# Markings Returned by Unsupervised Type Red Analyze

A trained Red Analyze tool returns an anomaly, a heat map that outlines possible defects, and a colored border around the 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..

- Green border: The tool marks the view as defect-free.
- Red border: The tool marks the view as having a defect.

The anomaly score each view receives is displayed in the bottom left-corner of the view. The small band in the top-right corner shows the label you assigned to the view.

Defect-Free Image | Image with Defect

## Region List

The Red Analyze tool also returns two tables displayed on the bottom of image display area that show the information of each defect region.

- The first table shows the labeled defect region (the defect region you labeled for 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.)

- The second table shows the marked defect region (the predicted defect region as the result of processing).

Each row in a table represents the information of each defect region. For each table, you can click a row to highlight its information both in the table and in the image display area.

Column | Description
--- | ---
Score | The highest defect probability among the defect probabilities of each pixel in the defect region, as the result of processing. For the labels table, this represents the highest defect probability for a region that was labeled as a defect region. For the markings table, this represents the highest defect probability for a region that was predicted as a defect region.
Position | The x, y coordinate of the center of the defect region.
Area | The number of pixels in the defect region.
Coverage | The overlapping ratio between the labeled defect region and the predicted (marked) defect region.