def get_features(fnames,
featfunc,
kernel_type = DEFAULT_SIMFUNC,
simfunc = DEFAULT_SIMFUNC,
info_str = 'the',
):
# --------------------------------------------------------------------------
# -- init
# load first vector to get dimensionality
fvector0 = get_fvector(fnames[0],
featfunc,
kernel_type,
simfunc=simfunc)
if kernel_type == "exp_mu_da":
# hack for GB with 204 dims
fvector0 = fvector0.reshape(-1, 204)
else:
fvector0 = fvector0.ravel()
featshape = fvector0.shape
featsize = fvector0.size
# -- helper function
# set up progress bar
def load_features(x_fnames, info_str):
print "-"*80
print "Loading %s data ..." % info_str
pbar = ProgressBar(widgets=widgets, maxval=len(x_fnames))
pbar.start()
x_features = sp.empty((len(x_fnames),) + featshape,
dtype='float32')
for i, one_or_two_fnames in enumerate(x_fnames):
fvector = get_fvector(one_or_two_fnames,
featfunc,
kernel_type,
simfunc=simfunc)
fvector = fvector.reshape(fvector0.shape)
x_features[i] = fvector
pbar.update(i+1)
pbar.finish()
print "-"*80
return x_features
# -- load features from filenames
try:
features = load_features(fnames, info_str=info_str)
except OverwriteError, err:
print err
def load_features(x_fnames, info_str):
print "-"*80
print "Loading %s data ..." % info_str
pbar = ProgressBar(widgets=widgets, maxval=len(x_fnames))
pbar.start()
x_features = sp.empty((len(x_fnames),) + featshape,
dtype='float32')
for i, one_or_two_fnames in enumerate(x_fnames):
fvector = get_fvector(one_or_two_fnames,
featfunc,
kernel_type,
simfunc=simfunc)
fvector = fvector.reshape(fvector0.shape)
x_features[i] = fvector
pbar.update(i+1)
pbar.finish()
print "-"*80
return x_features