Pretrained computer vision classifier
Identify galaxies with one API call.
A pretrained galaxies classifier that sorts an image into one of 10 categories — what type of galaxy it is. Use the galaxies API immediately, no training required, then adapt it to your own data when you need more.
Try the galaxies classifier
Drop in a photo and get the prediction back. No signup, no setup.
What this galaxies classifier recognizes
A sample of the 41 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.
Call the galaxies API
Get your own copy of this classifier behind your own endpoint — callable from any HTTP client:
curl -X POST "https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke" \
-H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"data": "https://example.com/photo.jpg"}'import requests
response = requests.post(
"https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke",
headers={"Authorization": "Bearer YOUR_ACCESS_TOKEN"},
json={"data": "https://example.com/photo.jpg"},
)
print(response.json())const response = await fetch("https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_ACCESS_TOKEN",
"Content-Type": "application/json",
},
body: JSON.stringify({ data: "https://example.com/photo.jpg" }),
});
console.log(await response.json());$ch = curl_init();
curl_setopt($ch, CURLOPT_URL, 'https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke');
curl_setopt($ch, CURLOPT_RETURNTRANSFER, 1);
curl_setopt($ch, CURLOPT_POST, 1);
curl_setopt($ch, CURLOPT_POSTFIELDS, '{"data": "https://example.com/photo.jpg"}');
$headers = array();
$headers[] = 'Authorization: Bearer YOUR_ACCESS_TOKEN';
$headers[] = 'Content-Type: application/json';
curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
$result = curl_exec($ch);
curl_close($ch);
echo $result;Example response
{
"labelName": "Andromeda",
"labelId": "label_...",
"confidence": 0.92
}Under the hood
Trained on a Nyckel-curated dataset covering 10 galaxies 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.
Where teams use galaxies classification
Astronomy Research Enhancement
This function can aid astronomers in classifying and cataloging galaxies based on their shapes and features. By automating the identification process, researchers can save time and focus on deeper analysis of cosmic phenomena.
Educational Tools for Science Curriculum
Schools and universities can integrate this image classification function into their curricula to teach students about galaxy types and morphology. Interactive educational programs can enhance engagement and understanding of astronomy topics.
Automated Space Telescope Data Analysis
Space missions often generate vast amounts of imagery from telescopes. This function can process and classify these images in real-time, allowing scientists to prioritize their observations and efficiently analyze new findings.
Sky-monitoring Apps for Amateur Astronomers
Mobile applications for stargazers can utilize this function to help users identify galaxies while observing the night sky. It would enhance the amateur astronomy experience and foster a greater appreciation for the universe.
AI-driven Astronomy Data Marketplaces
Platforms that aggregate astronomical data can implement this image classifier to provide users with curated datasets of galaxy images. This service can generate revenue from educational institutions and research organizations looking for quality data.
Enhanced Astronomy Visualization Software
This function can be embedded into astronomy visualization tools to offer users detailed classifications of galaxies alongside visualization features. Users can explore galaxy distribution and types more interactively, making complex data more accessible.
Public Engagement in Astronomy
Planetariums and science centers can use this function in interactive exhibits to engage the public. By allowing visitors to classify galaxy images, these organizations can inspire curiosity and interest in astronomy and science as a whole.
Common questions
What's the difference between a zero-shot and a Nyckel-trained classifier?
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.
How do I know whether this will work for my application?
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.
What happens when it makes a mistake?
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.
Do I need training data to get started?
No. This galaxies 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.
What does it cost to try?
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.
Related classifiers
Ready to classify galaxies at scale?
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.