predicting maintenance needs based on the ship's make and model. This proactive approach can reduce downtime and enhance operational efficiency by scheduling repairs before issues arise.
Environmental agencies can use the cargo ship make identifier to track the types of vessels that enter specific ecosystems. This information is crucial for assessing potential environmental impacts and ensuring that proper measures are in place to protect marine environments.
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 cargo ship make 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.