def __init__(self, iou_thresh=0.5, neg_thresh=0.5, negative_mining_ratio=3,
stds=(0.1, 0.1, 0.2, 0.2), **kwargs):
super(SSDTargetGenerator, self).__init__(**kwargs)
self._matcher = CompositeMatcher([BipartiteMatcher(), MaximumMatcher(iou_thresh)])
if negative_mining_ratio > 0:
self._sampler = OHEMSampler(negative_mining_ratio, thresh=neg_thresh)
self._use_negative_sampling = True
else:
#实际使用的是这个模式
self._sampler = NaiveSampler()
self._use_negative_sampling = False
self._cls_encoder = MultiClassEncoder()
self._box_encoder = NormalizedBoxCenterEncoder(stds=stds)
self._center_to_corner = BBoxCenterToCorner(split=False)
def __init__(self):
super(AssginTarget, self).__init__()
self.matcher = CompositeMatcher(
[BipartiteMatcher(share_max=False),
MaximumMatcher(threshold=0.5)])
self.center_to_corner = gcv.nn.bbox.BBoxCenterToCorner(split=False)
#self.sampler = gcv.nn.sampler.NaiveSampler()
self.sampler = gcv.nn.sampler.OHEMSampler(3.0, thresh=0.5)
self.cls_encoder = gcv.nn.coder.MultiClassEncoder()
self.bbox_encoder = gcv.nn.coder.NormalizedBoxCenterEncoder(
stds=[0.1, 0.1, 0.2, 0.2])
return