def derts2blobs(dert__, verbose=False, render=False, use_c=False):
if verbose:
start_time = time()
if use_c:
dert__ = dert__[0], np.empty(0), np.empty(0), *dert__[1:], np.empty(0)
frame, idmap, adj_pairs = wrapped_flood_fill(dert__)
else:
blob_, idmap, adj_pairs = flood_fill(dert__,
sign__=dert__[3] > 0, # sign of deviation of gradient
# g__ was not signed, we used dy__ sign instead
verbose=verbose)
I = Dy = Dx = G = M = 0
for blob in blob_:
I += blob.I
Dy += blob.Dy
Dx += blob.Dx
G += blob.G
M += blob.M
frame = FrameOfBlobs(I=I, Dy=Dy, Dx=Dx, G=G, M=M, blob_=blob_, dert__=dert__)
assign_adjacents(adj_pairs)
if verbose:
print(f"{len(frame.blob_)} blobs formed in {time() - start_time} seconds")
if render:
visualize_blobs(idmap, frame.blob_)
return frame
def cluster_derts(dert__, mask, Ave, fcr, fca, verbose=False, **kwargs):
if fca:
crit__ = Ave - dert__[3] # temporary crit
elif fcr: # comp_r output; form clustering criterion:
crit__ = Ave - dert__[3] # eval by -g, accum in rng
else:
crit__ = Ave - dert__[3] # eval by -g, accum in rng
if kwargs.get('use_c'):
raise NotImplementedError
(_, _, _, blob_, _), idmap, adj_pairs = flood_fill()
else:
blob_, idmap, adj_pairs = flood_fill(dert__,
sign__=crit__ > 0,
verbose=verbose,
mask=mask,
blob_cls=CDeepBlob,
accum_func=accum_blob_Dert)
assign_adjacents(adj_pairs, CDeepBlob)
if kwargs.get('render', False):
visualize_blobs(idmap,
blob_,
winname=f"Deep blobs (fcr = {fcr}, fig = {fig})")
return blob_
def cluster_derts(dert__, mask, Ave, fcr, fig, verbose=False, **kwargs):
if fcr: # comp_r output; form clustering criterion:
if fig:
crit__ = dert__[0] + dert__[
6] - Ave # eval by i + m, accum in rng; dert__[:,:,0] if not transposed
else:
crit__ = Ave - dert__[3] # eval by -g, accum in rng
else: # comp_g output
crit__ = dert__[
6] - Ave # comp_g output eval by m, or clustering is always by m?
if kwargs.get('use_c'):
raise NotImplementedError
(_, _, _, blob_, _), idmap, adj_pairs = flood_fill()
else:
blob_, idmap, adj_pairs = flood_fill(dert__,
sign__=crit__ > 0,
verbose=verbose,
mask=mask,
blob_cls=CDeepBlob,
accum_func=accum_blob_Dert)
assign_adjacents(adj_pairs, CDeepBlob)
if kwargs.get('render', False):
visualize_blobs(idmap,
blob_,
winname=f"Deep blobs (fcr = {fcr}, fig = {fig})")
return blob_
def cluster_derts(dert__, crit__, mask, verbose=False, **kwargs):
# this is function should be folded into flood_fill()
''' obsolete define clustering criterion:
if fia: # input is from comp_a
if fca: # comp_a eval by g / cos(ga)
crit__ = dert__[3] / np.cos(dert__[7]) - Ave # combined value, no comp_r: no use for ma?
else: # P_blobs eval by g * cos(ga)
crit__ = dert__[3] * np.cos(dert__[7]) - Ave # separate from g and ga
else: # input is from comp_r
if fca: # comp_a eval by g
crit__ = dert__[3] - Ave
else: # comp_r eval by m
crit__ = dert__[4] - Ave
'''
if kwargs.get('use_c'):
raise NotImplementedError
(_, _, _, blob_, _), idmap, adj_pairs = flood_fill()
else:
blob_, idmap, adj_pairs = flood_fill(dert__,
sign__=crit__ > 0,
verbose=verbose,
mask=mask,
blob_cls=CDeepBlob,
accum_func=accum_blob_Dert)
assign_adjacents(adj_pairs, CDeepBlob)
if kwargs.get('render', False):
visualize_blobs(idmap,
blob_,
winname=f"Deep blobs (fcr = {fcr}, fia = {fia})")
return blob_