├── .DS_Store
├── .gitignore
├── LICENSE
├── README.md
├── SRM.py
└── assets
├── .DS_Store
├── compare.png
├── result_classification.png
├── result_transfer.png
└── teaser.png
/.DS_Store:
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https://raw.githubusercontent.com/taki0112/SRM-Tensorflow/649cbd02d1b3c06fb51e9bc071234c7ca3cbfd69/.DS_Store
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/.gitignore:
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1 | # Byte-compiled / optimized / DLL files
2 | __pycache__/
3 | *.py[cod]
4 | *$py.class
5 |
6 | # C extensions
7 | *.so
8 |
9 | # Distribution / packaging
10 | .Python
11 | build/
12 | develop-eggs/
13 | dist/
14 | downloads/
15 | eggs/
16 | .eggs/
17 | lib/
18 | lib64/
19 | parts/
20 | sdist/
21 | var/
22 | wheels/
23 | *.egg-info/
24 | .installed.cfg
25 | *.egg
26 | MANIFEST
27 |
28 | # PyInstaller
29 | # Usually these files are written by a python script from a template
30 | # before PyInstaller builds the exe, so as to inject date/other infos into it.
31 | *.manifest
32 | *.spec
33 |
34 | # Installer logs
35 | pip-log.txt
36 | pip-delete-this-directory.txt
37 |
38 | # Unit test / coverage reports
39 | htmlcov/
40 | .tox/
41 | .coverage
42 | .coverage.*
43 | .cache
44 | nosetests.xml
45 | coverage.xml
46 | *.cover
47 | .hypothesis/
48 | .pytest_cache/
49 |
50 | # Translations
51 | *.mo
52 | *.pot
53 |
54 | # Django stuff:
55 | *.log
56 | local_settings.py
57 | db.sqlite3
58 |
59 | # Flask stuff:
60 | instance/
61 | .webassets-cache
62 |
63 | # Scrapy stuff:
64 | .scrapy
65 |
66 | # Sphinx documentation
67 | docs/_build/
68 |
69 | # PyBuilder
70 | target/
71 |
72 | # Jupyter Notebook
73 | .ipynb_checkpoints
74 |
75 | # pyenv
76 | .python-version
77 |
78 | # celery beat schedule file
79 | celerybeat-schedule
80 |
81 | # SageMath parsed files
82 | *.sage.py
83 |
84 | # Environments
85 | .env
86 | .venv
87 | env/
88 | venv/
89 | ENV/
90 | env.bak/
91 | venv.bak/
92 |
93 | # Spyder project settings
94 | .spyderproject
95 | .spyproject
96 |
97 | # Rope project settings
98 | .ropeproject
99 |
100 | # mkdocs documentation
101 | /site
102 |
103 | # mypy
104 | .mypy_cache/
105 |
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/LICENSE:
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1 | MIT License
2 |
3 | Copyright (c) 2019 Junho Kim (1993.01.12)
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 |
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 |
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 |
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/README.md:
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1 | # SRM-Tensorflow
2 | Simple Tensorflow implementation of ["SRM : A Style-based Recalibration Module for Convolutional Neural Networks"](https://arxiv.org/abs/1903.10829)
3 |
4 |
5 |
6 |
18 |
19 |
25 |
26 | ### Style Transfer
27 | 
28 |
29 | ### Reference
30 | * [SRMNet-Pytorch](https://github.com/EvgenyKashin/SRMnet)
31 |
32 | ## Author
33 | Junho Kim
34 |
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/SRM.py:
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1 | import tensorflow as tf
2 |
3 | def SRM_block(x, channels, use_bias=False, is_training=True, scope='srm_block'):
4 | with tf.variable_scope(scope) :
5 | bs, h, w, c = x.get_shape().as_list() # c = channels
6 |
7 | x = tf.reshape(x, shape=[bs, -1, c]) # [bs, h*w, c]
8 |
9 | x_mean, x_var = tf.nn.moments(x, axes=1, keep_dims=True) # [bs, 1, c]
10 | x_std = tf.sqrt(x_var + 1e-5)
11 |
12 | t = tf.concat([x_mean, x_std], axis=1) # [bs, 2, c]
13 |
14 | z = tf.layers.conv1d(t, channels, kernel_size=2, strides=1, use_bias=use_bias)
15 | z = tf.layers.batch_normalization(z, momentum=0.9, epsilon=1e-05, center=True, scale=True, training=is_training, name=scope)
16 | # z = tf.contrib.layers.batch_norm(z, decay=0.9, epsilon=1e-05, center=True, scale=True, updates_collections=None, is_training=is_training, scope=scope)
17 |
18 | g = tf.sigmoid(z)
19 |
20 | x = tf.reshape(x * g, shape=[bs, h, w, c])
21 |
22 | return x
23 |
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/assets/.DS_Store:
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https://raw.githubusercontent.com/taki0112/SRM-Tensorflow/649cbd02d1b3c06fb51e9bc071234c7ca3cbfd69/assets/.DS_Store
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/assets/compare.png:
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https://raw.githubusercontent.com/taki0112/SRM-Tensorflow/649cbd02d1b3c06fb51e9bc071234c7ca3cbfd69/assets/compare.png
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/assets/result_classification.png:
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https://raw.githubusercontent.com/taki0112/SRM-Tensorflow/649cbd02d1b3c06fb51e9bc071234c7ca3cbfd69/assets/result_classification.png
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/assets/result_transfer.png:
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https://raw.githubusercontent.com/taki0112/SRM-Tensorflow/649cbd02d1b3c06fb51e9bc071234c7ca3cbfd69/assets/result_transfer.png
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/assets/teaser.png:
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https://raw.githubusercontent.com/taki0112/SRM-Tensorflow/649cbd02d1b3c06fb51e9bc071234c7ca3cbfd69/assets/teaser.png
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