A pretrained power cord types classifier that sorts an image into one of 10 categories — the type of power cord it is. Use the power cord 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": "Ac Power Cord",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 10 power cord 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.
A retail store specializing in electronics can use the power cord types identifier to accurately identify and categorize power cords during inventory management. This prevents mislabeling and enhances the speed of stocking shelves, ensuring customers can easily find the correct power cords for their devices.
Online marketplaces can implement the classification function to automatically categorize power cords based on type. This improves user experience by helping customers quickly filter products that are compatible with their devices, leading to increased sales and customer satisfaction.
Manufacturers can integrate the power cord types identifier into their customer support systems to assist users with compatibility questions. By allowing users to upload images of their cords, the system can quickly confirm whether a particular cord is suitable for specific devices, reducing return rates.
Service centers can use the identifier in warranty claim evaluations to verify if the correct power cord type was used with their products. This helps streamline the claims process and ensures that warranties are honored only when the proper accessories are utilized.
Environmental organizations can leverage the function to identify and categorize different types of power cords for proper recycling and disposal. This facilitates the creation of targeted e-waste initiatives and encourages consumers to recycle their unused or broken cords responsibly.
Technical support teams can utilize the identifier as part of a chatbot feature that assists customers with troubleshooting. By identifying the type of power cord, the system can provide tailored advice that aligns with the user’s equipment and its specifications, enhancing service speed and effectiveness.
Educational institutions can incorporate the power cord types identifier into hands-on learning modules about electronics and electrical safety. By classifying various cord types, students can gain practical experience, aiding their understanding of electrical devices and improving their technical literacy in a safe manner.
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 power cord 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.