Comments (6)
我导出来的onnx和你的不太一样,想知道在concate的时候,你是怎么操作的
loc_pred = loc.view(loc.size(0), -1, 4).reshape(1,-1) #[1, 7759, 4]-->[1,7759x4]
conf_pred = self.softmax(conf.view(-1, self.num_classes)).reshape(1,-1) #[7759, 2]-->[1,7559x2]
output = torch.cat((loc_pred,conf_pred),0)
@xiaoxiaotao
from person-detection.
他的网络输出,7759×4是位置信息,7759×2是置信度,两个都reshape成一维的再进行连接
from person-detection.
嗯嗯 我用自己导出来的也可以推断 只是可能一些细节跟你不太一样
from person-detection.
loc = torch.cat([o.flatten(1) for o in loc], 1)
conf = torch.cat([o.flatten(1) for o in conf], 1)
print(loc.shape)
print(conf.shape)
output=torch.cat((loc,conf),1)
from person-detection.
没有搞懂为什么要把softmax拿出来呢
from person-detection.
当时为了了解数据的流动,全都拆开了,进一步了解运行过程
from person-detection.
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from person-detection.