Identify vision types
using AI
Below is a free classifier to identify vision types. Just input your text, and our AI will predict the type of vision it represents - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("vision-types", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/vision-types/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_text_here"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_text_here"}' \
https://www.nyckel.com/v1/functions/vision-types/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict the type of vision it represents.
This pretrained text model uses a Nyckel-created dataset and has 23 labels, including Aniseikonia, Astigmatism, Blindness, Cataract Vision, Color Blindness, Diabetic Retinopathy, Double Vision, Farsighted Vision, Hemianopia and Hyperopia.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the type of vision it represents).
Whether you're just curious or building vision types detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify vision types at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Automated Document Classification: This function can categorize documents based on predefined vision types, streamlining the organization and retrieval of information in digital libraries. By automating this process, businesses can significantly reduce manual sorting and improve workflow efficiency.
- Content Moderation: The vision types identifier can be used in social media platforms to classify and flag inappropriate visual content in user-generated images. This enhances community guidelines enforcement and ensures a safer online environment for users.
- E-Commerce Image Tagging: In online retail, this function can automatically classify product images into specific vision types, aiding in accurate tagging and categorization. This helps improve searchability and enhances user experience by guiding customers to relevant products effectively.
- Medical Image Analysis: In healthcare, this identifier can be applied to categorize medical imaging data, such as X-rays or MRIs, into standard vision types. This could assist radiologists in prioritizing cases and enhance diagnostic efficiency by providing structured classifications of medical images.
- Advertising Optimization: Marketing teams can utilize the vision types identifier to categorize visual assets for targeted advertising campaigns. By analyzing the performance of different image types, businesses can optimize their ad strategies and improve engagement rates.
- Social Media Insights: Brands can use this function to analyze visual content shared on social media platforms and categorize it based on vision types. This can help in understanding audience preferences and trends, enabling more effective content creation and marketing strategies.
- Educational Content Organization: In e-learning platforms, this identifier can classify educational videos and images according to different vision types. It allows for a more organized content structure, improving navigation and accessibility for learners seeking specific visual learning materials.