Beispiel #1
0
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
Beispiel #2
0
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