Pretrained computer vision classifier
Identify qr code contrast level with one API call.
A pretrained qr code contrast level classifier that sorts an image into one of 8 categories — the contrast level of the QR code. Use the qr code contrast level API immediately, no training required, then adapt it to your own data when you need more.
Try the qr code contrast level classifier
Drop in a photo and get the prediction back. No signup, no setup.
What this qr code contrast level 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 qr code contrast level 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": "Acceptable Contrast",
"labelId": "label_...",
"confidence": 0.92
}Under the hood
Trained on a Nyckel-curated dataset covering 8 qr code contrast level 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 qr code contrast level classification
Retail Checkout Optimization
Retailers can utilize the 'qr code contrast level' identifier to ensure that QR codes on products and digital receipts are printed with the appropriate contrast levels. This reduces scanning errors at checkout, leading to improved customer experience and faster transaction times.
Event Ticketing System
Event organizers can implement this function to verify the contrast levels of QR codes on tickets, ensuring that they can be easily scanned by entry staff. This helps eliminate queues and enhances attendee satisfaction by streamlining the entry process.
Marketing Campaign Monitoring
Marketers can analyze the contrast levels of QR codes used in printed materials, such as flyers and posters, to ensure optimal visibility. By ensuring that these codes are scannable, they can track engagement and conversion rates more effectively from various campaigns.
Product Authentication
Manufacturers can use this function to verify QR codes on products meant for authentication purposes. By ensuring a high contrast level, they can prevent counterfeiting and enhance consumer trust in their brand.
Mobile Payment Solutions
Payment providers can assess QR code contrast levels to ensure seamless scanning during transactions. This ensures that users can make payments quickly and efficiently, reducing the likelihood of transaction failures and enhancing overall user satisfaction.
Logistics and Supply Chain Management
Logistics companies can incorporate this identifier to validate QR codes on shipping labels. By ensuring that the contrast levels meet the required standards, they can minimize scanning errors throughout the supply chain, leading to improved inventory tracking and management.
Healthcare Patient Check-In
Hospitals and clinics can use the contrast level identifier to ensure that patient QR codes on appointment confirmations or ID badges are easily scannable. This improves check-in processes, reduces wait times, and enhances the overall patient experience.
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 qr code contrast level 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 qr code contrast level 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.