First commit

.gitignore

+*~
+*.swp
+*.pyc
+bin
+eggs
+parts
+.installed.cfg
+.mr.developer.cfg
+*.egg-info
+src
+develop-eggs
+sphinx
+dist
+bob/ip/caffe_extractor/data/face_verification_experiment-master/
+bob/ip/caffe_extractor/data/vgg_face_caffe/

.gitlab-ci.yml

+# This build file heavily uses template features from YAML so it is generic
+# enough for any Bob project. Don't modify it unless you know what you're
+# doing.
+
+
+# Definition of our build pipeline
+stages:
+  - build
+  - test
+  - docs
+  - wheels
+  - deploy
+
+
+# ---------
+# Templates
+# ---------
+
+# Template for the build stage
+# Needs to run on all supported architectures, platforms and python versions
+.build_template: &build_job
+  stage: build
+  before_script:
+    - git clean -ffdx
+    - mkdir _ci
+    - curl --silent "https://gitlab.idiap.ch/bob/bob.admin/raw/master/gitlab/install.sh" > _ci/install.sh
+    - chmod 755 _ci/install.sh
+    - ./_ci/install.sh _ci #updates
+    - ./_ci/before_build.sh
+  script:
+    - ./_ci/build.sh
+  after_script:
+    - ./_ci/after_build.sh
+  artifacts:
+    expire_in: 1 week
+    paths:
+      - _ci/
+      - dist/
+      - sphinx/
+
+
+# Template for the test stage - re-installs from uploaded wheels
+# Needs to run on all supported architectures, platforms and python versions
+.test_template: &test_job
+  stage: test
+  before_script:
+    - ./_ci/install.sh _ci #updates
+    - ./_ci/before_test.sh
+  script:
+    - ./_ci/test.sh
+  after_script:
+    - ./_ci/after_test.sh
+
+
+# Template for the wheel uploading stage
+# Needs to run against one supported architecture, platform and python version
+.wheels_template: &wheels_job
+  stage: wheels
+  environment: intranet
+  only:
+    - master
+    - /^v\d+\.\d+\.\d+([abc]\d*)?$/  # PEP-440 compliant version (tags)
+  before_script:
+    - ./_ci/install.sh _ci #updates
+    - ./_ci/before_wheels.sh
+  script:
+    - ./_ci/wheels.sh
+  after_script:
+    - ./_ci/after_wheels.sh
+
+
+# Template for (latest) documentation upload stage
+# Only one real job needs to do this
+.docs_template: &docs_job
+  stage: docs
+  environment: intranet
+  only:
+    - master
+  before_script:
+    - ./_ci/install.sh _ci #updates
+    - ./_ci/before_docs.sh
+  script:
+    - ./_ci/docs.sh
+  after_script:
+    - ./_ci/after_docs.sh
+
+
+# Template for the deployment stage - re-installs from uploaded wheels
+# Needs to run on a single architecture only
+# Will deploy your package to PyPI and other required services
+# Only runs for tags
+.deploy_template: &deploy_job
+  stage: deploy
+  environment: internet
+  only:
+    - /^v\d+\.\d+\.\d+([abc]\d*)?$/  # PEP-440 compliant version (tags)
+  except:
+    - branches
+  before_script:
+    - ./_ci/install.sh _ci #updates
+    - ./_ci/before_deploy.sh
+  script:
+    - ./_ci/deploy.sh
+  after_script:
+    - ./_ci/after_deploy.sh
+
+
+# -------------
+# Build Targets
+# -------------
+
+# Linux + Python 2.7: Builds, tests, uploads wheel and deploys (if needed)
+build_linux_27:
+  <<: *build_job
+  variables: &linux_27_build_variables
+    PYTHON_VERSION: "2.7"
+    WHEEL_TAG: "py27"
+  tags:
+    - conda-linux
+
+test_linux_27:
+  <<: *test_job
+  variables: *linux_27_build_variables
+  dependencies:
+    - build_linux_27
+  tags:
+    - conda-linux
+
+wheels_linux_27:
+  <<: *wheels_job
+  variables: *linux_27_build_variables
+  dependencies:
+    - build_linux_27
+  tags:
+    - conda-linux
+
+deploy_linux_27:
+  <<: *deploy_job
+  variables: *linux_27_build_variables
+  dependencies:
+    - build_linux_27
+  tags:
+    - conda-linux
+
+
+# Linux + Python 3.5: Builds, tests and uploads wheel
+build_linux_35:
+  <<: *build_job
+  variables: &linux_35_build_variables
+    PYTHON_VERSION: "3.5"
+    WHEEL_TAG: "py3"
+  tags:
+    - conda-linux
+
+test_linux_35:
+  <<: *test_job
+  variables: *linux_35_build_variables
+  dependencies:
+    - build_linux_35
+  tags:
+    - conda-linux
+
+wheels_linux_35:
+  <<: *wheels_job
+  variables: *linux_35_build_variables
+  dependencies:
+    - build_linux_35
+  tags:
+    - conda-linux
+
+docs_linux_35:
+  <<: *docs_job
+  variables: *linux_35_build_variables
+  dependencies:
+    - build_linux_35
+  tags:
+    - conda-linux
+
+
+# Linux + Python 3.6: Builds and tests
+build_linux_36:
+  <<: *build_job
+  variables: &linux_36_build_variables
+    PYTHON_VERSION: "3.6"
+    WHEEL_TAG: "py3"
+  tags:
+    - conda-linux
+
+test_linux_36:
+  <<: *test_job
+  variables: *linux_36_build_variables
+  dependencies:
+    - build_linux_36
+  tags:
+    - conda-linux

