Community Contributed Image Object Detection
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Detects and crops objects from an image using Cloudflare Workers AI and indexes them in Elasticsearch.
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About This Workflow
Overview
This workflow demonstrates how to leverage n8n, Cloudflare Workers AI (Detr-Resnet-50 model), and Elasticsearch to perform object detection within an image. It takes a source image, identifies objects and their bounding boxes, crops each detected object into a separate image, uploads these cropped images to Cloudinary, and finally indexes metadata about the original image and the detected objects in Elasticsearch for searchable image data.
Key Features
- Utilizes Cloudflare Workers AI for efficient object detection.
- Crops detected objects from the source image using n8n's image editing capabilities.
- Uploads cropped images to Cloudinary for hosting.
- Indexes image metadata and object details in Elasticsearch for advanced search functionality.
- Provides a template for building community-contributed image analysis workflows.
How To Use
- Set Environment Variables: Configure your
BASE_URL,WEBHOOK_URL, andAPI_BASE_URLin your n8n environment settings. - Configure Credentials: Set up your Cloudflare API, Cloudinary API, and Elasticsearch API credentials in n8n.
- Import Workflow: Import this JSON into your n8n instance.
- Manual Trigger: Click the "Test workflow" button on the manual trigger node to initiate the process.
- Observe Results: Check your Cloudinary account for uploaded images and your Elasticsearch index for the created documents.
Apps Used
Workflow JSON
{
"id": "46da35c6-cef0-450b-be7d-069ec84b10b9",
"name": "Community Contributed Image Object Detection",
"nodes": 0,
"category": "Image Processing",
"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: 46da35c6-cef0...
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