Pretrained computer vision classifier
Identify broken fingers with one API call.
A pretrained broken fingers classifier that sorts an image into one of 2 categories — whether the finger is broken or not. Use the broken fingers API immediately, no training required, then adapt it to your own data when you need more.
Try the broken fingers classifier
Drop in a photo and get the prediction back. No signup, no setup.
What this broken fingers classifier recognizes
A sample of the 8 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 broken fingers 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": "Broken",
"labelId": "label_...",
"confidence": 0.92
}Under the hood
Trained on a Nyckel-curated dataset covering 2 broken fingers 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 broken fingers classification
Medical Diagnosis Support
This feature can be used in healthcare businesses for aiding doctors in medical diagnosis. It could quickly identify potentially broken fingers from imaging results, providing a quick initial assessment for medical professionals.
Emergency Triage Tool
In emergency cases, this could be used as a first point of assessment. As patients come in, basic images of potential injuries could be taken and quickly analyzed, helping medical staff prioritize patients in a busy ER.
Insurance Claim Verification
Insurance companies could use the 'broken finger' identifier to verify claims related to broken fingers. This will aid in ensuring the validity of claims, thereby reducing the risk of fraudulent claims.
Workplace Safety Assessment
Companies with high risk environments such as construction sites can use this tool to assess the staff's hand safety. It can help identify potential injuries quickly, even if the employee didn't initially report it.
Telemedicine Consultations
This tool can be useful in conducting consultations virtually, enabling remote diagnosis of possible broken fingers. It increases the reach of healthcare professionals to remote locations.
Sports Training Centers
This function could be used in sports centers for instant assessment of any finger-related injuries suffered by the athletes during training or games.
Education and Training
This can be used in medical schools or training sessions to educate students about how to identify a broken finger. This tool will help them to learn quickly and efficiently by showing them real-life, practical examples.
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 broken fingers 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 broken fingers 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.