Crop Visualization
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The Crop Visualization block crops detected regions from an image, makes them bigger, then adds the regions back above the detected region.
This block is useful if you want to highlight detections in an image.
This block works with:
Object detection models
Segmentation models
To use this block, you need:
An input image or video frame, and;
Predictions from an Object Detection or Segmentation model.
The Crop Visualization block returns an image with a circle drawn around detected regions in an image.
Here is an example output from this block:
For reference, here is the input image:
In the result from the block, the detected region is made bigger.
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.
This block does not add class labels from your detection or segmentation model by default. If you want to see the classes that correspond with each crop, you will need to add a .
