<p>optimal numbers of layers and resolution depend on dataset.
The smaller objects - the higher resolution is required.
The large objects - the more layers are required. There is an article on choosing the optimal number of layers, filters and resolution for MS COCO dataset: https://arxiv.org/pdf/1911.09070.pdf</p>
<p>It depends on what accuracy and speed do you want. To reduce rewritten_bbox % just increase resolution and/or move some masks from [yolo] layers with low resolution, the [yolo] layers with higher resolution, and train. Also iou_thresh=1 may reduce rewritten_bbox %</p>
what does mean by rewritten box during yolo training on custom dataset?
<p>I am training my custom dataset on Yolo network and during training, I am getting info of rewritten box (as shown in the figure).</p>
<p>for example: total_bbox = 29159, rewritten_bbox = 0.006859 %</p>
<p>what does that mean? Is my training proceeding right?</p>
<p><a href="https://i.stack.imgur.com/MJm1Y.png" rel="nofollow noreferrer">enter image description here</a></p>