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IoU threshold for training? #8448
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Hello @DieBirke
All the best. |
Hello, thanks for the amount of infos. But I have some questions regarding the other methods: For 2. anchors: First calculate anchors for my dataset with the calc_anchors command thenI would just add or change the values in the .cfg file for that? Also I found options in my .cfg file for each yolo layer (where the anchors are incidently) that there is an iou-thresh
So there are options for tweaking the iuo right? |
Yes. That's right. You need to change mask and anchors, and also change number of filters in previous layer if required. Most of the parameters in yolo layer are explained in wiki Unfortunately, I'm not very good at understating loss functions for yolo. This two papers are major papers for bounding box regression training:
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Is there a way to modify the loss function so the bounding boxes are more precise?
I know I can calculate map with an IoU threshold (standard 0.5) but can I adjust how the model is trained by inputting such a threshold?
While the model works well enough in detecting my objects, the bounding box isn't quite right sometimes and will cut off small parts of the obejct. Maybe this problem vanishes with more training data, which I am generating atm.
I already looked through my data and the bounding boxes there are as accurate as they can be.
IoU threshold = 0.5 results in a 98% map
IoU threshold = 0.8 drops this down to 45%
Average IoU is 64.58% which is good but I am trying to maximize the precision of the bounding boxes
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