A pretrained wire gauge classifier that sorts an image into one of 10 categories — what wire gauge it is. Use the wire gauge 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 10 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": "Coarse",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 10 wire gauge 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.
The wire gauge identifier can be utilized in manufacturing facilities to ensure the correct wire gauge is being used in production. By automating the inspection process, it minimizes human error and enhances product quality, ensuring that all products meet stringent specifications.
Engineers can leverage the wire gauge identifier to select appropriate wire gauges for their electrical equipment designs. By accurately identifying wire gauges from images, it can assist in preventing issues related to wire overheating or insufficient current-carrying capacity.
Retailers selling electrical components can use the wire gauge identifier to streamline inventory management. By automatically recognizing wire gauges in stock, they can quickly categorize products, thus enhancing stock accuracy and reducing overstock or understock situations.
Training programs in electrical engineering or vocational education can incorporate the wire gauge identifier as a teaching tool. This function helps students learn about wire gauges through practical application, fostering a deeper understanding of their impact on electrical systems.
Repair technicians can utilize the wire gauge identifier when diagnosing issues with electrical systems. By accurately identifying the wire gauge used in a system, they can ensure proper replacements are made, thus improving service efficiency and customer satisfaction.
Companies in the electrical industry can implement the wire gauge identifier to ensure compliance with industry standards. By validating the wire gauge used in products against regulatory requirements, businesses can avoid potential fines and enhance their reputation.
E-commerce platforms specializing in electrical components can integrate the wire gauge identifier within their systems. By allowing customers to upload images of the wires they need, the identifier can facilitate easier product selection, reducing returns and increasing customer satisfaction.
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 wire gauge 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.