Comments (5)
Can you put small example which fails?
I mean archive with files.
from weighted-boxes-fusion.
this is an example
boxes_list = [
[
[]
],
[
[0.04, 0.56, 0.84, 0.92]
],
]
scores_list = [
[],
[0.5]
]
labels_list = [
[],
[1]
]
weights = [2, 1]
boxes, scores, labels = nms_method(boxes_list, scores_list, labels_list, method=3, weights=weights, iou_thr=0.5, sigma=0.5, thresh=0.001)
from weighted-boxes-fusion.
It was a little bit incorrect. boxes_list shouldn't contain anything if empty:
boxes_list = [
[
],
[
[0.04, 0.56, 0.84, 0.92]
],
]
scores_list = [
[],
[0.5]
]
labels_list = [
[],
[1]
]
weights = [2, 1]
boxes, scores, labels = nms_method(
boxes_list,
scores_list,
labels_list,
method=3,
weights=weights,
iou_thr=0.5,
sigma=0.5,
thresh=0.001
)
I fixed the problem.
from weighted-boxes-fusion.
It was a little bit incorrect. boxes_list shouldn't contain anything if empty:
boxes_list = [ [ ], [ [0.04, 0.56, 0.84, 0.92] ], ] scores_list = [ [], [0.5] ] labels_list = [ [], [1] ] weights = [2, 1] boxes, scores, labels = nms_method( boxes_list, scores_list, labels_list, method=3, weights=weights, iou_thr=0.5, sigma=0.5, thresh=0.001 )
I fixed the problem.
I meet this problem too. This example can not work for me, it still comes to the ValueError: all the input arrays must have same number of dimensions.
Hope you can give me some advice about how to fix it
from weighted-boxes-fusion.
The fix is in repository alredy.
from weighted-boxes-fusion.
Related Issues (20)
- Incorrect allows_overflow=False mode HOT 5
- 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
- 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
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from weighted-boxes-fusion.