Pretrained computer vision classifier
Identify bathroom condition with one API call.
A pretrained bathroom condition classifier that sorts an image into one of 10 categories — the condition of the bathroom.. Use the bathroom condition API immediately, no training required, then adapt it to your own data when you need more.
Try the bathroom condition classifier
Drop in a photo and get the prediction back. No signup, no setup.
What this bathroom condition classifier recognizes
A sample of the 15 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 bathroom condition 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 Condition",
"labelId": "label_...",
"confidence": 0.92
}Under the hood
Trained on a Nyckel-curated dataset covering 10 bathroom condition 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 bathroom condition classification
Hotel Quality Assurance
This function can be utilized by hotel chains to automatically assess the condition of their bathrooms through image analysis. By identifying issues such as cleanliness, maintenance needs, and amenity availability, management can ensure a consistent quality experience for guests.
Property Management Inspections
Property management companies can incorporate this function during regular inspections to evaluate the state of bathrooms in rental properties. By quickly identifying problems, they can address maintenance issues proactively, thereby enhancing tenant satisfaction and retention.
Smart Home Devices
Smart home systems can integrate this function to monitor bathroom conditions in real-time. This would allow for alerts regarding cleanliness or maintenance, helping homeowners maintain a better living environment and increase the lifespan of plumbing fixtures.
Facility Maintenance Scheduling
Businesses and institutions can leverage this function to streamline their facility maintenance operations. By automating inspections and condition assessments, management can prioritize cleaning or repairs more efficiently, ultimately reducing operational costs and improving service delivery.
Insurance Claim Evaluations
Insurance companies can use this image classification function to assess bathroom conditions in claims related to water damage or other incidents. By accurately identifying the state of facilities from images, they can make informed decisions regarding claims processing and payouts.
Real Estate Listing Verification
Real estate agents and platforms can implement this function to verify the actual condition of bathrooms in properties being listed. By ensuring that images reflect true conditions, they can increase trust with potential buyers, leading to faster sales and satisfaction.
Market Research Analysis
Companies in the cleaning and home improvement sectors can employ this function to gather data about bathroom conditions across various demographics or regions. Insights derived from this analysis can inform product development and targeted marketing strategies to better serve their customer base.
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 bathroom condition 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 bathroom condition 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.