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Comment: images update

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3. [SMART SORTING] - Click on the ‘SMART SORTING’ button, and type what’s the prefix for the

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images within the field. There is also an option to use regular expressions instead of prefixes if you check the ‘Regex’ checkbox or you can filter images by their tags.

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Info

Tip: It is also possible to select multiple images at once using the ‘Shift’ key and classify them in bulk, by selecting the first image, then holding 'Shift' and selecting the last image from the range.

Note

Attention: For 3. [SMART SORTING], please note that if the filename standard is, for instance, ‘testpart_OK52’, you would have to type ‘testpart_OK' - if you type only ‘OK’ as part of the name it won’t classify, as it classifies literally by prefix.

Another approach is to check the Regex checkbox which allows you to write regular expressions instead of prefixes - then if you write only ‘OK’ it matches all images which contain ‘OK’ anywhere in their name.

Info

Assigning at least 1 image as ‘OK’ already enables you to Start Training, but we usually recommend using at least 20% of OK images for optimal results, depending on the surface variability.

Feature size

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The view-finder size should be determined depending on how detailed the inspection model should be.

If you choose a size that is too small, the algorithm will not be able to identify details on the surroundings, therefore, some defects may not be identified.

On the other hand, if you select a size that is too large, some details can be overlooked - resulting in a large number of false positives.

Some errors are seen from a larger distance, and others can only be seen through a magnifying glass, just as when a human eye focuses on detecting errors.

Along with the view-finder size, the processing time will be directly proportional to it, as the user indicates how detailed the inspection should beFeature Size option configures the expected and also allowed size of defect features that the trained model is going to be able to find in an image. This acts as optimalization for training and evaluation.

For small annotations set small feature size, for bigger annotations higher feature size is better.

There is no general rule on how to set the right size, however, the size of the defects you are searching for can be used as a guideline. You need to try out several sizes in order to learn what works best for your inspection scenario.The view-finder size, ideally, should be slightly larger than the largest defect., it is necessary to tweak the values for optimal results.

Detection Results - Heatmap

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