Identify how many bikes are in the bike rack outside
using AI
Below is a free classifier to identify how many bikes are in the bike rack outside. Just upload your image, and our AI will predict how many bikes are in the bike rack outside - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("how-many-bikes-are-in-the-bike-rack-outside", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/how-many-bikes-are-in-the-bike-rack-outside/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-many-bikes-are-in-the-bike-rack-outside/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict how many bikes are in the bike rack outside.
This pretrained image model uses a Nyckel-created dataset and has 16 labels, including 0 Bikes, 1 Bike, 2 Bikes, 3 Bikes, 4 Bikes, 5 Bikes, 6 Bikes, 7 Bikes, 8 Bikes and 9 Bikes.
We'll also show a confidence score (the higher the number, the more confident the AI model is around how many bikes are in the bike rack outside).
Whether you're just curious or building how many bikes are in the bike rack outside detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify how many bikes are in the bike rack outside at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Inventory Management: Businesses with bike parking facilities can use this function to automatically track how many bikes are parked outside at any given time. This data helps in assessing demand for bike storage and informs decisions about potential capacity expansions.
- Usage Analytics for Transportation Apps: Cycling and urban mobility apps can integrate this functionality to provide users with real-time data on bike availability at various locations. By analyzing trends in bike parking, the app can suggest optimal parking spots to users based on historical data.
- Event Planning: Organizations hosting cycling events can employ this function to gauge the number of bikes parked during the event. This information is crucial for logistical planning, including ensuring there are enough bike racks and managing congestion in high-traffic areas.
- Local Government Monitoring: Municipalities can utilize this technology to monitor bike usage in bike-share programs. By capturing the number of bikes parked, cities can analyze usage patterns to improve bike infrastructure and promote cycling as an eco-friendly transportation option.
- Retail Analytics for Bike Shops: Bike retailers can deploy this function outside their stores to monitor foot traffic indirectly. By observing bike parking trends, shop owners can analyze the correlation between external biking activity and in-store sales, enhancing marketing strategies.
- Smart City Integration: Cities can integrate this function into their smart city initiatives to monitor bike-sharing schemes in real-time. This data will assist in creating automated responses, such as reallocating bikes to areas of higher demand based on parking statistics.
- Community Health Initiatives: Non-profit organizations focused on promoting active lifestyles can use this information to measure the adoption of cycling in specific neighborhoods. This data can help in assessing the impact of health campaigns and designing future programs aimed at increasing cycling participation.