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bob
bob.learn.pytorch
Commits
a592c144
Commit
a592c144
authored
Mar 01, 2019
by
Anjith GEORGE
Committed by
Anjith GEORGE
Mar 14, 2019
Browse files
Added a MultiSpectral extension for VGG16 for PAD
parent
5335c905
Changes
3
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Inline
Side-by-side
bob/learn/pytorch/architectures/DeepMSPAD.py
0 → 100644
View file @
a592c144
import
torch
from
torch
import
nn
from
torchvision
import
models
class
DeepMSPAD
(
nn
.
Module
):
""" Deep multispectral PAD algorithm
Attributes:
pretrained: bool
if set `True` loads the pretrained vgg16 model.
vgg: :py:class:`torch.nn.Module`
The VGG16 model
relu: :py:class:`torch.nn.Module`
ReLU activation
enc: :py:class:`torch.nn.Module`
Uses the layers for feature extraction
linear1: :py:class:`torch.nn.Module`
Fully connected layer
linear2: :py:class:`torch.nn.Module`
Fully connected layer
dropout: :py:class:`torch.nn.Module`
Dropout layer
sigmoid: :py:class:`torch.nn.Module`
Sigmoid activation
"""
def
__init__
(
self
,
pretrained
=
True
,
num_channels
=
4
):
""" Init method
Parameters
----------
pretrained: bool
if set `True` loads the pretrained vgg16 model.
num_channels: int
Number of channels in the input
"""
super
(
DeepMSPAD
,
self
).
__init__
()
vgg
=
models
.
vgg16
(
pretrained
=
pretrained
)
features
=
list
(
vgg
.
features
.
children
())
features
[
0
]
=
nn
.
Conv2d
(
num_channels
,
64
,
kernel_size
=
(
3
,
3
),
stride
=
(
1
,
1
),
padding
=
(
1
,
1
))
self
.
enc
=
nn
.
Sequential
(
*
features
)
self
.
linear1
=
nn
.
Linear
(
25088
,
256
)
self
.
relu
=
nn
.
ReLU
()
self
.
dropout
=
nn
.
Dropout
(
p
=
0.5
)
self
.
linear2
=
nn
.
Linear
(
256
,
1
)
self
.
sigmoid
=
nn
.
Sigmoid
()
def
forward
(
self
,
x
):
""" Propagate data through the network
Parameters
----------
x: :py:class:`torch.Tensor`
The data to forward through the network
Returns
-------
x: :py:class:`torch.Tensor`
The last layer of the network
"""
enc
=
self
.
enc
(
x
)
x
=
enc
.
view
(
-
1
,
25088
)
x
=
self
.
linear1
(
x
)
x
=
self
.
relu
(
x
)
x
=
self
.
dropout
(
x
)
x
=
self
.
linear2
(
x
)
x
=
self
.
sigmoid
(
x
)
return
x
bob/learn/pytorch/architectures/__init__.py
View file @
a592c144
...
...
@@ -6,6 +6,7 @@ from .LightCNN import LightCNN29v2
from
.MCCNN
import
MCCNN
from
.MCCNNv2
import
MCCNNv2
from
.FASNet
import
FASNet
from
.DeepMSPAD
import
DeepMSPAD
from
.DCGAN
import
DCGAN_generator
from
.DCGAN
import
DCGAN_discriminator
...
...
bob/learn/pytorch/test/test.py
View file @
a592c144
...
...
@@ -84,6 +84,14 @@ def test_architectures():
output
=
net
.
forward
(
t
)
assert
output
.
shape
==
torch
.
Size
([
1
,
1
])
#DeepMSPAD
a
=
numpy
.
random
.
rand
(
1
,
8
,
224
,
224
).
astype
(
"float32"
)
t
=
torch
.
from_numpy
(
a
)
from
..architectures
import
DeepMSPAD
net
=
FASNet
(
pretrained
=
False
,
num_channels
=
8
)
output
=
net
.
forward
(
t
)
assert
output
.
shape
==
torch
.
Size
([
1
,
1
])
# DCGAN
d
=
numpy
.
random
.
rand
(
1
,
3
,
64
,
64
).
astype
(
"float32"
)
t
=
torch
.
from_numpy
(
d
)
...
...
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