Identify how dirty the gym is
using AI
Below is a free classifier to identify how dirty the gym is. Just upload your image, and our AI will predict how dirty the gym is - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("how-dirty-the-gym-is", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/how-dirty-the-gym-is/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_image_url"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_image_url"}' \
https://www.nyckel.com/v1/functions/how-dirty-the-gym-is/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict how dirty the gym is.
This pretrained image model uses a Nyckel-created dataset and has 5 labels, including Clean, Extremely Dirty, Moderately Dirty, Slightly Dirty and Very Dirty.
We'll also show a confidence score (the higher the number, the more confident the AI model is around how dirty the gym is).
Whether you're just curious or building how dirty the gym is detection into your application, we hope our classifier proves helpful.
Need to identify how dirty the gym is at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Gym Hygiene Monitoring: This function can be employed by gym owners to evaluate the cleanliness of their facilities in real time. By classifying areas as "dirty" or "clean," gym operators can prioritize cleaning tasks and ensure a healthy environment for members.
- Member Feedback Integration: The false image classification can assist in streamlining member feedback regarding gym cleanliness. Users can report dirty areas through an app, which uses the function to validate the complaint, thus allowing for quick resolution and enhancing member satisfaction.
- Predictive Cleaning Scheduling: By analyzing historical data on cleanliness levels, this function can help gym management develop predictive models to schedule cleaning staff more effectively. By anticipating peak usage times and identified dirty spots, cleaning operations can be optimized.
- Marketing and Promotion: Gyms can utilize cleanliness data derived from this function to highlight their commitment to hygiene in marketing campaigns. Cleanliness indicators can be displayed in promotional materials to attract new members who prioritize a clean workout environment.
- Compliance Reporting: This classification function can help gyms maintain compliance with health and safety regulations by documenting cleanliness levels over time. Regular reports generated can serve as accountability measures during inspections or audits.
- Training and Staff Management: The function can be used to identify specific areas that require attention from cleaning staff, leading to targeted training and management strategies. Staff can be trained to focus on frequently dirty areas, improving overall cleaning efficiency.
- Environmental Improvement Initiatives: This identifier can help gyms assess the impact of environmental improvements on cleanliness. By implementing changes like better ventilation or increased material durability, gyms can evaluate their effectiveness through the analysis of cleanliness data, leading to informed decision-making.