def __init__(self,
iou_thresh=0.35,
neg_thresh=0.5,
negative_mining_ratio=3,
stds=(0.1, 0.1, 0.2, 0.2),
num_sample=1000,
pos_thresh=0.35,
neg_thresh_high=0.25,
pos_ratio=0.3,
neg_ratio=None,
fill_negative=False,
**kwargs):
super(PyramidBoxTargetGenerator, self).__init__(**kwargs)
self._matcher = CompositeMatcher([MaximumMatcher(iou_thresh)])
if negative_mining_ratio > 0:
self._sampler = OHEMSampler(negative_mining_ratio,
thresh=neg_thresh)
else:
# self._sampler = NaiveSampler()
self._sampler = QuotaSampler(num_sample=num_sample,
pos_thresh=pos_thresh,
neg_thresh_high=neg_thresh_high,
neg_thresh_low=-np.inf,
pos_ratio=pos_ratio,
neg_ratio=neg_ratio,
fill_negative=fill_negative)
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, 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)