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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2020-03-05 14:20:52 -08:00
parent 378f08c6d5
commit 692b006f4d
1 changed files with 3 additions and 3 deletions
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6
utils/utils.py
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@ -501,7 +501,7 @@ def build_targets(model, targets):
return tcls, tbox, indices, av
def non_max_suppression(prediction, conf_thres=0.1, iou_thres=0.6, multi_cls=True, classes=None, agnostic=False):
def non_max_suppression(prediction, conf_thres=0.1, iou_thres=0.6, multi_label=True, classes=None, agnostic=False):
"""
Removes detections with lower object confidence score than 'conf_thres'
Non-Maximum Suppression to further filter detections.
@ -516,7 +516,7 @@ def non_max_suppression(prediction, conf_thres=0.1, iou_thres=0.6, multi_cls=Tru
method = 'vision_batch'
batched = 'batch' in method # run once per image, all classes simultaneously
nc = prediction[0].shape[1] - 5 # number of classes
multi_cls = multi_cls and (nc > 1) # allow multiple classes per anchor
multi_label &= nc > 1 # multiple labels per box
output = [None] * len(prediction)
for image_i, pred in enumerate(prediction):
# Apply conf constraint
@ -536,7 +536,7 @@ def non_max_suppression(prediction, conf_thres=0.1, iou_thres=0.6, multi_cls=Tru
box = xywh2xyxy(pred[:, :4])
# Detections matrix nx6 (xyxy, conf, cls)
if multi_cls:
if multi_label:
i, j = (pred[:, 5:] > conf_thres).nonzero().t()
pred = torch.cat((box[i], pred[i, j + 5].unsqueeze(1), j.float().unsqueeze(1)), 1)
else: # best class only