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I am trying to finetune yolo on my dataset to predict the object, but even if the object is skewed the boundary box is always and not a skewed rectangle. While training I labelled my dataset carefully, not just using standard rectangles, rather skewed 4 sided polygons to outline the object. But why is it that while predicting it doesnt do this
The text was updated successfully, but these errors were encountered:
There are 3 types of annotations a model can support
Bounding boxes, which are always implied to be rectangles without any rotation.
Masks, which operate on pixel-level and can take any shape.
Oriented Bounding Boxes (OBB) which are rectangles, but rotated. This is the least popular method.
Very precisely detecting a skewed rectangle can only be done with masks and instance segmentation. I would suggest trying out oriented bounding boxes as well.
I am trying to finetune yolo on my dataset to predict the object, but even if the object is skewed the boundary box is always and not a skewed rectangle. While training I labelled my dataset carefully, not just using standard rectangles, rather skewed 4 sided polygons to outline the object. But why is it that while predicting it doesnt do this
The text was updated successfully, but these errors were encountered: