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loss不是很懂 about iim HOT 6 OPEN

taohan10200 avatar taohan10200 commented on July 28, 2024
loss不是很懂

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henbucuoshanghai avatar henbucuoshanghai commented on July 28, 2024

self.binar_map_loss = (torch.abs(binar_map-mask_gt)).mean()

        self.head_map_loss = F.mse_loss(pre_map, mask_gt)

请问为什么二个map在回归的时候 均和mask_gt计算loss? 那这样的话 推理的时候直接任何一个map不就是最后的结果?为什么二者做差呢?不是很懂 多谢

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taohan10200 avatar taohan10200 commented on July 28, 2024

两个损失针对的是不同的对象,一个是二值化后的输出,一个是二值化前的,二值化后的输出才是最后用来检测连通域进行定位的输出。二者作差即L1损失。

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henbucuoshanghai avatar henbucuoshanghai commented on July 28, 2024

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taohan10200 avatar taohan10200 commented on July 28, 2024

pre_map和gt计算L2 loss, gt 是[0,1]的mask图。 没有出现两个map做差再和gt算L1 loss的, 用来计算L1 loss的是二值化后的输出binar_map。

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henbucuoshanghai avatar henbucuoshanghai commented on July 28, 2024

你好 感谢回复 请问figure1的 图 代码有公开吗?请问在哪里呢?感谢

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henbucuoshanghai avatar henbucuoshanghai commented on July 28, 2024

密度图方法是怎样生成groundtruth的? 直接人头中心是一个点,只有一个点吗?密度图的gt云图是怎么得到的?

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