A pretrained algae species classifier that sorts an image into one of 10 categories — what species of algae it is. Use the algae species 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 44 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": "Anabaena",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 10 algae species 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 algae species identifier can be utilized by environmental agencies to monitor water quality in lakes, rivers, and oceans. By accurately classifying the types of algae present, agencies can assess ecological health and detect harmful algal blooms that may pose risks to aquatic life and human health.
Fish and shellfish farms can employ the algae species identifier to optimize their feeding practices. By identifying beneficial algae species, farmers can enhance growth rates and health of their stock while avoiding harmful blooms that could lead to significant losses.
Municipalities can use the algae species classification function to ensure the safety of recreational waters like beaches and swimming pools. By identifying dangerous species, officials can issue timely warnings to the public, protecting community health.
Academic institutions and research organizations can leverage the algae species identifier to facilitate studies on algae biodiversity. This data aids in understanding ecosystem dynamics and informs conservation efforts by identifying species of interest for research.
The identifier can assist climate scientists in tracking changes in algal communities over time as indicators of climate change. By analyzing shifts in species distribution, researchers can gather valuable insights into broader environmental impacts and develop adaptive management strategies.
Environmental consultants can use the algae species identifier to design bioremediation interventions that target specific pollutants in water bodies. By selecting the right species that naturally absorb toxins, they can effectively restore water quality in affected areas.
Entrepreneurs in the algae industry can utilize this function to identify and select high-value algae species for cultivation. By ensuring they grow the most desirable species, businesses can optimize their production for food, biofuels, or cosmetics, thus increasing profitability and sustainability.
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 algae species 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.