v2022.1 / v2022.1.5 (March 1, 2022)
Feature walk-through: Improved interaction between your classification/quantification models and the image data
Modeling and data analysis
Improved the interaction between models and image data, making easier to add new training data, retrain models and view the results on your image
Apply models on images directly in the Record Study table
Include, exclude or balance new training samples and then retrain models
Update categories and properties data from model prediction results
ONNX models inference performance improvements
Constrained spectral unmixing with new options for Scatter correction parameter "None" and method for "Sum To One Least Squares" Unmixing (descriptor) Unmixing (segmentation)
Better naming for the different machine learning algorithms
More statistics in the classification confusion matrix (f-score, precision and recall)
Prediction summary (Observed vs Predicted) for quantification analysis through right-click in Table
Pre-treatment option to use SNV in the Explore tab
Use multiple spectral ranges for SAM (Spectral Angle Mapper) Spectral angle mapper (SAM) guide
Balance model with included train data or all train data
Image segmentation
Deep Learning Image Segmentation (Faster R-CNN and Yolo4/5) applied to pseudo RGB or model predicted image ONNX image segmentation
Image segmentation using YOLOv5
K-Means clustering as method for selecting representative spectrum Representative spectrum
Add samples to Manual segmentation through right-click in Table
Object filter for segmentation (ex. object shape)
Summary table showing pixel overlap of multiple segmentations
Setting for Max number of objects in Deep Learning Image Segmentation
Visualization
Pixels on an object that are excluded in the segmentation (e.g. holes showing the background) are also excluded in the visualizations (Pixel Explore, Table thumbnail)
Merge all samples in segmentation now show all merged samples as one object in the preview image and in Table
Change RGB bands by right clicking on image
Test scan show % saturated bands
Selected samples in Pixel Explore can be highlighted in Table and vice versa
Option for Quantification model to predict and show value for individual pixels or only object average
Change direction of real time visualization (horizontal or vertical)
Option to show all or individual segmentation in Table if there are multiple segmentations on the same level
Select multiple samples in preview image by holding down the shift key and making rectangular selection of the area with the mouse
Yellow color for added class in Classification summary (confusion matrix)
Workflow
Disable nodes in Analyse Tree that should not be used
Export and import Breeze models into your study
White and dark reference descriptor (signal intensity value)
Metadata descriptor for each image (ex. image length and resolution)
Delete workflow command in Breeze Runtime
Access Study settings in Analyse Tree on Measurement node
Link multiple segmentations to one output
Data acquisition
Stray light correction option in Settings
Saturation descriptor for maximum value and percent saturated band per pixel
Explore pixel spectra on images in Test Scan
Indication that new white or dark reference will be taken when recording using reference cache
Set integration time in Record wizard
General ease-of-use improvements
Duplicate Study with option to include all measurements and data
Move measurement to another Group in the same Study
Improved help sections for Segmentations , Descriptors and Actions
New tutorial and data included: Classification of plastics Plastic Classification