Pretrained computer vision classifier
Identify length of car in feet with one API call.
A pretrained length of car in feet classifier that sorts an image into one of 10 categories — the length of the car in feet. Use the length of car in feet API immediately, no training required, then adapt it to your own data when you need more.
Try the length of car in feet classifier
Drop in a photo and get the prediction back. No signup, no setup.
What this length of car in feet classifier recognizes
A sample of the 52 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 length of car in feet 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": "1 Foot",
"labelId": "label_...",
"confidence": 0.92
}Under the hood
Trained on a Nyckel-curated dataset covering 10 length of car in feet 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 length of car in feet classification
Automated Vehicle Inventory Management
In car dealerships, the 'length of car in feet' identifier can enhance inventory management systems by accurately classifying vehicles based on their size. This helps streamline space allocation in showrooms and lots, ensuring optimal use of available resources and improving customer experience.
Parking Space Optimization
Cities can utilize this function in smart parking solutions to assess and categorize parking spaces according to the length of vehicles. By analyzing the lengths of cars, cities can optimize parking space availability, guiding drivers to appropriate areas and reducing congestion.
Insurance Risk Assessment
Insurance companies can apply the length classification to determine potential risk factors associated with insuring different vehicle types. Understanding the dimensions of cars helps in tailoring policies and premiums based on risk profiles associated with vehicle size and usage.
Road Safety Analysis
Transportation agencies can leverage the length of vehicles to conduct safety analyses on road conditions and accident data. By correlating vehicle length with accident rates, they can implement targeted safety measures and improve road infrastructure planning.
Fleet Management Efficiency
Companies with vehicle fleets can use this classification function to manage and categorize their vehicles. By understanding the length of each vehicle, managers can enhance logistics planning and optimize routes based on vehicle size, leading to better fuel efficiency and reduced operational costs.
Automated Toll Collection Systems
Highway toll systems can implement this function to classify vehicles for toll fee determination. By identifying car lengths automatically, the system can charge fees based on vehicle size, promoting a fairer tolling system and enhancing revenue collection.
Environmental Impact Assessments
Researchers can utilize the length of cars to study the environmental impact of different vehicle types. By analyzing data on vehicle size alongside emissions statistics, they can identify trends and advocate for policies that promote smaller, more efficient vehicles for better environmental outcomes.
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 length of car in feet 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 length of car in feet 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.