# Label in Blue Read

The Blue Read tool is a pre-trained tool to automatically recognize characters and strings, so 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. is not required to use the tool in most cases. However, labeling is recommended for application validation Validation refers to a process during the training of a tool that helps to evaluate performance. Validation is like a mock exam that the tool takes during the training phase, separate from the final test. For example, validation helps you to recognize overfitting and avoid wasting time when training a tool. If you recognize that the tool is overfitting, you can stop the training early. and incremental 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.. Since the Blue Read tool does not return detailed information about character positions, it does not require precise positional labeling. Instead, the labeling is simply the approximate size of the character, and its identity. Supported characters can be any single UTF-8 character.

1 | Feature Size
2 | Feature Identity

The images in your image set are either labeled or unlabeled. Labeled images are indicated by the presence of green graphics, either features or strings, on the display. In order to determine the performance of the Blue Read tool on your images, you need to be able to compare the characters identified by the tool with the actual character values in the image. The process of Labeling allows you to specify the positions and values of the characters in your images. Once your image set is partially or completely labeled, you can do two important things:

- You can compute statistical measures of the performance of the tool on your images, including Recall, Confusion, Precision and F-Score.
- You can perform incremental training of your tool. (You can improve your tool’s performance by giving it examples of how specific characters appear in your images.)

An extremely important consideration when labeling images is that if an image is labeled, all of the characters in the image should be labeled. If only some characters are labeled, this will invalidate the statistical measurements (since the tool will be finding “spurious” or “unexpected” characters), and it will also cause any incremental training to reduce, rather than improve, the accuracy of the tool (because any characters in an image that are unlabeled are assumed by the tool to not be characters).

### Convert Features to Labels

The simplest method for labeling an image is to start with the features in the image that the tool has found. To convert all of the found features in an image into labels, simply right-click on the image and select Accept View. All of the yellow found features are replaced with green labels:

Green labels are similar to yellow features in several ways:

- You can click on them to select them.
- You can create a 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. from them (select one or more, then right-click on the image and select Create Model).

But green labels have some important differences from features:

- You can move them. If a found 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).’s location is incorrect, you can reposition it as part of labeling.
- You can change the feature’s value. If a found yellow feature has the wrong character value (a ‘B’ for an ‘8’, for example), you can convert the feature to a label, select it, and simply type the correct value. Once the label has been corrected, the difference between the feature that the tool found and the label that you have created will be reflected in the tool’s performance statistics. In addition, when you incrementally train the tool, the correct value will be incorporated in the trained tool.

### Direct Labeling

In addition to converting features to labels, you can also create labels by simply clicking on the image and typing the label value. If you click on the image and create a feature, but you do not specify the character value, the tool considers that an “Empty Feature” and will not allow you to train.

If you click on an unlabeled image that contains found features, the tool asks you what it should do with the found features in the image:

If you click Yes, the yellow found features are converted into green labels, and you can adjust their positions and change their character values as needed. If you click No, the found features are not converted. The found features are now shown in orange – this indicates that they should probably be converted to features.

## Feature Label Graphics

This is how the tool indicates labeled characters that have not been matched with any model. Labeled characters are displayed in the color green.

## Feature Parameters for Blue Read

The two Features parameters, Oriented and Scaled, are only available for the Blue Locate tool and the Blue Read tool. For the Blue Read tool, they are enabled by default, and cannot be disabled. In addition the Blue Read tool is set to use the Non-uniform option for the Scaled parameter.