ManualTrigger Automate

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.

How users can customize and adapt this workflow:

- Change the Image URL: Update the URL in the Get Test Image node to process different images.
- Modify Detection Prompt: Alter the text prompt in the Gemini 2.0 Object Detection node to detect different objects based on user needs.
- Adjust Bounding Box Color: Change the color parameter in the Draw Bounding Boxes node to customize the appearance of the annotations.
- Expand or Reduce Object Detection: Add or remove operations in the drawing step to accommodate the number of objects detected, allowing for flexibility based on the image content.
- Integrate Additional Nodes: Users can add more nodes for further processing, such as saving the edited image or sending notifications upon completion.