ROI and Mask

Setting a ROI

Use an ROI (region of interest) to crop an image or a whole dataset to a rectangular area aligned with the axis.

All the ground truth annotations (EasySegment Supervised or EasyLocate) located outside the region of interest are lost.

In the API

● To define an ROI for an image:
□ Specify the ROI when you add the image to the dataset.
□ Or use EClassificationDataset.SetRegionOfInterest.

In Deep Learning Studio

● To change the ROI:
a. Select an image from the dataset.
b. Click on the ROI button (ALT+I).

c. Drag the ROI green box, or directly set the ROI origin (x and y), Width and Height.

● To set the same ROI for all the images of the dataset:
a. Set the ROI for one of the image.
b. Click on the Apply to All Images button (CTRL+SHIFT+A).

● To visualize the ROI within its parent image:
a. Click on the button.

Setting a mask

Set a mask on an image in a dataset to remove the pixels in the mask area from any computation. The mask works as a “don’t care area”.

In the API

● To define a mask for an image:
□ Specify the mask when you add the image to the dataset.
□ Or use EClassificationDataset.SetMask.

In Deep Learning Studio

● To change the mask:
a. Select an image from the dataset.
b. Click on the Mask button (ALT+M).

c. Select a drawing tool to draw the mask.

d. Draw the mask.

Click on the Open mask button to use an image to specify a mask. All the pixels of the image (such as an EROIBW8) that are over 127 are considered as part of the mask.

● To set the same mask for all the images of the dataset:
a. Specify the mask for one of the images.
b. Click on the Apply to All Images button (CTRL+SHIFT+A).