def _pyramid(store, key, new, pars):
"""Pyramid store.
"""
# this needs the cv module from osdf.
chunk, schema, params = pars[0], pars[1], pars[2]
depth = 0
if schema is "laplace":
from osdfcv.pyramid.laplacian import build_pil
build_pyr = build_pil
depth = params[0]
elif schema is "lcn":
from osdfcv.pyramid.lcn import build_pil
depth, width, sigma = params
shape = store[key].shape
dx = int(np.sqrt(shape[1]))
shape = (dx, dx)
lcns = _build_lcns(shape, depth, width, sigma)
from functools import partial
build_pyr = partial(build_pil, lcns=lcns)
elif schema is "fovea":
from osdfcv.pyramid.fovea import build
depth = params[0]
build_pyr = build
else:
assert False, "Don't know pyramid schmema %s"%schema
assert depth > 0, "Need a decent depth: %d"%depth
# collect inputs in group
grp = new.create_group(name=key)
dsets = []
dtype = store[key].dtype
shape = store[key].shape
dx = int(np.sqrt(shape[1]))
for d in xrange(depth):
dsets.append(grp.create_dataset(name=key+str(d), shape=shape, dtype=dtype))
shape = (shape[0], shape[1]/4)
k = 0 # global counter, not nice
for i in xrange(0, store[key].shape[0], chunk):
for l in store[key][i:i+chunk]:
pyramid = build_pyr(l.reshape(dx, dx), depth)
for j, img in enumerate(pyramid):
dsets[j][k] = img.ravel()
k = k + 1
for attrs in store.attrs:
grp.attrs[attrs] = store.attrs[attrs]
for d in xrange(depth):
dsets[d].attrs["patch_shape"] = (dx, dx)
dx = dx/2
grp.attrs['depth'] = depth
grp.attrs['schema'] = schema
def _pyramid_fuse(store, key, new, pars):
"""Pyramid store. All stages of a pyramid
fused into one row vector.
"""
# this needs the cv module from osdf.
chunk, schema, shapes = pars[0], pars[1], pars[2]
depth = len(shapes)
if schema is "laplace":
from osdfcv.pyramid.laplacian import build_pil
dtype = store[key].dtype
n, x = store[key].shape
dx = int(np.sqrt(x))
shape = 0
for sh in shapes:
shape = shape + sh[0]*sh[1]
dset = new.create_dataset(name=key+"_pyr", shape=(n, shape), dtype=dtype)
k = 0 # global counter, not nice
for i in xrange(0, store[key].shape[0], chunk):
for l in store[key][i:i+chunk]:
pyramid = build_pil(l.reshape(dx, dx), depth)
start = 0
for j, img in enumerate(pyramid):
stop = start + shapes[j][0]*shapes[j][1]
dset[k][start:stop] = img.ravel()
print dset[k]
start = stop
k = k + 1
print k
for attrs in store.attrs:
new.attrs[attrs] = store.attrs[attrs]
new.attrs['depth'] = depth
new.attrs['schema'] = schema
