Replaced the download_model method to the new one implemented in bob.extension

Updated URLs

Updated URLs

Fixed download method

Fixing import

Created the directory automatically

bob/ip/tensorflow_extractor/DrGanMSU.py

@@ -6,9 +6,10 @@ 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 +349,21 @@ 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://www.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 +391,6 @@ 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
 

bob/ip/tensorflow_extractor/FaceNet.py

@@ -8,8 +8,8 @@ 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__)
 
@@ -98,7 +98,21 @@ 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://www.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)):
@@ -158,46 +172,3 @@ 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)

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
-"""