LICENSE

+Copyright (c) 2016 Idiap Research Institute, http://www.idiap.ch/
+Written by Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this
+list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice,
+this list of conditions and the following disclaimer in the documentation
+and/or other materials provided with the distribution.
+
+3. Neither the name of the copyright holder nor the names of its contributors
+may be used to endorse or promote products derived from this software without
+specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

MANIFEST.in

+include README.rst buildout.cfg LICENSE version.txt requirements.txt ./bob/ip/tensorflow_extractor/data/checkpoint ./bob/ip/tensorflow_extractor/data/model.ckp.data-00000-of-00001 ./bob/ip/tensorflow_extractor/data/model.ckp.index ./bob/ip/tensorflow_extractor/data/model.ckp.meta
+recursive-include doc *.py *.rst
+recursive-include bob *.hdf5

README.rst

+.. vim: set fileencoding=utf-8 :
+.. Thu Jul 20 12:30:48 CEST 2017
+
+.. image:: https://img.shields.io/badge/docs-stable-yellow.svg
+   :target: https://www.idiap.ch/software/bob/docs/bob/bob.ip.tensorflow_extractor/stable/index.html
+.. image:: https://img.shields.io/badge/docs-latest-orange.svg
+   :target: https://www.idiap.ch/software/bob/docs/bob/bob.ip.tensorflow_extractor/master/index.html
+.. image:: https://gitlab.idiap.ch/bob/bob.ip.tensorflow_extractor/badges/master/build.svg
+   :target: https://gitlab.idiap.ch/bob/bob.ip.tensorflow_extractor/commits/master
+.. image:: https://gitlab.idiap.ch/bob/bob.ip.tensorflow_extractor/badges/master/coverage.svg
+   :target: https://gitlab.idiap.ch/bob/bob.ip.tensorflow_extractor/commits/master
+.. image:: https://img.shields.io/badge/gitlab-project-0000c0.svg
+   :target: https://gitlab.idiap.ch/bob/bob.ip.tensorflow_extractor
+.. image:: https://img.shields.io/pypi/v/bob.ip.tensorflow_extractor.svg
+   :target: https://pypi.python.org/pypi/bob.ip.tensorflow_extractor
+
+
+======================================================
+ Bob interface for feature extraction using Tensorflow
+======================================================
+
+This package is part of the signal-processing and machine learning toolbox
+Bob_. This package contains functionality to extract features from CNNs trained
+with tensorflow http://http://tensorflow.org/
+
+
+Installation
+------------
+
+Complete Bob's `installation`_ instructions. Then, to install this package,
+run::
+
+  $ conda install bob.ip.tensorflow_extractor
+
+
+Contact
+-------
+
+For questions or reporting issues to this software package, contact our
+development `mailing list`_.
+
+
+.. Place your references here:
+.. _bob: https://www.idiap.ch/software/bob
+.. _installation: https://www.idiap.ch/software/bob/install
+.. _mailing list: https://www.idiap.ch/software/bob/discuss

bob/__init__.py

+# see https://docs.python.org/3/library/pkgutil.html
+from pkgutil import extend_path
+__path__ = extend_path(__path__, __name__)

bob/ip/__init__.py

+# see https://docs.python.org/3/library/pkgutil.html
+from pkgutil import extend_path
+__path__ = extend_path(__path__, __name__)

