KNN Image Classifier with Qdrant Vector DB for AI Agents

This workflow classifies input images using K-Nearest Neighbors (KNN) on datasets stored in Qdrant vector database. Ideal for production AI agents handling big data image analysis.

This n8n workflow serves as a powerful KNN classifier tool, leveraging Qdrant vector database to perform image classification on any input image against pre-uploaded datasets like agricultural crops or landuse scenes from Kaggle. It is part of a webinar series on building production-ready AI agents, following data upload and setup workflows. The pipeline embeds the input image, queries Qdrant for the k-nearest neighbors, and determines the classification based on majority voting or distance-weig
Platform
n8n
Category
AI & Machine Learning
Price
$24.99
Creator
Matt Buds

How to import this workflow into n8n

  1. 1Purchase or download the workflow to get the n8n workflow JSON file.
  2. 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
  3. 3Open each node marked with a credential warning and connect your own accounts and API keys.
  4. 4Run the workflow once manually to verify the data flow, then toggle it to Active.

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