For the complete documentation index, see llms.txt. This page is also available as Markdown.

Detection Offset

Add padding around detected regions.

About this block

The Detection Offset block lets you add a padding around regions detected by an object detection model or segmentation model.

This block is useful if you want to add space around a detection. You may want to do this if you want to see some background around the detected regions in an image.

This block works with:

  • Object detection models

  • Segmentation models

The Detection Offset block.

What you can send into this block

To use this block, you need:

  1. An input image, video frame, or a cropped region in your image, and;

  2. Predictions from an Object Detection or Segmentation model.

What this block returns

The Detection Offset block returns a version of the xyxy coordinates returned by a detection model. These coordinates have padding (space).

These coordinates can then be passed into any block that supports detections (i.e. an OCR Model, or a Bounding Box Visualization).

Here is an example showing raw detections displayed with a Bounding Box Visualization (left) and detections to which an offset (padding) has been applied:

The defect in the image is magnified.

For reference, here is the input image:

In the result from the block, the detected region is made bigger.

Use cases

This block is useful if you want to see the results from a model on an image. This is common during testing.

Because visualizing predictions adds a small amount of overhead to running a Workflow, we only recommend adding a Visualization in production if you need to see the location of results from your model.

Last updated

Was this helpful?