bob/ip/tensorflow_extractor/Extractor.py

+#!/usr/bin/env python
+# vim: set fileencoding=utf-8 :
+# @author: Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
+# @date: Fri 17 Jun 2016 10:41:36 CEST
+
+
+import tensorflow as tf
+import os
+
+
+class Extractor(object):
+    """
+    Feature extractor using tensorflow
+
+    """
+
+    def __init__(self, checkpoint_filename, input_tensor, graph):
+        """Loads the tensorflow model
+
+        Parameters
+        ----------
+        checkpoint_filename: str
+            Path of your checkpoint. If the .meta file is providede the last checkpoint will be loaded.
+
+        model :
+            input_tensor: tf.Tensor used as a data entrypoint. It can be a **tf.placeholder**, the 
+            result of **tf.train.string_input_producer**, etc
+                        
+        graph : 
+            A tf.Tensor containing the operations to be executed
+        """
+
+        self.input_tensor = input_tensor
+        self.graph = graph
+
+        # Initializing the variables of the current graph
+        self.session = tf.Session()
+        self.session.run(tf.global_variables_initializer())
+
+        # Loading the last checkpoint and overwriting the current variables
+        saver = tf.train.Saver()
+        
+        if os.path.splitext(checkpoint_filename)[1] == ".meta":
+            saver.restore(self.session, tf.train.latest_checkpoint(os.path.dirname(checkpoint_filename)))
+        else:
+            saver.restore(self.session, checkpoint_filename)
+
+
+    def __del__(self):
+        tf.reset_default_graph()
+
+
+    def __call__(self, data):
+        """
+        Forward the data with the loaded neural network
+
+        Parameters
+        ----------
+        image : numpy.array
+            Input Data
+
+        Returns
+        -------
+        numpy.array
+            The features.
+
+        """
+        
+        return self.session.run(self.graph, feed_dict={self.input_tensor: data})
+

bob/ip/tensorflow_extractor/__init__.py

+#!/usr/bin/env python
+
+
+def scratch_network(inputs, end_point="fc1", reuse = False):
+
+    import tensorflow as tf
+    slim = tf.contrib.slim
+
+    # Creating a random network
+    initializer = tf.contrib.layers.xavier_initializer(seed=10)
+    end_points = dict()
+    
+    graph = slim.conv2d(inputs, 10, [3, 3], activation_fn=tf.nn.relu, stride=1, scope='conv1',
+                        weights_initializer=initializer, reuse=reuse)
+    end_points["conv1"] = graph
+                        
+    graph = slim.max_pool2d(graph, [4, 4], scope='pool1')
+    end_points["pool1"] = graph
+    
+    graph = slim.flatten(graph, scope='flatten1')
+    end_points["flatten1"] = graph
+        
+    graph = slim.fully_connected(graph, 10, activation_fn=None, scope='fc1',
+                                 weights_initializer=initializer, reuse=reuse)
+    end_points["fc1"] = graph                                 
+
+    return end_points[end_point]
+
+
+def download_file(url, out_file):
+  """Downloads a file from a given url
+
+  Parameters
+  ----------
+  url : str
+      The url to download form.
+  out_file : str
+      Where to save the file.
+  """
+  import sys
+  if sys.version_info[0] < 3:
+    # python2 technique for downloading a file
+    from urllib2 import urlopen
+    with open(out_file, 'wb') as f:
+      response = urlopen(url)
+      f.write(response.read())
+
+  else:
+    # python3 technique for downloading a file
+    from urllib.request import urlopen
+    from shutil import copyfileobj
+    with urlopen(url) as response:
+      with open(out_file, 'wb') as f:
+        copyfileobj(response, f)
+
+from .Extractor import Extractor
+
+
+def get_config():
+  """Returns a string containing the configuration information.
+  """
+  import bob.extension
+  return bob.extension.get_config(__name__)
+
+
+# gets sphinx autodoc done right - don't remove it
+def __appropriate__(*args):
+  """Says object was actually declared here, and not in the import module.
+  Fixing sphinx warnings of not being able to find classes, when path is shortened.
+  Parameters:
+
+    *args: An iterable of objects to modify
+
+  Resolves `Sphinx referencing issues
+  <https://github.com/sphinx-doc/sphinx/issues/3048>`
+  """
+
+  for obj in args:
+    obj.__module__ = __name__
+
+__appropriate__(
+    Extractor,    
+)
+
+# gets sphinx autodoc done right - don't remove it
+__all__ = [_ for _ in dir() if not _.startswith('_')]

bob/ip/tensorflow_extractor/data/checkpoint

+model_checkpoint_path: "model.ckp"
+all_model_checkpoint_paths: "model.ckp"

