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There can be 4 results, as shown in this image:
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True positive (TP) - A user classified the image as
and the application evaluated the image asStatus colour Green title ok
.Status colour Green title ok False positive (FP) - A user classified the image as
but the application evaluated the image asStatus colour Red title ng
.Status colour Green title OK False negative (FN) - A user classified the image as
but the application evaluated the image asStatus colour Green title ok
.Status colour Red title ng True negative (TN) - A user classified the image as
and the application evaluated the image asStatus colour Red title ng
.Status colour Red title ng
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Choose the amount of images to be included (if not all a random subset of images is selected, this subset still honors the total split between training and testing images, meaning if, among all of the modules 40% of images are used for training, then 40% of images in the report will be training)
Decide on displaying training or only testing images
Change the maximum image size - images in the report will be scaled to that size.
Show statistics like - recall, precision, confusion matrix, processing time
Show the modules used in the flow
Set default language (this can also be later changed inside the report)
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