Pretrained computer vision classifier
Identify furniture presence with one API call.
A pretrained furniture presence classifier that sorts an image into one of 2 categories. Use the furniture presence API immediately, no training required, then adapt it to your own data when you need more.
Try the furniture presence classifier
Drop in a photo and get the prediction back. No signup, no setup.
What this furniture presence classifier recognizes
A sample of the 2 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 furniture presence 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": "Furniture Present",
"labelId": "label_...",
"confidence": 0.92
}Under the hood
Trained on a Nyckel-curated dataset covering 2 furniture presence 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 furniture presence classification
Real Estate Listing Accuracy
Real estate websites could use the 'furniture presence' identifier to ensure the accuracy of their listings. If a property is described as furnished, the tool can validate this by checking if the associated images include furniture.
Automated Inventory Management
Furniture stores could use the technology to quickly and accurately inventory their stock based on photographs of the showroom floor, simplifying and accelerating the inventory management process.
Second-hand Marketplace Verification
Online platforms for selling used furniture could integrate this feature to verify that uploaded photos indeed contain furniture, thus improving the quality and relevancy of listings.
Virtual Staging Service
Real estate agencies can use the 'furniture presence' function to identify and remove existing furniture from property images, then virtually "stage" or redesign the space with different furniture using augmented reality.
Damage Assessment for Insurance Companies
Insurers could use this tool to evaluate claim photos for furniture damage. This could speed up claim processing by automatically recognizing the damaged furniture items.
Furniture Removal Companies Efficiency
Furniture removal companies can use the identifier to estimate the quantity, size, and style of furniture to be removed, thereby improving quote accuracy and planning efficiency.
Assisting in Interior Design
Interior design firms can use this feature to identify the presence of furniture and its position in a room. It can help them visualize new design concepts and communicate ideas with their clients more effectively.
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 furniture presence 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 furniture presence 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.