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With this method you can automatically create the required classes and annotate images without any additional input.
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Training
Look at the following annotations in one image.
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Before starting a training we have several options. You are able to https://pekatvision.atlassian.net/wiki/spaces/KB32/pages/934184772/Training+Overview#Extend-Model extend an existing model, set #Max-max size and other.
It is also possible to set a custom Training Data Split, this allows the user to specify how many annotation examples go into training the model and and how many go into testing the accuracy of classification.
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If the amount of available images is very low, it is recommended to set the slider to 100% train.
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The Training Data Split splits annotated images pseudo-randomly between Training and Testing. A random number generator is initiated using the selected seed, this means that with the same seed, the split of images will be the same.
Smart sorting
Smart sorting allows you to automatically classify all the detected objects according to image names or tags. All objects within the image will belong to the same class.
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To assign a class to an object, click on that object and select a class. The minimum number of classes for training is 2. Not all objects need to have a class assigned. The number in brackets next to the class name indicates the number of objects in that class. Classes can also be selected by pressing a numeric key for faster annotations.
Max size
For trainingIf you’re training the model using the classification over whole image, the classifier module must resize all images to the size of the biggest one, so that they all have the same size, with a maximum value of 800 pixels. The pre-set and recommendation is to keep max size at 256 pixels for most usecases.
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To evaluate the accuracy of the trained model you can have a look at Confusion Matrix https://pekatvision.atlassian.net/wiki/spaces/KB32/pages/934186628/Confusion+Matrix#Classifier-confusion-matrix. The matrix shows the classification results on the testing data.
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