Pretrained computer vision classifier

Identify flooring status with one API call.

A pretrained flooring status classifier that sorts an image into one of 10 categories — the condition of various flooring types.. Use the flooring status API immediately, no training required, then adapt it to your own data when you need more.

Pretrained · Nyckel-trained 10 labels out of the box Image input

Try the flooring status classifier

Drop in a photo and get the prediction back. No signup, no setup.

What this flooring status classifier recognizes

A sample of the 20 labels this pretrained classifier chooses between.

Clean
Cracked
Damaged
Discolored
Faded
Loose Tiles
Maintained
New
Original
Polished

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 flooring status API

Get your own copy of this classifier behind your own endpoint — callable from any HTTP client:

API quick start
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"}'

Example response

{
  "labelName": "Clean",
  "labelId": "label_...",
  "confidence": 0.92
}

Under the hood

Model type
Nyckel-trained

Trained on a Nyckel-curated dataset covering 10 flooring status categories, served on Nyckel's own infrastructure — your image stays on Nyckel.

Input
Image

Send an image URL or file to the invoke endpoint; the response is a label with a confidence score.

Make it yours
Adaptable

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.

More than a demo: this page is one of thousands of pretrained functions on Nyckel, an ML classification platform. You can invoke classifiers by API, review predictions, correct labels, collect samples from production traffic, and promote any pretrained function to a private custom model — without changing your integration.

Where teams use flooring status classification

Property Management Efficiency

The flooring status identifier can be used by property management companies to automatically assess the condition of flooring in multiple units. By quickly categorizing the flooring status, managers can prioritize maintenance tasks, schedule repairs, and enhance tenant satisfaction through timely interventions.

Real Estate Valuation

Real estate appraisers can integrate this function to evaluate flooring conditions during property assessments. Accurate identification of flooring status can impact the property’s market value, enabling appraisers to provide more precise valuations for buyers and sellers.

Insurance Claims Processing

Insurance companies can utilize the flooring status identifier to streamline claims related to water damage, fire, or wear and tear. By quickly classifying the flooring condition, insurers can expedite the claims process and determine the extent of coverage needed for repairs.

Renovation Planning

Contractors and renovation companies can leverage this function to assess the existing flooring in homes or commercial spaces before undertaking projects. This will help them provide accurate estimates for flooring replacements or refinishing and ensure that project timelines are adhered to.

Inventory Management for Flooring Suppliers

Flooring suppliers can implement the identifier to assess returned or unsold inventory. By determining the condition of flooring samples or stock, suppliers can make informed decisions about restocking, pricing, and promotions.

Flooring Maintenance Tracking

Businesses with large commercial spaces can use this function to keep track of the flooring condition over time. By regularly assessing flooring status, they can schedule maintenance proactively, reducing long-term costs associated with flooring replacement or extensive repairs.

Smart Home Integration

The flooring status identifier can be integrated into smart home systems, allowing homeowners to monitor the condition of their flooring. This can provide alerts for unusual wear and tear, enabling homeowners to address issues before they lead to more significant damage or safety hazards.

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 flooring status 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.

Ready to classify flooring status 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.