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Open the application > Create new project > Start Interactive Tutorial
You will be guided through the main functionalities of our software, using this module.
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2. [NUMPAD] - When the image is selected, press numpad key ‘1’, it then categorizes it as an 'OK' image.
3. [SET BY FILENAMESMART SORTING] - Click on ‘SET BY FILENAMESMART SORTING’ button, and type what’s the prefix for the OK images within the field. There is also an option to use regular expressions instead of prefix if you check the ‘Regex’ checkbox. You can also filter images by their tags.
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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 hold 'Shift' and select the last image from the range. |
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Attention: For 3. [SET BY FILENAMESMART 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 prefix - then if you write only ‘OK’ it matches all images which contain ‘OK’ anywhere in their name. |
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Assigning at least 1 image as ‘OK’ already enables you to Start Training, but we usually recommend using at least 10 to 20 20% of OK images for optimal results, depending on the surface variability. |
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Lightweight
Fast Lightweight is the first type of Anomaly Detector, which uses a viewfinder size parameter, and its number of training epochs is set in the training settings. It offers faster inference than the Precise Standard type.
View-finder
The view-finder size should be determined depending on how detailed the inspection model should be.
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When you find suitable settings , but want to achieve even more precise results, you should then try Deep Training with more training cycles.
However, you should use the same settings as the best Fast Training model result, in order to compare them properly.
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Standard
Precise Standard is the newer second type of Anomaly Detector. It doesn’t use the viewfinder size parameter, because it is able to search for features of different sizes at once. Can offer more precise results, but the inference time is longer than with Fast the Lightweight type.
Detection Results - Heatmap
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