Pretrained computer vision classifier
Identify smartphone brands with one API call.
A pretrained smartphone brands classifier that sorts an image into one of 10 categories — which smartphone brand it is. Use the smartphone brands API immediately, no training required, then adapt it to your own data when you need more.
Try the smartphone brands classifier
Drop in a photo and get the prediction back. No signup, no setup.
What this smartphone brands classifier recognizes
A sample of the 21 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 smartphone brands 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": "Alcatel",
"labelId": "label_...",
"confidence": 0.92
}Under the hood
Trained on a Nyckel-curated dataset covering 10 smartphone brands 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 smartphone brands classification
Brand Authenticity Verification
This function can be utilized by retailers to authenticate smartphone brands before sale. By classifying the brand of smartphones, retailers can reduce counterfeit products and enhance consumer trust.
Market Research Analysis
Market research firms can leverage this classification function to analyze brand popularity across various demographics. By quickly identifying smartphone brands in user-generated content, firms can gather valuable insights into consumer preferences and trends.
Warranty and Support Services
Customer support centers can use this function to streamline warranty claims and technical support. By accurately identifying the smartphone brand, representatives can provide tailored assistance, improving customer satisfaction and resolution times.
Inventory Management
E-commerce platforms can implement this classification to optimize inventory management. By analyzing the brands of smartphones in stock, businesses can forecast demand, manage resources effectively, and adjust marketing strategies accordingly.
Advertising Targeting
Advertising agencies can use the smartphone brand identifier to tailor marketing campaigns. By understanding which brands are trending, agencies can target ads more effectively, ensuring that promotions reach the right audience.
Social Media Monitoring
Brands can use this function to monitor social media mentions of their products against competitor brands. By classifying the smartphone brands in posts, companies can gauge public sentiment and adjust their marketing strategies.
Fraud Detection in Resale Market
This classification function can aid platforms that facilitate second-hand smartphone sales to detect fraud. By verifying the brand of listed smartphones, platforms can flag inconsistencies and protect buyers from purchasing counterfeit devices.
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 smartphone brands 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 smartphone brands 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.