User Interface

After starting the program, the standard user interface opens (Fig. 10).

The elements of the user interface are described in Table 1.

LumiScan Training Framework user interface with options to select a configuration file, start training, testing, and inference, convert a model, and cancel the current process
Figure 1. Fig. 10: LumiScan Training Framework User Interface
Table 1. Table 1: LumiScan Training Framework User Interface Description
No. Description

1

Select Config File/Browse is used to select the configuration file.

2

Process Status displays the current status of the process.
Possible messages include:

  • Waiting for configuration file! The program is waiting for a configuration file to be selected.

  • Testing Network! Appears after clicking Start Testing and indicates that an existing network is being tested with a test data set.

  • Waiting for deployment! Appears after training while the network is being prepared for conversion and export to an ONNX file.

  • Finished cleanup indicates that the process has finished.

  • Time Remaining displays the estimated remaining process time.

  • Latest test scores displays a metric for evaluating trained networks. The value should be used primarily to compare networks tested with the same data set rather than as an absolute measure of performance.

3

Start Training starts the training process using the selected configuration.

4

Start Testing tests the network using the test data set specified in the configuration. The results are stored in the Export folder.

5

Start Inference opens a dialog for selecting a folder containing images. The trained network is then applied to these images, and the prediction results are saved in the predictions folder within the export directory.

6

Model Conversion opens a dialog for converting a trained ONNX model to a Hailo model. See Model Conversion: ONNX to Hailo.
This function requires the Hailo PlugIn.

7

Cancel interrupts an ongoing training, testing, or inference process.

For successful training, all relevant parameters must be configured in the JSON settings beforehand. An example configuration is provided in the next section.