Pretrained computer vision classifier
Identify motorcycle make by engine with one API call.
A pretrained motorcycle make by engine classifier that sorts an image into one of 10 categories — what make of motorcycle it is. Use the motorcycle make by engine API immediately, no training required, then adapt it to your own data when you need more.
Try the motorcycle make by engine classifier
Drop in a photo and get the prediction back. No signup, no setup.
What this motorcycle make by engine classifier recognizes
A sample of the 20 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 motorcycle make by engine 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": "Aprilia",
"labelId": "label_...",
"confidence": 0.92
}Under the hood
Trained on a Nyckel-curated dataset covering 10 motorcycle make by engine 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 motorcycle make by engine classification
Insurance Claim Processing
Insurance companies can use the motorcycle make by engine identifier to verify the make of a motorcycle during claim processing. By accurately identifying the motorcycle, insurers can streamline verification, assess coverage, and reduce fraudulent claims based on mismatches between reported and actual motorcycle details.
Motorcycle Retail Inventory Management
Motorcycle dealerships can implement this function to optimize their inventory management. By automatically categorizing motorcycles by make and engine type, dealerships can enhance their inventory accuracy, quickly identify popular models, and manage restocks based on consumer demand trends.
Theft Recovery Systems
Law enforcement agencies can deploy the motorcycle make by engine identifier in conjunction with vehicle recovery systems. This identification helps officers swiftly verify the ownership and legitimacy of recovered motorcycles, facilitating quicker returns to rightful owners and aiding in criminal investigations.
Vehicle Registration Compliance
Government agencies tasked with vehicle registration can use this identifier to ensure compliance with regulations. By cross-referencing the motorcycle make and engine data during the registration process, agencies can mitigate registration fraud and ensure that all vehicles on the road meet safety and environmental standards.
Sales and Marketing Insights
Motorcycle manufacturers can leverage the identifier to gather insights on market trends related to specific engine types and motorcycle makes. By analyzing this data, companies can tailor their marketing strategies to target specific demographics, optimize their product lines, and increase sales effectiveness.
Aftermarket Parts Compatibility
Aftermarket part suppliers can utilize the motorcycle make by engine identifier to enhance their product offerings. By accurately identifying the compatible motorcycles for various parts, suppliers can improve customer satisfaction, reduce return rates, and enhance the overall shopping experience.
Motorcycle Enthusiast Communities
Online platforms and forums dedicated to motorcycle enthusiasts can use this function to categorize motorcycles based on their engine make. This allows users to easily find and share information, reviews, and recommendations related to specific types of motorcycles, fostering a sense of community and support among riders.
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 motorcycle make by engine 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 motorcycle make by engine 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.