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Surfaces marked with ‘Ignore’ class are excluded from the training. Whereas, parts of the image which are left unannotated, are part of the training, but are considered an ‘OK’ class, which is not displayed when detected. Type 3 . Can be used e.g. in case we are unsure whether specific part of an image is OK or NG or if there’s some distortion and we don’t want to put that part into training. Precise type of surface detector doesn't use Ignore class.
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Types of Surface Detection
Three Two types of surface detector are available, each based on a different kind of neural network.
Type 1 – Fast:
Detects a wide range of defects, however can suffer from a higher amount of false positives (good parts evaluated as bad by the software).
Training time is reduced, with bigger & less options of view-finder sizes.
The model can optionally be optimized using Tensor RT for the specific GPU used when you check the TRT switch in model list. The optimisation improves inference times when processing images using this model. The model is optimized for specific GPU, so if you transfer the project to a PC with different type of GPU, the optimisation needs to be done again for the new graphics card.
This type does not require large datasets, however, performance on highly variable patterns may be more suitable for the Precise option.
Type 2 – ExperimentalPrecise:
This type may work well for smaller defects, however, it usually requires a lot more training data and it is our Experimental type, meaning that may not perform well in some applications.
Training time is usually longer.
Smaller & more precise view-finder sizes.
Type 3 – Precise:
This type works well with smaller defects such as scratches and others, however, it usually requires more training data to perform wellproduces very precise heatmaps and usually doesn’t have too much false positives. It's ideal for searching for objects/defects with closed shape. It also takes into account the surroundings, not just the surface itself.
Training time is usually longer.
View-finder size not available & ignore function not included.
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Along with the size, the recognition speed also varies. There is no general rule on how to set the right size, you need to try out a number of sizes and learn how to estimate the best size at the first try. The size of the defects you are searching for might be of help.
Surface detector of Type 1 usually works better using bigger size of view-finder than what would work with Type 2. The Type 3 The Precise type of surface detector doesn't use this parameter.
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