This n8n workflow demonstrates how to automate indexing of images to build an object-based image search.
By using 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 Cloudflare'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 than 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 Cloudflare 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.