bob/ip/tensorflow_extractor/test.py

+import bob.io.base
+from bob.io.base.test_utils import datafile
+import bob.ip.tensorflow_extractor
+import tensorflow as tf
+
+import pkg_resources
+import numpy
+numpy.random.seed(10)
+import os
+
+slim = tf.contrib.slim
+from . import scratch_network
+
+
+def test_output():
+
+    # Loading MNIST model    
+    filename = os.path.join( pkg_resources.resource_filename(__name__, 'data'), 'model.ckp')
+    inputs = tf.placeholder(tf.float32, shape=(None, 28, 28, 1))
+
+    # Testing the last output
+    graph = scratch_network(inputs)
+    extractor = bob.ip.tensorflow_extractor.Extractor(filename, inputs, graph)
+    
+    
+    data = numpy.random.rand(2, 28, 28, 1).astype("float32")
+    output = extractor(data)
+    assert extractor(data).shape == (2, 10)
+    del extractor
+    
+    # Testing flatten
+    inputs = tf.placeholder(tf.float32, shape=(None, 28, 28, 1))
+    graph = scratch_network(inputs, end_point="flatten1")
+    extractor = bob.ip.tensorflow_extractor.Extractor(filename, inputs, graph)
+    
+    data = numpy.random.rand(2, 28, 28, 1).astype("float32")
+    output = extractor(data)
+    assert extractor(data).shape == (2, 1690)
+    del extractor
+
+
+def test_output_from_meta():
+
+    # Loading MNIST model
+    filename = os.path.join( pkg_resources.resource_filename(__name__, 'data'), "model.ckp.meta")
+    inputs = tf.placeholder(tf.float32, shape=(None, 28, 28, 1))
+
+    # Testing the last output
+    graph = scratch_network(inputs)
+    extractor = bob.ip.tensorflow_extractor.Extractor(filename, inputs, graph)
+    
+    data = numpy.random.rand(2, 28, 28, 1).astype("float32")
+    output = extractor(data)
+    assert extractor(data).shape == (2, 10)
+    del extractor
+    
+    # Testing flatten
+    inputs = tf.placeholder(tf.float32, shape=(None, 28, 28, 1))
+    graph = scratch_network(inputs, end_point="flatten1")
+    extractor = bob.ip.tensorflow_extractor.Extractor(filename, inputs, graph)
+    
+    data = numpy.random.rand(2, 28, 28, 1).astype("float32")
+    output = extractor(data)
+    assert extractor(data).shape == (2, 1690)
+    del extractor    
+

buildout.cfg

+; vim: set fileencoding=utf-8 :
+; Manuel Guenther <tiago.pereira@idiap.ch>
+; Thu Oct  9 16:51:06 CEST 2014
+
+[buildout]
+parts = scripts
+develop = .
+eggs = bob.ip.tensorflow_extractor
+
+extensions = bob.buildout
+auto-checkout = *
+
+; options for bob.buildout
+debug = false
+verbose = true
+newest = false
+
+[scripts]
+recipe = bob.buildout:scripts
+dependent-scripts = true

doc/conf.py

+#!/usr/bin/env python
+# vim: set fileencoding=utf-8 :
+
+import os
+import sys
+import glob
+import pkg_resources
+
+
+# -- General configuration -----------------------------------------------------
+
+# If your documentation needs a minimal Sphinx version, state it here.
+needs_sphinx = '1.3'
+
+# Add any Sphinx extension module names here, as strings. They can be extensions
+# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
+extensions = [
+    'sphinx.ext.todo',
+    'sphinx.ext.coverage',
+    'sphinx.ext.ifconfig',
+    'sphinx.ext.autodoc',
+    'sphinx.ext.autosummary',
+    'sphinx.ext.doctest',
+    'sphinx.ext.graphviz',
+    'sphinx.ext.intersphinx',
+    'sphinx.ext.napoleon',
+    'sphinx.ext.viewcode',
+    'matplotlib.sphinxext.plot_directive'
+    ]
+
+import sphinx
+if sphinx.__version__ >= "1.4.1":
+    extensions.append('sphinx.ext.imgmath')
+    imgmath_image_format = 'svg'
+else:
+    extensions.append('sphinx.ext.pngmath')
+
+# Be picky about warnings
+nitpicky = True
+
+# Ignores stuff we can't easily resolve on other project's sphinx manuals
+nitpick_ignore = []
+
+# Allows the user to override warnings from a separate file
+if os.path.exists('nitpick-exceptions.txt'):
+    for line in open('nitpick-exceptions.txt'):
+        if line.strip() == "" or line.startswith("#"):
+            continue
+        dtype, target = line.split(None, 1)
+        target = target.strip()
+        try: # python 2.x
+            target = unicode(target)
+        except NameError:
+            pass
+        nitpick_ignore.append((dtype, target))
+
+# Always includes todos
+todo_include_todos = True
+
+# Generates auto-summary automatically
+autosummary_generate = True
+
+# Create numbers on figures with captions
+numfig = True
+
+# If we are on OSX, the 'dvipng' path maybe different
+dvipng_osx = '/opt/local/libexec/texlive/binaries/dvipng'
+if os.path.exists(dvipng_osx): pngmath_dvipng = dvipng_osx
+