...
| Widget Connector | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
|
Training
Annotations
First, annotate defects in the image - the size of the annotation should be just enough to fit the whole defect without too much excess background (especially when the background is very variable).
...
To speed up the annotation process, there is a possibility to train a model on a small amount number of annotations first and then use the predictions of this model to quickly make more annotations for further training.
If we select a trained model from a list of models and then go to the training tab, we can see predictions of that selected model on our images. They are marked with red rectangles with percentages.
...
Clicking Set annotations will automatically set annotations for all the detected rectangles in the selected image.
...
It is possible to edit these annotations afterwards afterward if we want to make them more precise. We can also add more annotations, delete them if some of them are wrong, or change their classes if Classify is enabled, the same as with normal annotations.
...
This adds the option to classify the object into one of the classes. If the classification is enabled, each marked object needs a class to be assigned to it.
For more details visit Classifier Classifier. This can also be achieved by combining Detector and Classifier as separate modules as described in the video below. However, classifying objects directly in the Detector is easier and faster.
...