KNN Image Classifier for Land Types Using Voyage AI and Qdrant
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Classify land types from an image URL using Voyage AI's multimodal embeddings and Qdrant for KNN search. This workflow employs majority voting to determine the most likely land classification.
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About This Workflow
Overview
This n8n workflow is designed to classify the type of land depicted in an image. It leverages advanced AI and vector database technologies to achieve this. The process begins by taking an image URL, converting it into an embedding using Voyage AI's multimodal embedding API. This embedding is then used to query a Qdrant vector database, searching for the K nearest neighbors (KNN) within a collection of land-use data. The 'Majority Vote' node analyzes the labels of these neighbors to determine the most probable land type. The workflow also includes logic to handle ties in the majority vote by increasing the KNN search limit and re-querying.
Key Features
- Classifies land types from image URLs.
- Utilizes Voyage AI for multimodal image embeddings.
- Employs Qdrant as a vector database for efficient KNN search.
- Implements majority voting for classification.
- Includes logic for tie-breaking in classification results.
How To Use
- Trigger the workflow with an image URL via the
Execute Workflow Triggernode. - The
Embed imagenode will generate an embedding for the image using Voyage AI. - The
Query Qdrantnode will use this embedding to find the nearest neighbors in the Qdrant database. - The
Majority Votenode will determine the most frequent land type among the neighbors. - If a tie occurs, the
Check tienode will trigger a re-query with an increased limitKNN to resolve the ambiguity. TheReturn classnode will ultimately output the classified land type.
Apps Used
Workflow JSON
{
"id": "e15cabdd-a4b8-47ac-8707-f4e300040984",
"name": "KNN Image Classifier for Land Types Using Voyage AI and Qdrant",
"nodes": 0,
"category": "AI Research, RAG, and Data Analysis",
"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: e15cabdd-a4b8...
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Crypto_Watcher
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