diff --git a/bob/ip/tensorflow_extractor/DrGanMSU.py b/bob/ip/tensorflow_extractor/DrGanMSU.py
index 298de65d9e9c110337157361f0fba588df72253d..65caaa1f422f538995484aa307b1f95773e9721b 100644
--- a/bob/ip/tensorflow_extractor/DrGanMSU.py
+++ b/bob/ip/tensorflow_extractor/DrGanMSU.py
@@ -6,9 +6,9 @@ import numpy
import tensorflow as tf
import os
from bob.extension import rc
-from bob.extension.rc_config import _saverc
-from . import download_file
import logging
+import bob.extension.download
+import bob.io.base
logger = logging.getLogger(__name__)
@@ -348,12 +348,21 @@ class DrGanMSUExtractor(object):
# If the path is not, set the default path
if model_path is None:
- model_path = self.get_modelpath()
+ model_path = self.get_modelpath()
# If does not exist, download
if not os.path.exists(model_path):
- self.download_model()
-
+ bob.io.base.create_directories_safe(DrGanMSUExtractor.get_modelpath())
+ zip_file = os.path.join(DrGanMSUExtractor.get_modelpath(),
+ "DR_GAN_model.zip")
+ urls = [
+ # This is a private link at Idiap to save bandwidth.
+ "http://beatubulatest.lab.idiap.ch/private/wheels/gitlab/"
+ "DR_GAN_model.zip",
+ ]
+
+ bob.extension.download.download_and_unzip(urls, zip_file)
+
self.saver = tf.train.Saver()
# Reestore either from the last checkpoint or from a particular checkpoint
if os.path.isdir(model_path):
@@ -381,46 +390,6 @@ class DrGanMSUExtractor(object):
return "bob.ip.tensorflow_extractor.drgan_modelpath"
- @staticmethod
- def download_model():
- """
- Download and extract the DrGanMSU files in bob/ip/tensorflow_extractor
- """
- import zipfile
- zip_file = os.path.join(DrGanMSUExtractor.get_modelpath(),
- "DR_GAN_model.zip")
- urls = [
- # This is a private link at Idiap to save bandwidth.
- "http://beatubulatest.lab.idiap.ch/private/wheels/gitlab/"
- "DR_GAN_model.zip",
- ]
-
- for url in urls:
- try:
- logger.info(
- "Downloading the DrGanMSU model from "
- "{} ...".format(url))
- download_file(url, zip_file)
- break
- except Exception:
- logger.warning(
- "Could not download from the %s url", url, exc_info=True)
- else: # else is for the for loop
- if not os.path.isfile(zip_file):
- raise RuntimeError("Could not download the zip file.")
-
- # Unzip
- logger.info("Unziping in {0}".format(DrGanMSUExtractor.get_modelpath()))
- with zipfile.ZipFile(zip_file) as myzip:
- myzip.extractall(os.path.dirname(DrGanMSUExtractor.get_modelpath()))
-
- logger.info("Saving the path `{0}` in the ~.bobrc file".format(DrGanMSUExtractor.get_modelpath()))
- rc[DrGanMSUExtractor.get_rcvariable()] = DrGanMSUExtractor.get_modelpath()
- _saverc(rc)
-
- # delete extra files
- os.unlink(zip_file)
-
def __call__(self, image):
"""__call__(image) -> feature
diff --git a/bob/ip/tensorflow_extractor/FaceNet.py b/bob/ip/tensorflow_extractor/FaceNet.py
index 4b2a8e16402ec644c07596051a4150d337f8b32d..169573c43d1d164b83a052f9e6526c6a45a8cbfe 100644
--- a/bob/ip/tensorflow_extractor/FaceNet.py
+++ b/bob/ip/tensorflow_extractor/FaceNet.py
@@ -6,10 +6,9 @@ import numpy
import tensorflow as tf
from bob.ip.color import gray_to_rgb
from bob.io.image import to_matplotlib
-from . import download_file
from bob.extension import rc
-from bob.extension.rc_config import _saverc
-
+import bob.extension.download
+import bob.io.base
logger = logging.getLogger(__name__)
@@ -77,7 +76,7 @@ class FaceNet(object):
def __init__(self,
model_path=rc["bob.ip.tensorflow_extractor.facenet_modelpath"],
image_size=160,
- **kwargs):
+ **kwargs):
super(FaceNet, self).__init__()
self.model_path = model_path
self.image_size = image_size
@@ -98,7 +97,19 @@ class FaceNet(object):
if self.model_path is None:
self.model_path = self.get_modelpath()
if not os.path.exists(self.model_path):
- self.download_model()
+ bob.io.base.create_directories_safe(FaceNet.get_modelpath())
+ zip_file = os.path.join(FaceNet.get_modelpath(),
+ "20170512-110547.zip")
+ urls = [
+ # This is a private link at Idiap to save bandwidth.
