Crop Anomaly Detection Tool

Name: Crop Anomaly Detection Tool
Rating: 5 (5 reviews)
Author: Free N8N

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AI/MLanomaly-detectioncropsimage-classificationqdrantvoyageai

Detects if an input image depicts an anomalous crop not present in the trained dataset.

About This Workflow

This workflow acts as a standalone tool for detecting anomalies within the agricultural crops dataset. It takes an image URL as input and leverages pre-trained embeddings and a Qdrant database to determine if the depicted crop is an anomaly compared to the known crop types. This tool is the third part of a series, building upon previous pipelines that prepared the Qdrant collection with crop data and medoid cluster centers.

Key Features

Image URL Input: Accepts any image URL to process.
Voyage.ai Embedding: Generates multimodal embeddings for the input image.
Qdrant Similarity Search: Queries a Qdrant collection to find the most similar known crop types.
Threshold-Based Anomaly Detection: Compares the image's similarity scores against pre-defined thresholds for each crop class.
Clear Anomaly Reporting: Outputs a message indicating if the image is an anomaly or resembles a specific crop.

How To Use

Input Image URL: Provide an image URL to the Execute Workflow Trigger node. This can be done by modifying the pinData section of the workflow JSON.
Workflow Execution: Run the workflow.
Receive Result: The Compare scores node will output a message indicating whether the image is an anomaly or resembles a known crop.

Apps Used

anomaly-detection

crops

image-classification

qdrant

voyageai

Workflow JSON

{
  "id": "77992610-72bb-4cc0-9f5c-0283de432cb3",
  "name": "Crop Anomaly Detection Tool",
  "nodes": 27,
  "category": "AI/ML",
  "status": "active",
  "version": "1.0.0"
}

Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.