Source code for bob.ip.caffe_extractor.VGGFace

#!/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 numpy
import os
from Extractor import Extractor
import bob.core
logger = bob.core.log.setup("bob.ip.caffe_extractor")
bob.core.log.set_verbosity_level(logger, 3)


[docs]class VGGFace(Extractor):
    """
    Extract features using the VGG model http://www.robots.ox.ac.uk/~vgg/software/vgg_face/
    """

    def __init__(self, end_cnn):
        """
        VGG constructor

        **Parameters**

         end_cnn: The name of the layer that you want to use as a feature
        """

        deploy_architecture = os.path.join(VGGFace.get_vggpath(), "vgg_face_caffe", "VGG_FACE_deploy.prototxt")
        model = os.path.join(VGGFace.get_vggpath(), "vgg_face_caffe", "VGG_FACE.caffemodel")

        # Average image provided in http://www.robots.ox.ac.uk/~vgg/software/vgg_face/
        self.average_img = [129.1863, 104.7624, 93.5940]

        if not os.path.exists(deploy_architecture) or not os.path.exists(model):
            VGGFace.download_vgg()

        super(VGGFace, self).__init__(
            deploy_architecture, model, end_cnn
        )

    def __call__(self, image):
        """
        Forward the image with the loaded neural network.

        **Parameters**
          image: Input image in RGB format

        **Returns**
            Features

        """

        # The input must be 1,c,w,h
        # if RGB
        if len(image.shape) == 3:
            R = image[0, :, :] - self.average_img[0]
            G = image[1, :, :] - self.average_img[1]
            B = image[2, :, :] - self.average_img[2]

            #Converting to
            bgr_image = numpy.zeros(shape=image.shape)
            bgr_image[0, :, :] = B
            bgr_image[1, :, :] = G
            bgr_image[2, :, :] = R

            return super(VGGFace, self).__call__(bgr_image)
        else:
            raise ValueError("Image should have 3 channels")

    @staticmethod
[docs]    def get_vggpath():
        import pkg_resources
        return pkg_resources.resource_filename(__name__, 'data')

    @staticmethod
[docs]    def download_vgg():
        """
        Download and extract the VGG files in ./bob/ip/caffe_extractor
        """
        import sys
        import os
        import tarfile
        logger.info("Downloading the VGG Face model from  database from http://www.robots.ox.ac.uk/~vgg/software/vgg_face/src/vgg_face_caffe.tar.gz ...")

        tmp_file = os.path.join(VGGFace.get_vggpath(), "vgg_face_caffe.tar.gz")
        #url = 'http://www.robots.ox.ac.uk/~vgg/software/vgg_face/src/vgg_face_caffe.tar.gz'
        url = 'http://beatubulatest.lab.idiap.ch/software/bob/packages/vgg_face_caffe.tar.gz'


        if sys.version_info[0] < 3:
            # python2 technique for downloading a file
            from urllib2 import urlopen
            with open(tmp_file, 'wb') as out_file:
                response = urlopen(url)
                out_file.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(tmp_file, 'wb') as out_file:
                    copyfileobj(response, out_file)
        # Unzip
        logger.info("Unziping in {0}".format(VGGFace.get_vggpath()))
        t = tarfile.open(fileobj=open(tmp_file), mode='r:gz')
        t.extractall(VGGFace.get_vggpath())
        t.close()