+ "http://beatubulatest.lab.idiap.ch/private/wheels/gitlab/"
+ "facenet_model2_20170512-110547.zip",
+ # this works for everybody
+ "https://drive.google.com/uc?export=download&id="
+ "0B5MzpY9kBtDVZ2RpVDYwWmxoSUk",
+ ]
+ bob.extension.download.download_and_unzip(urls, zip_file)
+
# code from https://github.com/davidsandberg/facenet
model_exp = os.path.expanduser(self.model_path)
if (os.path.isfile(model_exp)):
@@ -143,10 +154,20 @@ class FaceNet(object):
@staticmethod
def get_rcvariable():
+ """
+ Variable name used in the Bob Global Configuration System
+ https://www.idiap.ch/software/bob/docs/bob/bob.extension/stable/rc.html#global-configuration-system
+ """
return "bob.ip.tensorflow_extractor.facenet_modelpath"
@staticmethod
def get_modelpath():
+ """
+ Get default model path.
+
+ First we try the to search this path via Global Configuration System.
+ If we can not find it, we set the path in the directory `<project>/data`
+ """
# Priority to the RC path
model_path = rc[FaceNet.get_rcvariable()]
@@ -158,46 +179,3 @@ class FaceNet(object):
return model_path
-
- @staticmethod
- def download_model():
- """
- Download and extract the FaceNet files in bob/ip/tensorflow_extractor
- """
- import zipfile
- zip_file = os.path.join(FaceNet.get_modelpath(),
- "20170512-110547.zip")
- urls = [
- # This is a private link at Idiap to save bandwidth.
- "http://beatubulatest.lab.idiap.ch/private/wheels/gitlab/"
- "facenet_model2_20170512-110547.zip",
- # this works for everybody
- "https://drive.google.com/uc?export=download&id="
- "0B5MzpY9kBtDVZ2RpVDYwWmxoSUk",
- ]
-
- for url in urls:
- try:
- logger.info(
- "Downloading the FaceNet model from "
- "{} ...".format(url))
- download_file(url, zip_file)
- break
- except Exception:
- logger.warning(
- "Could not download from the %s url", url, exc_info=True)
- else: # else is for the for loop
- if not os.path.isfile(zip_file):
- raise RuntimeError("Could not download the zip file.")
-
- # Unzip
- logger.info("Unziping in {0}".format(FaceNet.get_modelpath()))
- with zipfile.ZipFile(zip_file) as myzip:
- myzip.extractall(os.path.dirname(FaceNet.get_modelpath()))
-
- logger.info("Saving the path `{0}` in the ~.bobrc file".format(FaceNet.get_modelpath()))
- rc[FaceNet.get_rcvariable()] = FaceNet.get_modelpath()
- _saverc(rc)
-
- # delete extra files
- os.unlink(zip_file)
diff --git a/bob/ip/tensorflow_extractor/__init__.py b/bob/ip/tensorflow_extractor/__init__.py
index af38dd5d05ed6e9ecafa7566084675b14ab965ac..7c21c731ff30b44f2251770f3417ec6188982780 100755
--- a/bob/ip/tensorflow_extractor/__init__.py
+++ b/bob/ip/tensorflow_extractor/__init__.py
@@ -26,37 +26,6 @@ def scratch_network(inputs, end_point="fc1", reuse=False):
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.
- """
- from bob.io.base import create_directories_safe
- import os
- create_directories_safe(os.path.dirname(out_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)
-
-
def get_config():
"""Returns a string containing the configuration information.
"""
diff --git a/bob/ip/tensorflow_extractor/test.py b/bob/ip/tensorflow_extractor/test.py
index 67414c54e62d8ff66adfc514b5e1683c586a41f6..78955e626ad4cfe4dfe599b1ada0de36bdd17cad 100644
--- a/bob/ip/tensorflow_extractor/test.py
+++ b/bob/ip/tensorflow_extractor/test.py
@@ -47,41 +47,9 @@ def test_facenet():
assert output.size == 128, output.shape
def test_drgan():
- """
- '/remote/idiap.svm/user.active/heusch/work/dev/DR-GAN_code_wmodel/DR_GAN_model/DCGAN.model-590000'
- """
from bob.ip.tensorflow_extractor import DrGanMSUExtractor
- #extractor = DrGanMSUExtractor("/idiap/project/hface/models/cnn/DR_GAN_model/", image_size=[96, 96, 3])
extractor = DrGanMSUExtractor()
data = numpy.random.rand(3, 96, 96).astype("uint8")
output = extractor(data)
assert output.size == 320, output.shape
-
-
-"""
-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
-"""