To correct markings after training Training is the process that your tool, which is a neural network, is learning about the features (pixels) based on the labels you made. For example, a tool will learn the defect/normal pixels in each image based on the defect/normal labels you drew. The goal of the tool Training is learning enough to give the correct inspection results of whether an unseen image is defective or not. The key to training is to ensure that you include all possible variations within your training set, and that your images are accurately labeled. Training times vary by the application, tool setup and the GPU in the PC being used to train the network.:

1. Identify a view A view of an image is a region of pixels in an image. Tool processing is limited to the pixels within the view. You can manually specify a view, or you can use the results of an upstream tool to generate a view. that does not appear to be properly marked.

2. Make sure that the image is improperly marked. In the above image, the overlay markings have been hidden (by pressing Alt+Arrow key), indicating that the defect area was improperly drawn.
3. Accept the view in order to retain the area already marked as a bad region.

4. Open the Edit Regions toolbar.

5. Properly draw over the defect region.

6. Optionally, if the tool has difficulty with this particular image, add the image to the list of images that are always used when training.