A pretrained mushroom species classifier that sorts an image into one of 10 categories — what mushroom species it is. Use the mushroom 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 21 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": "Agaricus Bisporus",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 10 mushroom 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.
A mobile application for foragers that uses the mushroom species identifier to verify the edibility of wild mushrooms. Users can take photos of mushrooms they encounter, and the app will classify the species, helping to prevent the consumption of poisonous varieties.
A tool for farmers and agricultural researchers to monitor the presence of specific mushroom species that may affect crops. By identifying harmful fungi early through image classification, farmers can take preventive measures to protect their yields.
Researchers studying biodiversity can utilize the mushroom species identifier to catalog and analyze mushroom populations in different ecosystems. This can assist in understanding ecological dynamics, species distribution, and changes over time due to factors like climate change.
An interactive educational platform for students and enthusiasts to learn about various mushroom species. Users can upload images to identify species and access detailed information, fostering a deeper understanding of mycology.
A service for mushroom growers that offers insights into the best growing conditions for various mushroom species. By identifying mushrooms based on images, the system can suggest optimal substrates and climates for cultivation.
A tool for wildlife conservationists to monitor mushroom species that might affect local fauna. By understanding which mushrooms are prevalent, conservationists can better manage habitats and understand food sources for various animal species.
A cooking application that allows users to identify mushrooms before adding them to dishes. Users can photograph mushrooms they plan to cook with, ensuring they select the right species, which enhances their culinary experience and avoids health risks.
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 mushroom 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.