Cropping in the Portal

This article will demonstrate how to create linearization on "Original" images.

Original images are often called WetUncropped or DryUncropped,  the original images are the rawest form of an imagery uploaded to Imago, it is off this version that other Image Types are created, image types such as Wet, Dry (boundary cropping) and imagery types such as Downhole/Wet, Downhole/Dry.

If we want to use linearization on an Imagery Type we must first ensure that said Imagery Type will support it. Below an image taken from the settings menu, that demonstrates things to check if linearization is supported, this can also be used as a guide for implementing it if necessary.

If the above checks out we can continue to applying linearization on imageries.

Moving on, in the image presented below I have got a Core Tray Picture that I want to see the excess margins removed and the downhole format of the tray.



To begin cropping, open the dropdown item "Features" which is inside Core Boxes the Active Imagery menu. This will show all the features available, in most cases it will only be Linearization and Core Tray Layout. Select Linearization to continue.

Side Note:
After this if you notice the image already has linearization (like the image below), please refer to the article Edit Linearization and Cropping in the Portal and checkout how to "update actions" in the fourth paragraph and screenshot. 
Otherwise ignore this and the following image.

Moving forwards.

To make any changes in Imago you need to enable Editing on the top right-hand side.

After doing so a new tool will appear on the bottom right hand side.

Select Boundary to crop out the margins in the image.

Select row to crop out the core rows.



Refresh, wait and refresh for results.
A few moments after the backend takes up processing, your results will be viewable under Imagery Types corresponding to your configuration, in this case Wet, Dry as well as Downhole/Wet and Downhole/Dry.





A good time is 10 seconds per image, but depending on the current server workload you image could take some time to process.