# Train Green Classify High Detail

When a Green Classify tool is in Green Classify High Detail mode, the training workflow of the tool is:

1. Launch VisionPro Deep Learning.
2. Create a new workspace or import an existing one into VisionPro Deep Learning.
3. Collect images and load them into VisionPro Deep Learning.
4. Define ROI (Region of Interest) to construct Views.
   1. If a pose from a Blue Locate tool is being used to transform the orientation of the View being used as an input to the Green Classify tool, process the images (press the Scissors icon) before opening the Green Classify tool. For more details, see .

   2. If necessary, adjust the Region of Interest (ROI). Within the Display Area, right-click and select Edit ROI from the menu.

   3. After adjusting the ROI, press the Apply button and the adjusted ROI will be applied to all of the images.
   4. Press the Close button on the toolbar to continue.
5. If there is extraneous information in the image, add appropriate masks to exclude those areas of the image. Within the Display Area, right-click and select Edit Mask from the menu.

   1. From the Mask toolbar, select and edit the appropriate masks.

   2. After adding the necessary mask(s), press the Apply button and the mask will be applied to the current image.

      If you click Apply All and click Yes button on the ensuing Apply Mask dialog after adding the necessary masks, the same mask will be applied on all the images. If you click No on the dialog, the mask will not be applied and you go back to the Edit Mask window.

   3. Press the Close button on the toolbar to continue.

6. Go through all of the images and label the images with classification tags. See for the details of labeling.

   Tip: It is recommended to annotate your image files with descriptive names or numbering schemes to help when labeling the images.

7. You can use the Label Views option in the View Browser.

8. When labeling, you can either apply a tag or use regular expressions to apply the classification tag label.

9. Make sure that all of the images have been labeled with a classification tag.
10. Split the entire images into the training images and the test images. Utilize image sets to properly divide them into the training and test group. Add images to the training set.
    1. Select the images in the View Browser, and on the right-click pop-up menu click Add views to training set. To select multiple images in the View Browser, use the Shift + Left Mouse Button.
    2. Or, use to show the desired images for the training only and add them to the training set by clicking Actions for ... views → Add views to training set.
11. Prior to training, you need to set parameters in Tool Parameters. You can configure Training and Perturbation parameters or just use the default values of these. See for the details of the supported parameters.
    1. Green Classify High Detail doesn't have Sampling parameters as it doesn't use feature-based sampler but it samples from the entire pixel of each view.
    2. If you want more granular control over training or processing, turn on Expert Mode on Help menu to initialize additional parameters in Tool Parameters.
    3. If you want to change the proportion of the amount of data ceded to the validation set out of training set for the training with validation, change the Validation Set Ratio. See for the details of the training with validation.
    4. If the class distribution of training set images is highly imbalanced, for example, more than 50% of training set images were labeled with a certain tag, configure Class Weights to differentiate the weights to each class. See for the details of Class Weights.
12. Train the tool by pressing the Brain icon.
    1. You can check the training status by monitoring Validation Loss with . See for more details.
    2. If you stop training in the middle of it by pressing the Stop icon, you can stop training with saving the current tool so far trained. You can later load this tool and process images with it, but you cannot continue the training from where the last training was stopped.

13. After training, review the results. Open Database Overview panel and review the Confusion Matrix and Precision, Recall, F-Score for each class (tag) to understand the results. See for the details of interpreting results.

14. After reviewing the results, go through all of the images and see how the tool correctly or incorrectly marked the tags for each image.
    1. If the tool has correctly marked the images with the appropriate tag, right-click the image and select Accept View.
    2. If the tool has incorrectly marked the images with incorrect tags:
       1. Right-click the image again and select Clear Markings and Labels.

       2. Manually tag the image.

    3. If you encountered the scenario in (a.), you are ready to use the tool. If you encountered the scenario in (b.), you will need to retrain the tool and repeat the steps 11 - 14.