Crop Anomaly Detection Tool
detail.loadingPreview
Detects if an input image depicts an anomalous crop compared to a known dataset.
🚀Ready to Deploy This Workflow?
About This Workflow
Overview
This tool leverages AI embeddings and a vector database to identify if an input crop image is an anomaly within a predefined dataset. It takes an image URL, generates its embedding, queries a Qdrant collection, and compares the similarity scores against crop-specific thresholds to determine anomaly status.
Key Features
- Accepts image URLs as input.
- Utilizes Voyage.ai embeddings for feature extraction.
- Queries Qdrant vector database for similarity search.
- Compares similarity scores against defined thresholds for each crop.
- Outputs a message indicating whether the crop is anomalous or similar to a known crop.
How To Use
- Import the workflow into n8n.
- Configure the
Voyage APIcredential with your API key. - Configure the
QdrantApicredential with your Qdrant connection details. - Set environment variables:
API_BASE_URLfor the Voyage API andBASE_URLfor your Qdrant instance. - The workflow expects an image URL as input, typically from an upstream node like an HTTP Request trigger or a manual trigger.
- Execute the workflow. The output will be a JSON object containing a
resultfield with a message indicating anomaly status.
Apps Used
Workflow JSON
{
"id": "168949f8-1296-4b52-9191-9a3b6f1436d2",
"name": "Crop Anomaly Detection Tool",
"nodes": 0,
"category": "AI/ML Automation",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 168949f8-1296...
About the Author
SaaS_Connector
Integration Guru
Connecting CRM, Notion, and Slack to automate your life.
Statistics
Verification Info
Related Workflows
Discover more workflows you might like
GROQ LLAVA V1.5 7B: Image Description with Telegram
Describe images using the GROQ LLAVA V1.5 7B model via Telegram.
Automated Ticket Urgency Classification with RAG and AI
This workflow leverages a RAG Agent, Pinecone, and AI models to automatically classify ticket urgency. It processes incoming tickets via a Webhook Trigger, splits text, generates embeddings, and stores them in Pinecone for intelligent classification and logging.
Generate Daily Content Ideas with Webhook, Supabase, and RAG Agent
Automate content idea generation by triggering a webhook that splits text, generates embeddings, and stores them in Supabase. A RAG agent then crafts unique content ideas using this data, logging results to Google Sheets.
AI-Powered PostgreSQL Data Agent with Conversational Interface
This n8n workflow empowers you to build an intelligent, conversational agent for your PostgreSQL database. Interact with your data using natural language, perform CRUD operations, explore schemas, and generate dynamic visualizations, streamlining data management and access for any user.
AI-Powered YouTube Video Metadata Automation
Effortlessly optimize your YouTube videos for search and engagement. This workflow automates the generation of SEO-friendly titles, descriptions, tags, and hashtags using AI, directly updating your YouTube content based on video transcripts and focus keywords.
Automated Multi-Platform Social Media Publisher
Streamline your social media content creation and publishing with this n8n workflow. Simply fill out a web form with your caption, media (image or video), and target platforms, and let n8n automate the posting process across multiple social networks.