Anomaly detection tool for crop images in Qdrant

• Detect anomalies in crop images for agricultural monitoring.
• Identify new crop types that are not present in the existing dataset.
• Enhance crop management by providing insights into crop health.

Receive image URL input through a trigger. Generate embeddings for the image using Voyage's embedding model. Query Qdrant to compare the image against known crop classes. Evaluate similarity scores to determine if the image is anomalous.

1. 1
   Import the workflow template into your n8n instance.
2. 2
   Configure the necessary credentials for Qdrant and Voyage.
3. 3
   Set up the Execute Workflow Trigger to receive image URLs.
4. 4
   Test the workflow with sample image URLs to ensure proper functionality.