# Use the Parameter Search Utility

The Parameter Search utility is used to determine which set of VisionPro Deep Learning Tool Parameters will give you the best results. The utility runs through both the training and processing parameter combinations for the tool.

To use this utility, you have to go through the 3 steps below.

1. Setup workspace, stream, and tool for search.

   1. Select the path for loading workspaces

   2. Select a workspace among the loaded workspaces

   3. Select a stream in the selected workspace

   4. Select a tool to be used in Parameter Search in that stream.

2. Select a set of tool parameters to be searched and start searching .

   - Select a set of parameters and provide the value range of them to be searched through, and start searching.

3. Examine the results.

   - After the searching is done, check Database Overview results for each combination of parameters, investigate the contour graphs that displays the relationships between the selected parameters in terms of the tool performance metrics, and decides which set is the best combination of the parameters for the current tool.

Parameter Search Utility consists of 4 main components: Home, Search, Results, and Graphs. These are what you can do with these 4 main pages.

- Home: Load the workspace, stream, and the tool to be tested against many training/processing parameter sets.

- Search: Setup the combination of parameter set, their value ranges, and other options including the number of search trials, and optimized GPU memory.

- Results: View the test results (F-score, AUC, and others) with the Database Overviews for the tool. The types of result metrics are different by tool type.

- Graphs: View the test results with a table that describes the result statistics for multiple trials, and with contour graphs that explain the relationships between each tested parameter and how it affects the test results.

Home

Search

Results

Graphs

Note:

- The length of the test is dependent upon the GPU (and number of GPUs), the number of parameters, the number of parameter settings per parameter, the number of images, and the number of test runs. Each additional set of parameters and values will cause the execution time of the experiment to run exponentially longer.
- If you have multiple GPUs, along with multiple test runs, the runs will be queued in parallel, and the utility will start the run on the next available GPU. For example, if you have a two GPU system, and a two run experiment, each run will happen on a separate GPU, thus improving the performance of the test execution.
- The Parameter Search application requires the use of the Standard or Advanced Cognex VisionPro Deep Learning license.