# Writing Filter Expressions

Filter expressions can include 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.-level filters where the variable refers to the entire view.

- filename ~ 'REJECT'// Returns views where filename contains 'REJECT'.
- count(feature A feature is a visually distinguishable area in an image. Features typically represent something of interest for the application (a defect, an object, a particular component of an object).) > 3// Returns views with more than three features.

Filter expressions can also include axis filters, where the individual marking Image markings are annotations produced by the VisionPro Deep Learning tools. The markings produced by a tool are the "answers" that the tool obtained when it processed a specific image. You validate the performance of the tool by comparing the markings produced by the tool with the labels that you applied to the same image. As with labels, the specific markings produced depend on the tool. or labeling Labeling is the process of annotating an image with "ground truth". Depending on the tool that you are using, labeling can take different forms. You label an image set for two reasons: to provide the information needed to train the tool and to allow you to measure and validate the performance of the trained tool against the ground truth. for each view is evaluated.

- feature [score > 0.5 ]// Returns views with a feature with score greater than 0.5.

You can combine view-level and axis-level filters.

- filename ~ 'REJECT' and feature [score > 0.5 ]// Returns views where filename contains 'REJECT' and a feature scoring greater than 0.5.

You can combine filters for multiple axes.

- feature [score > 0.5 ] and match [ score > 0.5 ]// Returns views with a feature with score greater than 0.5 and a match with a score greater than 0.5.

You can specify multiple filter conditions for an axis.

- feature[score > 0.5 and matched ]// Returns views with a feature with a score greater than 0.5 and the feature is in a matched model A specific spatial arrangement of a set of features (Blue Locate and Blue Read tools only.) During a post-processing step, the Blue Locate and Blue Read tools can fit all of the features detected in an image to the models defined for the tool. The overall pose and identity of the model is then returned..