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Faster R-CNN Process


Execute Faster R-CNN model, directly including the appropriate preproc and postproc, then add the detected framing rectangles. Type : polymorphic.


Input parameters


DNN Src : class
Image Src : class, type accepted U8, RGB, HSL.
Class Names Files : path,
path of classes file on which the model is trained.

Process Parameters : cluster,

Confidence Threshold : float, a threshold used to filter boxes by score.
NMS Threshold : float, a threshold used in non maximum suppression.
Additional Display : boolean, displays the result in a window external to LabVIEW.

Output parameters


DNN Dst : class
Image Dst : class


All these exemples are snippets PNG, you can drop these Snippet onto the block diagram and get the depicted code added to your VI (Do not forget to install TIGR library to run it).

Use Faster process

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