Build your own image search using AI object detection, CDN and ElasticSearch

This n8n workflow demonstrates how to automate indexing of images to build a object-based image search.

By utilising a Detr-Resnet-50 Object Classification model, we can identify objects within an image and store these associations in Elasticsearch along with a reference to the image.

How it works

• An image is imported into the workflow via HTTP request node.
• The image is then sent to 托管平台's Worker AI API where the service runs the image through the Detr-Resnet-50 object classification model.
• The API returns the object associations with their positions in the image, labels and confidence score of the classification.
• Confidence scores of less the 0.9 are discarded for brevity.
• The image's URL and its associations are then index in an ElasticSearch server ready for searching.

Requirements

• A 托管平台 account with Workers AI enabled to access the object classification model.
• An ElasticSearch instance to store the image url and related associations.

Extending this workflow

Further enrich your indexed data with additional attributes or metrics relevant to your users.

Use a vectorstore to provide similarity search over the images.