Comments (5)
I also have this question, do you find the problem?
from weighted-boxes-fusion.
If any coordinate goes below 0 or higher than 1 it will be trimmed to 0 or 1 respectively.
It's in the code here:
https://github.com/ZFTurbo/Weighted-Boxes-Fusion/blob/master/ensemble_boxes/ensemble_boxes_wbf.py#L56
from weighted-boxes-fusion.
how to normalize? the box coordinate is (x1, y1, x2, y2) which represents the left-top and right-bottom corner, and the image's height is h, image's width is w. the normalized coordinates is (x1/w, y1/h, x2/w, y2/h)?
from weighted-boxes-fusion.
how to normalize? the box coordinate is (x1, y1, x2, y2) which represents the left-top and right-bottom corner, and the image's height is h, image's width is w. the normalized coordinates is (x1/w, y1/h, x2/w, y2/h)?
Yes, that's right.
from weighted-boxes-fusion.
how to normalize? the box coordinate is (x1, y1, x2, y2) which represents the left-top and right-bottom corner, and the image's height is h, image's width is w. the normalized coordinates is (x1/w, y1/h, x2/w, y2/h)?
Yes, that's right.
Hi, I also have the same problem, I understand how to normalize the box coordinates. However, Weighted-Boxes fusion need to calculate the IoU for each pair of bounding boxes. It means we need image height and width to convert them to box coordinates with Pascal Voc (without normalized). In function below, it does not require image height and width.
boxes, scores, labels = weighted_boxes_fusion(boxes_list, scores_list, labels_list, weights=weights, iou_thr=iou_thr, skip_box_thr=skip_box_thr)
Please help me explain it. Thank you.
from weighted-boxes-fusion.
Related Issues (20)
- Incorrect conf_type='max' mode HOT 1
- Strange result if boxes are intersected inside one model HOT 2
- confidence score > 1 issue HOT 1
- Bbox is 'Nan' when weights have 0 HOT 4
- How to find the optimal hyper-parameters in the ensembling process HOT 6
- Can work with polygon object ? HOT 1
- Compatibility for Instance Segmentation HOT 1
- Building wheel for llvmlite ... error HOT 1
- How to use in Yolov5
- Implemetation on mobile phone HOT 4
- label list on SSD HOT 1
- run NMS on empty bounding box from one of ensembled models HOT 5
- Single instance NMS
- 2d bbox wbf compute result error
- Is WBF consider to be part of Ensemble Learning HOT 4
- Back propagation when multiple models are ensembled
- model fusion for rotating boxes
- Recall and Confusion matrix, also the confusion matrix, of the WBF HOT 5
- about map_boxes in run_benchmark_oid.py HOT 2
- AttributeError: module 'numpy' has no attribute 'str'
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from weighted-boxes-fusion.