KNN Land Use Classifier
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Classifies land use types using a KNN model with image embeddings.
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About This Workflow
Overview
This workflow takes an image URL, embeds it using a multimodal model, and then queries a Qdrant database to find the nearest neighbors (KNN) for land use classification. It then performs a majority vote on the results to determine the most likely land use type. The workflow is designed to be production-ready and optimized.
Key Features
- Embeds images using a multimodal AI model.
- Queries a vector database (Qdrant) for similar embeddings.
- Implements a K-Nearest Neighbors (KNN) approach.
- Determines land use classification through majority vote.
- Handles potential ties in classification results.
- Allows for dynamic adjustment of the KNN limit.
How To Use
- Set up credentials: Configure
Voyage APIandQdrantApicredentials. - Configure environment variables: Ensure
API_BASE_URLandBASE_URLare set for API endpoints. - Trigger the workflow: Provide an image URL to the workflow's entry point.
- Monitor results: The workflow will output the predicted land use class.
Apps Used
Workflow JSON
{
"id": "24bce8ed-c031-436c-b653-efd57ad5ab4b",
"name": "KNN Land Use Classifier",
"nodes": 0,
"category": "AI & Machine Learning",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 24bce8ed-c031...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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