periph_rois

[abajaj945]

Can you please explain the code for periph_rois ,I mean what it is for? and I am not able to understand the significance of 'expand' variable in traineryolo/box_utils.py

[martin-gorner]

Yes, this is an experimental feature. The idea is that assigning a ROI (region of interest) to a YOLO grid cell by its center might be problematic. If the ground truth ROI is off by just a pixel, it might be assigned to a different YOLO grid cell while nothing in the image really justifies it. More worryingly, both YOLO cells will probably find a plane, in roughly the correct position, but one of them will be punished for it in the loss because the ground truth ROI was assigned to one of the cells only.

The "expand" parameter allows a YOLO grid cell be assigned a ground truth ROI even if the ROI is centered slightly outside of the cell (by the factor specified in the "expand" param, typically 1.3). This way, if a plane is centered on a boundary, its ground truth ROI will be assigned to both YOLO grid cells and if both YOLO grid cells (correctly) find the plane, both will be rewarded for it in the loss.

[abajaj945]

Thank you, I am building a ship detection model and your work is really helpfull.

[martin-gorner]

Have you tried the object detection model and API that is provicded in the Tensorflow distribution ? https://github.com/tensorflow/models/tree/master/research/object_detection

[abajaj945]

you have taken width of ground truth roi with respect to cell width or image width?

[martin-gorner]

the "expand" parameter which is 1.3 by default is relative to the YOLO cell width.