Corrected the scripts so that they now run with the latest version of Bob and...

Corrected the scripts so that they now run with the latest version of Bob and the xbob.db.atnt database.

buildout.cfg

@@ -6,6 +6,7 @@
 
 [buildout]
 parts = external python
+newest = false
 develop = .
 
 ; required packages: sphinx (to generate the documentation), bob, and our package.

faceverify/dct_ubm.py

@@ -16,7 +16,7 @@ ATNT_IMAGE_EXTENSION = ".pgm"
 def load_images(db, group = None, purpose = None, client_id = None):
   """Reads the images for the given group and the given client id from the given database"""
   # get the file names from the database
-  file_names = db.files(groups = group, purposes = purpose, client_ids = client_id, directory = ATNT_IMAGE_DIRECTORY, extension = ATNT_IMAGE_EXTENSION)
+  file_names = db.files(groups = group, purposes = purpose, model_ids = client_id, directory = ATNT_IMAGE_DIRECTORY, extension = ATNT_IMAGE_EXTENSION)
   # iterate through the list of file names
   images = {}
   for key, image_name in file_names.iteritems():
@@ -37,7 +37,7 @@ def extract_feature(image):
   """Extracts the DCT features for the given image"""
 
   # compute shape of the image blocks
-  block_shape = bob.ip.get_block_shape(image, DCT_BLOCK_SIZE, DCT_BLOCK_SIZE, DCT_BLOCK_OVERLAP, DCT_BLOCK_OVERLAP)
+  block_shape = bob.ip.get_block_3d_output_shape(image, DCT_BLOCK_SIZE, DCT_BLOCK_SIZE, DCT_BLOCK_OVERLAP, DCT_BLOCK_OVERLAP)
   image_blocks = numpy.ndarray(block_shape, 'float64')
 
   # fill image blocks
@@ -155,7 +155,7 @@ def main():
   gmm_trainer.set_prior_gmm(ubm)
 
   # create a GMM model for each model identity
-  model_ids = atnt_db.client_ids(groups = 'dev')
+  model_ids = atnt_db.clients(groups = 'dev')
   models = {}
   for model_id in model_ids:
     # load images for the current model id

faceverify/gabor_phase.py

@@ -97,7 +97,7 @@ def main():
 
   print "Computing scores"
   # define a certain Gabor jet similarity function that should be used
-  similarity_function = bob.machine.DisparityCorrectedPhaseDifference()
+  similarity_function = bob.machine.GaborJetSimilarity(bob.machine.gabor_jet_similarity_type.PHASE_DIFF)
 
   # iterate through models and probes and compute scores
   for model_key, model_feature in model_features.iteritems():

setup.py

@@ -49,7 +49,7 @@ setup(
     # TODO: Add a version number requirement to bob, when ready
     install_requires=[
         "sphinx",                     # to generate the documentation
-        "bob",                        # base signal proc./machine learning library
+        "bob >= 1.1.0a0",               # base signal proc./machine learning library
         "xbob.db.atnt",               # the AT&T (ORL) database of images
     ],