# Deep Learning GUI and Third Party Application

The DLL supports integrated 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. through API only under a certain license (VisionPro Deep Learning Licenses), but you can use the VisionPro Deep Learning GUI to train a new recipe.

This is done in the following three, separate steps:

1. Acquire images.
2. Transmit them to the VisionPro Deep Learning GUI, either through the API, using the add to database method, or by manually dragging and dropping them into the VisionPro Deep Learning GUI.
3. Export the runtime workspace A runtime workspace is a configuration file that does not contain images or databases, containing only streams and tools, which makes it a smaller version of a full Workspace. This configuration file can be loaded in the library in order to perform some analysis. and load it inside the DLL. This can be done manually or using get workspace from server method in the DLL.

Your vision application is responsible for the following:

- Acquire images.
- Transmit the images to the VisionPro Deep Learning GUI through the DLL using either the add to database method, or writing them to disk.
- Load the new runtime workspace when training is completed.

To train the system, you do the following:

- Retrieve the images from hard drive and drops them into the VisionPro Deep Learning GUI.
- Train the tools.
- Export a runtime workspace.