本文整理匯總了Python中mmdet.core.mask_cross_entropy方法的典型用法代碼示例。如果您正苦於以下問題：Python core.mask_cross_entropy方法的具體用法？Python core.mask_cross_entropy怎麽用？Python core.mask_cross_entropy使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類mmdet.core的用法示例。
在下文中一共展示了core.mask_cross_entropy方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: loss
# 需要導入模塊: from mmdet import core [as 別名]
# 或者: from mmdet.core import mask_cross_entropy [as 別名]
def loss(self, mask_pred, mask_targets, labels):
loss = dict()
if self.class_agnostic:
loss_mask = mask_cross_entropy(mask_pred, mask_targets,
torch.zeros_like(labels))
else:
loss_mask = mask_cross_entropy(mask_pred, mask_targets, labels)
loss['loss_mask'] = loss_mask
return loss 示例2: loss_aux
# 需要導入模塊: from mmdet import core [as 別名]
# 或者: from mmdet.core import mask_cross_entropy [as 別名]
def loss_aux(self, mask_pred, mask_targets, labels, alpha=0.25):
loss = dict()
mask_pred_level0 = mask_pred[0::4,:]
mask_pred_level1 = mask_pred[1::4,:]
mask_pred_level2 = mask_pred[2::4,:]
mask_pred_level3 = mask_pred[3::4,:]
if self.class_agnostic:
loss_mask_level0 = mask_cross_entropy(mask_pred_level0, mask_targets,
torch.zeros_like(labels))
loss_mask_level1 = mask_cross_entropy(mask_pred_level1, mask_targets,
torch.zeros_like(labels))
loss_mask_level2 = mask_cross_entropy(mask_pred_level2, mask_targets,
torch.zeros_like(labels))
loss_mask_level3 = mask_cross_entropy(mask_pred_level3, mask_targets,
torch.zeros_like(labels))
else:
loss_mask_level0 = mask_cross_entropy(mask_pred_level0, mask_targets, labels)
loss_mask_level1 = mask_cross_entropy(mask_pred_level1, mask_targets, labels)
loss_mask_level2 = mask_cross_entropy(mask_pred_level2, mask_targets, labels)
loss_mask_level3 = mask_cross_entropy(mask_pred_level3, mask_targets, labels)
loss['loss_mask_level0'] = loss_mask_level0 * alpha
loss['loss_mask_level1'] = loss_mask_level1 * alpha
loss['loss_mask_level2'] = loss_mask_level2 * alpha
loss['loss_mask_level3'] = loss_mask_level3 * alpha
return loss