Fully Convolutional Networks
Project description
fcn - Fully Convolutional Networks
==================================
.. image:: https://badge.fury.io/gh/wkentaro%2Ffcn.svg
:target: https://badge.fury.io/gh/wkentaro%2Ffcn
.. image:: https://travis-ci.org/wkentaro/fcn.svg?branch=master
:target: https://travis-ci.org/wkentaro/fcn
This is Chainer_ implementation of fcn.berkeleyvision.org_.
.. _fcn.berkeleyvision.org: https://github.com/shelhamer/fcn.berkeleyvision.org.git
.. _Chainer: https://github.com/pfnet/chainer.git
Features
--------
- Provide FCN8s model for Chainer. [v1.0.0_]
- Copy caffemodel to chainermodel. [v1.0.0_]
- Forwarding with Chainer for pascal dataset. [v1.0.0_]
- Training with Chainer for pascal dataset. [v2.0.0_]
- Training for APC2015 dataset. [**not yet**]
.. _v1.0.0: https://github.com/wkentaro/fcn/releases/tag/v1.0.0
.. _v2.0.0: https://github.com/wkentaro/fcn/releases/tag/v2.0.0
License
-------
| Copyright (C) 2016 Kentaro Wada
| Released under the MIT license
| http://opensource.org/licenses/mit-license.php
For Beginners
-------------
Installation
++++++++++++
.. code-block:: bash
pip install fcn
Forwarding
++++++++++
Forwarding is done as below, and computation graph is `here <https://github.com/wkentaro/fcn/blob/master/_images/fcn8s_forward.jpg>`_.
.. code-block:: bash
# Download sample image
wget https://farm2.staticflickr.com/1522/26471792680_a485afb024_z_d.jpg -O sample.jpg
# forwaring of the networks
fcn_forward.py --img-files sample.jpg --gpu -1 # cpu mode
fcn_forward.py --img-files sample.jpg # gpu mode
.. image:: https://raw.githubusercontent.com/wkentaro/fcn/master/_images/26471792680.jpg
Original Image: https://www.flickr.com/photos/faceme/26471792680/
For Developers
--------------
Installation
++++++++++++
.. code-block:: bash
git clone https://github.com/wkentaro/fcn.git
cd fcn
python setup.py install
You need to download pascal VOC2012 dataset from `here <http://host.robots.ox.ac.uk/pascal/VOC/voc2012/>`_,
and install it as below construction::
- fcn - data - pascal - VOC2012 -- JPEGImages
- SegmentationClass
- ...
Fowarding
+++++++++
Forwarding with trained model in caffe is done as below:
.. code-block:: bash
# This downloads caffemodel and convert it to chainermodel
./scripts/caffe_to_chainermodel.py
# forwarding of the networks
./scripts/fcn_forward.py --img-files data/pascal/VOC2012/JPEGImages/2007_000129.jpg
.. image:: https://raw.githubusercontent.com/wkentaro/fcn/master/_images/2007_000129.jpg
Original Image: http://host.robots.ox.ac.uk/pascal/VOC/voc2012/
Training
++++++++
.. code-block:: bash
./scripts/fcn_train.py
Currently we support only training FCN32s.
The learning curve looks like below:
.. image:: https://raw.githubusercontent.com/wkentaro/fcn/master/_images/fcn32s_learning_curve.png
Forwarding with ``fcn32s_60000.chainermodel`` ends with below result:
.. image:: https://raw.githubusercontent.com/wkentaro/fcn/master/_images/fcn32s_2007_000129.jpg
==================================
.. image:: https://badge.fury.io/gh/wkentaro%2Ffcn.svg
:target: https://badge.fury.io/gh/wkentaro%2Ffcn
.. image:: https://travis-ci.org/wkentaro/fcn.svg?branch=master
:target: https://travis-ci.org/wkentaro/fcn
This is Chainer_ implementation of fcn.berkeleyvision.org_.
.. _fcn.berkeleyvision.org: https://github.com/shelhamer/fcn.berkeleyvision.org.git
.. _Chainer: https://github.com/pfnet/chainer.git
Features
--------
- Provide FCN8s model for Chainer. [v1.0.0_]
- Copy caffemodel to chainermodel. [v1.0.0_]
- Forwarding with Chainer for pascal dataset. [v1.0.0_]
- Training with Chainer for pascal dataset. [v2.0.0_]
- Training for APC2015 dataset. [**not yet**]
.. _v1.0.0: https://github.com/wkentaro/fcn/releases/tag/v1.0.0
.. _v2.0.0: https://github.com/wkentaro/fcn/releases/tag/v2.0.0
License
-------
| Copyright (C) 2016 Kentaro Wada
| Released under the MIT license
| http://opensource.org/licenses/mit-license.php
For Beginners
-------------
Installation
++++++++++++
.. code-block:: bash
pip install fcn
Forwarding
++++++++++
Forwarding is done as below, and computation graph is `here <https://github.com/wkentaro/fcn/blob/master/_images/fcn8s_forward.jpg>`_.
.. code-block:: bash
# Download sample image
wget https://farm2.staticflickr.com/1522/26471792680_a485afb024_z_d.jpg -O sample.jpg
# forwaring of the networks
fcn_forward.py --img-files sample.jpg --gpu -1 # cpu mode
fcn_forward.py --img-files sample.jpg # gpu mode
.. image:: https://raw.githubusercontent.com/wkentaro/fcn/master/_images/26471792680.jpg
Original Image: https://www.flickr.com/photos/faceme/26471792680/
For Developers
--------------
Installation
++++++++++++
.. code-block:: bash
git clone https://github.com/wkentaro/fcn.git
cd fcn
python setup.py install
You need to download pascal VOC2012 dataset from `here <http://host.robots.ox.ac.uk/pascal/VOC/voc2012/>`_,
and install it as below construction::
- fcn - data - pascal - VOC2012 -- JPEGImages
- SegmentationClass
- ...
Fowarding
+++++++++
Forwarding with trained model in caffe is done as below:
.. code-block:: bash
# This downloads caffemodel and convert it to chainermodel
./scripts/caffe_to_chainermodel.py
# forwarding of the networks
./scripts/fcn_forward.py --img-files data/pascal/VOC2012/JPEGImages/2007_000129.jpg
.. image:: https://raw.githubusercontent.com/wkentaro/fcn/master/_images/2007_000129.jpg
Original Image: http://host.robots.ox.ac.uk/pascal/VOC/voc2012/
Training
++++++++
.. code-block:: bash
./scripts/fcn_train.py
Currently we support only training FCN32s.
The learning curve looks like below:
.. image:: https://raw.githubusercontent.com/wkentaro/fcn/master/_images/fcn32s_learning_curve.png
Forwarding with ``fcn32s_60000.chainermodel`` ends with below result:
.. image:: https://raw.githubusercontent.com/wkentaro/fcn/master/_images/fcn32s_2007_000129.jpg
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