Who is this workflow for? This n8n workflow template leverages Gemini 2.0’s advanced Bounding Box detection to enable prompt-based object detection within your automated processes. It allows you to define specific criteria for identifying and locating objects in images, enhancing tasks such as contextual image searches and automated image annotations..

What does this workflow do?

  • Image Download: The workflow begins with an HTTP Request node that downloads the target image.
  • Extract Image Dimensions: An “Edit Image” node retrieves the image’s width and height, which are essential for accurate bounding box scaling.
  • Object Detection: The downloaded image is sent to the Gemini 2.0 API via the AI Model node. A specific prompt, such as identifying all bunnies, instructs the AI to detect relevant objects and return their bounding box coordinates.
  • Rescale Coordinates: The returned coordinates are adjusted based on the original image dimensions to ensure accurate alignment.
  • Draw Bounding Boxes: Using the “Edit Image” node, the workflow overlays the bounding boxes onto the original image, providing a visual representation of the detected objects.
  • Output Results: The final annotated image can be used for verification, reporting, or further automated processes within your workflow.

🤖 Why Use This Automation Workflow?

  • Precision Object Detection: Utilize Gemini 2.0’s capabilities to accurately identify and locate objects based on custom prompts.
  • Seamless Integration: Easily incorporate advanced image analysis into your existing n8n workflows without extensive coding.
  • Enhanced Automation: Automate complex image processing tasks, saving time and reducing manual effort.

👨‍💻 Who is This Workflow For?

This workflow is ideal for developers, data analysts, and businesses that require automated image processing and object detection. It is particularly useful for those looking to integrate AI-driven image analysis into their workflows without deep expertise in machine learning.

🎯 Use Cases

  1. Contextual Image Search: Enable searches based on specific objects or scenarios within images, such as finding all images containing adults with children.
  2. Automated Quality Control: Detect and flag items that do not meet predefined criteria, like cars parked out of designated spaces.
  3. Image Annotation: Automatically draw bounding boxes around identified objects to visualize detection results for reports or further analysis.

TL;DR

This n8n workflow template harnesses Gemini 2.0’s Bounding Box detection to provide a powerful tool for prompt-based object detection in images. By automating the identification and annotation of specific objects, it enhances image analysis capabilities and integrates seamlessly into diverse automated workflows.

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