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afdf3c3f
编写于
3月 05, 2019
作者:
D
dengkaipeng
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差异文件
fix doc.test=develop
上级
5b37cf0a
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2
隐藏空白更改
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2 changed file
with
6 addition
and
6 deletion
+6
-6
paddle/fluid/operators/detection/yolov3_loss_op.cc
paddle/fluid/operators/detection/yolov3_loss_op.cc
+2
-2
python/paddle/fluid/layers/detection.py
python/paddle/fluid/layers/detection.py
+4
-4
未找到文件。
paddle/fluid/operators/detection/yolov3_loss_op.cc
浏览文件 @
afdf3c3f
...
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@@ -227,8 +227,8 @@ class Yolov3LossOpMaker : public framework::OpProtoAndCheckerMaker {
While :attr:`use_label_smooth` is set to be :attr:`True`, the classification
target will be smoothed when calculating classification loss, target of
positive samples will be smoothed to
$$1.0 - 1.0/class_num$$
and target of
negetive samples will be smoothed to
$$1.0/class_num$$
.
positive samples will be smoothed to
:math:`1.0 - 1.0 / class\_num`
and target of
negetive samples will be smoothed to
:math:`1.0 / class\_num`
.
While :attr:`GTScore` is given, which means the mixup score of ground truth
boxes, all looses incured by a ground truth box will be multiplied by its
...
...
python/paddle/fluid/layers/detection.py
浏览文件 @
afdf3c3f
...
...
@@ -545,9 +545,9 @@ def yolov3_loss(x,
Raises:
TypeError: Input x of yolov3_loss must be Variable
TypeError: Input gtbox of yolov3_loss must be Variable
"
TypeError: Input gtlabel of yolov3_loss must be Variable
"
TypeError: Input gtscore of yolov3_loss must be Variable
"
TypeError: Input gtbox of yolov3_loss must be Variable
TypeError: Input gtlabel of yolov3_loss must be Variable
TypeError: Input gtscore of yolov3_loss must be Variable
TypeError: Attr anchors of yolov3_loss must be list or tuple
TypeError: Attr class_num of yolov3_loss must be an integer
TypeError: Attr ignore_thresh of yolov3_loss must be a float number
...
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@@ -559,7 +559,7 @@ def yolov3_loss(x,
x = fluid.layers.data(name='x', shape=[255, 13, 13], dtype='float32')
gtbox = fluid.layers.data(name='gtbox', shape=[6, 4], dtype='float32')
gtlabel = fluid.layers.data(name='gtlabel', shape=[6], dtype='int32')
gtscore = fluid.layers.data(name='gt
label
', shape=[6], dtype='int32')
gtscore = fluid.layers.data(name='gt
score
', shape=[6], dtype='int32')
anchors = [10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59, 119, 116, 90, 156, 198, 373, 326]
anchor_mask = [0, 1, 2]
loss = fluid.layers.yolov3_loss(x=x, gtbox=gtbox, gtlabel=gtlabel,
...
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