import os.path
from cvpr_build_models_frgc import build_all_models_frgc
from sfs_io import load_frgc
celebrities_path = '/home/pts08/research/sfs/celebrities'
#celebrity_subjects = ['clint_eastwood', 'gerard_depardieu', 'jack_nicholson',
# 'jude_law', 'mona_lisa', 'samuel_beckett', 'tom_cruise',
# 'tom_hanks']
# 'jude_law' is too big an image
celebrity_subjects = ['mona_lisa', 'samuel_beckett', 'tom_cruise', 'tom_hanks']
print "Loading FRGC"
images = load_frgc('spring2003')
for subject in celebrity_subjects:
base_path = os.path.join(celebrities_path, subject + '.png')
build_all_models_frgc(images, base_path, subject)
sys.stdout.flush()
# <markdowncell>
# ## Load all the aligned shapes from the dataset
# <codecell>
RECREATE_MESHES = False
# <codecell>
from sfs_io import load_frgc
images = load_frgc('spring2003', RECREATE_MESHES)
# <codecell>
def extract_normals(images):
vector_shape = images[0].mesh.vertex_normals.shape
N = len(images)
normals = np.zeros([N, vector_shape[0], vector_shape[1]])
for i, im in enumerate(images):
normals[i, ...] = im.mesh.vertex_normals
return normals
# <codecell>
sys.stdout.write('\r' + string)
sys.stdout.flush()
# <markdowncell>
# ## Load all the aligned shapes from the dataset
# <codecell>
RECREATE_MESHES = False
# <codecell>
from sfs_io import load_frgc
images = load_frgc('spring2003', RECREATE_MESHES)
# <codecell>
def extract_normals(images):
vector_shape = images[0].mesh.vertex_normals.shape
N = len(images)
normals = np.zeros([N, vector_shape[0], vector_shape[1]])
for i, im in enumerate(images):
normals[i, ...] = im.mesh.vertex_normals
return normals
# <codecell>
def create_feature_space(feature_matrix, example_image, feature_space_name):
feature_space_images = []
import os.path
from cvpr_build_models_frgc import build_all_models_frgc
from sfs_io import load_frgc
celebrities_path = '/home/pts08/research/sfs/celebrities'
#celebrity_subjects = ['clint_eastwood', 'gerard_depardieu', 'jack_nicholson',
# 'jude_law', 'mona_lisa', 'samuel_beckett', 'tom_cruise',
# 'tom_hanks']
# 'jude_law' is too big an image
celebrity_subjects = ['mona_lisa', 'samuel_beckett', 'tom_cruise',
'tom_hanks']
print "Loading FRGC"
images = load_frgc('spring2003')
for subject in celebrity_subjects:
base_path = os.path.join(celebrities_path, subject + '.png')
build_all_models_frgc(images, base_path, subject)
