Automated Image Processing with Object Detection

Who should use this workflow:

• Developers looking to integrate advanced object detection capabilities into their applications.
• Data Scientists interested in visualizing and analyzing images with bounding box annotations.
• Content Creators who need to identify and highlight specific objects in images for presentations or reports.
• Researchers studying machine learning and AI applications in image processing.
• Marketers aiming to enhance their visual content with AI-driven insights.

What problem does this workflow solve:

This workflow addresses the challenge of automatically detecting and annotating objects within images. By leveraging the Gemini 2.0 Object Detection API, users can easily identify specific items (like rabbits in this case) and visualize them with bounding boxes. It eliminates the need for manual annotation and speeds up the process of image analysis, making it efficient and scalable.

Detailed explanation of the workflow process:

1. Manual Trigger: The workflow begins with a manual trigger, allowing users to start the process when ready.
2. Get Test Image: An image is downloaded from a specified URL to be processed.
3. Get Image Info: The dimensions (width and height) of the downloaded image are retrieved to ensure accurate scaling of detected objects.
4. Gemini 2.0 Object Detection: The image is sent to the Gemini 2.0 API with a prompt to detect specific objects (e.g., rabbits). The API returns bounding box coordinates for the detected objects.
5. Scale Normalized Coordinates: The bounding box coordinates are scaled to fit the original image dimensions, ensuring accurate placement of the bounding boxes.
6. Draw Bounding Boxes: Finally, the bounding boxes are drawn on the original image using the Edit Image node, visually marking the detected objects.