A pretrained charging connector types classifier that sorts an image into one of 10 categories — what type of charging connector it is. Use the charging connector types API immediately, no training required, then adapt it to your own data when you need more.
Drop in a photo and get the prediction back. No signup, no setup.
A sample of the 20 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.
Once you've added this classifier to your console, you get your own copy of it behind your own endpoint. Invoke it with any HTTP client:
curl
curl -X POST "https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke" \
-H "Authorization: Bearer $NYCKEL_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"data": "https://example.com/photo.jpg"}'Python
import requests
# Get an access token: https://www.nyckel.com/docs/api/overview/authentication/
token = "YOUR_ACCESS_TOKEN"
response = requests.post(
"https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke",
headers={"Authorization": "Bearer " + token},
json={"data": "https://example.com/photo.jpg"},
)
print(response.json())Example response
{
"labelName": "3.5Mm Audio Jack",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 10 charging connector types 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.
This function can be utilized by charging station operators to identify the type of connector needed for various electric vehicles. By recognizing connector types, operators can optimize their station layouts and ensure that the most commonly used connectors are readily available for users.
Retailers of electric vehicle (EV) charging equipment can implement this classification system to track their inventory of charging connectors. By accurately categorizing their stock, businesses can better manage supply chains and ensure they are always equipped with the necessary connectors for their customers.
Automotive manufacturers can leverage this function to assess compatibility between different EV models and charging connectors. By identifying which connectors are most commonly used across their vehicle lineup, manufacturers can make informed decisions on which types to include in their designs.
This classification function can be integrated into consumer-facing applications to help EV owners understand which charging connectors their vehicles require. Providing accurate information will enhance user experience and reduce the chances of connection errors at charging stations.
Companies operating fleets of electric vehicles can use this classification function to ensure their charging infrastructure matches their fleet's specific connector requirements. By streamlining this process, fleets can minimize downtime caused by incompatibility issues.
Charging networks and vehicle manufacturers can analyze the classified data to detect trends in charging connector usage. This insight can guide future product development and marketing strategies based on consumer preferences and emerging standards in the industry.
Utility companies can utilize the charging connector type identifier to facilitate better integration of charging stations into the smart grid. By understanding connector types and locations, they can optimize energy distribution and improve demand response initiatives for electric charging.
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.
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.
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.
No. This charging connector types 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.
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.
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.