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NMS的使用.drawio
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NMS的使用.drawio
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<mxCell id="iZZFebuZpYIs87GABAeR-1" value="<font style="font-size: 18px;">rcnn 311<br>self.proposal_generator</font>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-2" value="<font style="font-size: 18px;">ubteacher modeling rpn.py 61<br>proposals = self.predict_proposals</font>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-3" value="<font style="font-size: 18px;">d2 modeling proposal_generator rpn.py 504<br>find_top_rpn_proposals<br>RPN的采样时从anchor中采样<br></font>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-4" value="<font style="font-size: 18px;">d2 modeling proposal_generator prpposal_utils.py 122<br>batched_nms<br>先计算损失，再NMS<br>这里的NMS有点特殊，RPN的分数是直接使用未激活的<br>RPN使用原本的NMS，但是ROI的使用自定义的NMS<br>还有一点需要强调，RPN 计算损失的时候没有NMS<br>&nbsp;而是对带0和1标签的样本进行了损失的计算<br></font>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-10" value="<span style="font-size: 18px;">ubteacher modeling roi_heads 83行</span><span style="font-size: 18px;"><br>label_and_sample_proposals<br>对2000个proposals 取样512个<br>128个正样本 384个负样本<br></span>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-14" value="<font style="font-size: 18px;">ubteacher modeling roi_heads 164行<br>self.proposal_matcher(match_quality_matrix)<br>计算和Ground truth IOU, 值大于0.5的作为正样本<br><font style="font-size: 18px;" color="#ff3333">RPN 和 ROI 都有采样的做法<br>但是RPN是阈值设为0.7 计算损失<br>ROI 是设置0.5作为阈值<br></font><font style="font-size: 18px;" color="#ff3333">matched_labels 只包含 0和1</font><br>返回的参数分别包括IOU最大的ID，以及正负样本的标签</font>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-15" value="<span style="font-size: 18px;">ubteacher modeling roi_heads 167行</span><br><span style="font-size: 18px;">self._sample_proposals()<br>从正样本中挑选128个作为正样本</span><br><span style="font-size: 18px;">从负样本中挑选384个作为负样本</span>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-16" value="<span style="font-size: 18px;">ubteacher modeling roi_heads 180行</span><br><span style="font-size: 18px;">proposals_per_image.set<br>将gt_boxes 加到proposal中去<br>返回512个proposals<br></span>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-17" value="<span style="font-size: 18px;">ubteacher modeling roi_heads 103行</span><br><span style="font-size: 18px;">self._forward_box</span><br>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-18" value="<font style="font-size: 18px;">ubteacher modeling roi_heads 103行<br>self.box_pooler<br>self.box_head<br>self.box_predictor</font>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-19" value="<span style="font-size: 18px;">ubteacher modeling roi_heads fast_rcnn 245行<br></span><p><font style="font-size: 18px;">计算512个proposal的类别分数</font></p>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-20" value="<font style="font-size: 18px;">ubteacher modeling roi_heads 128行<br>self.box_pooler<br>self.box_head<br>self.box_predictor</font>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-21" value="<span style="font-size: 18px;">ubteacher modeling roi_heads fast_rcnn 128行<br></span><p><font style="font-size: 18px;">计算512个proposal中正样本的回归损失</font></p><p><font style="font-size: 18px;">那么就是说ROI计算损失的时候依然用不到NMS</font></p>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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<mxCell id="iZZFebuZpYIs87GABAeR-23" value="<font style="font-size: 18px;"><font color="#ff6666">总结一下，proposal和roi在计算损失的时候都不会用到NMS，而proposal在给roi提供proposal的时候用到了<br>并且teacher模型给student模型提供伪标签用到了<br>在模型最后的计算map时用到了</font><br></font>" style="rounded=1;whiteSpace=wrap;html=1;fontFamily=Helvetica;fontStyle=0;" parent="1" vertex="1">
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