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 (fca = {fca}, fia = {fia})")
return blob_
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 segment_by_direction(iblob, **kwargs):
verbose = kwargs.get('verbose')
render = kwargs.get('render')
dert__ = list(iblob.dert__)
mask__ = iblob.mask__
dy__ = dert__[1]
dx__ = dert__[2]
# segment blob into primarily vertical and horizontal sub blobs according to the direction of kernel-level gradient:
dir_blob_, idmap, adj_pairs = \
flood_fill(dert__, abs(dy__) > abs(dx__), verbose=verbose, mask__=mask__, blob_cls=CBlob, fseg=True, accum_func=accum_dir_blob_Dert)
assign_adjacents(adj_pairs, CBlob) # fseg=True: skip adding the pose
if render:
_dir_blob_ = deepcopy(
dir_blob_
) # get a copy for dir blob before merging, for visualization purpose
merged_ids = [
] # ids of merged adjacent blobs, to skip in the rest of dir_blobs
for i, blob in enumerate(dir_blob_):
if blob.id not in merged_ids:
blob = merge_adjacents_recursive(blob,
merged_ids,
blob.adj_blobs[0],
strong_adj_blobs=[]) # no pose
if (blob.Dert.M >
ave_M) and (blob.box[1] - blob.box[0] >
1): # y size >1, else we can't form derP
blob.fsliced = True
slice_blob(
blob, verbose
) # slice and comp_slice_ across directional sub-blob
iblob.dir_blobs.append(blob)
for dir_blob in iblob.dir_blobs:
if dir_blob.id in merged_ids: # strong blob was merged to another blob, remove it
iblob.dir_blobs.remove(dir_blob)
if render:
visualize_merging_process(iblob, dir_blob_, _dir_blob_, mask__, i)
if render:
# for debugging: visualize adjacents of merged blob to see that adjacents are assigned correctly after the merging:
if len(dir_blob_) > 50 and len(dir_blob_) < 500:
new_idmap = (np.zeros_like(idmap).astype('int')) - 2
for blob in iblob.dir_blobs:
y0, yn, x0, xn = blob.box
new_idmap[y0:yn, x0:xn] += (~blob.mask__) * (blob.id + 2)
visualize_merging_process(iblob, dir_blob_, _dir_blob_, mask__, 0)
from draw_frame_blobs import visualize_blobs
visualize_blobs(new_idmap, iblob.dir_blobs)
def cluster_sub_eval(blob, dert__, sign__, mask__, render,
verbose): # comp_r or comp_a eval per sub_blob:
AveB = aveB * blob.rdn
sub_blobs, idmap, adj_pairs = flood_fill(dert__,
sign__,
verbose=False,
mask__=mask__,
blob_cls=CBlob)
assign_adjacents(adj_pairs, CBlob)
if render:
visualize_blobs(
idmap,
sub_blobs,
winname=
f"Deep blobs (f_comp_a = {blob.f_comp_a}, f_root_a = {blob.prior_forks[-1] == 'a'})"
)
blob.Ls = len(sub_blobs) # for visibility and next-fork rdn
blob.sublayers = [sub_blobs] # 1st layer of sub_blobs
for sub_blob in sub_blobs: # evaluate sub_blob
sub_blob.prior_forks = blob.prior_forks.copy(
) # increments forking sequence: m->r, g->a, a->p
# min size in y and x, at least one dert in dert__:
if sub_blob.mask__.shape[0] > 2 and sub_blob.mask__.shape[
1] > 2 and False in sub_blob.mask__:
# p fork:
if sub_blob.prior_forks[-1] == 'a':
if -sub_blob.M * sub_blob.Ma > AveB * pcoef:
sub_blob.prior_forks.extend('p')
if verbose: print('\nslice_blob fork\n')
segment_by_direction(sub_blob, verbose=True)
else: # a fork or r fork:
'''
G = blob.G # Gr, Grr...
adj_M = blob.adj_blobs[3] # adj_M is incomplete, computed within current dert_only, use root blobs instead:
adjacent valuable blobs of any sign are tracked from frame_blobs to form borrow_M?
track adjacency of sub_blobs: wrong sub-type but right macro-type: flat blobs of greater range?
G indicates or dert__ extend per blob G?
borrow_M = min(G, adj_M / 2): usually not available, use average
'''
if -sub_blob.M > AveB: # replace with borrow_M when known
# comp_a:
sub_blob.rdn = sub_blob.rdn + 1 + 1 / blob.Ls
blob.sublayers += comp_angle(sub_blob, render, verbose)
elif sub_blob.M > AveB:
# comp_r:
sub_blob.rng = blob.rng
sub_blob.rdn = sub_blob.rdn + 1 + 1 / blob.Ls
blob.sublayers += comp_range(sub_blob, render, verbose)
def cluster_sub_eval(blob, dert__, sign__, mask__,
**kwargs): # comp_r or comp_a eval per sub_blob:
AveB = aveB * blob.rdn
sub_blobs, idmap, adj_pairs = flood_fill(dert__,
sign__,
verbose=False,
mask__=mask__,
blob_cls=CBlob,
accum_func=accum_blob_Dert)
assign_adjacents(adj_pairs, CBlob)
if kwargs.get('render', False):
visualize_blobs(
idmap,
sub_blobs,
winname=
f"Deep blobs (f_comp_a = {blob.f_comp_a}, f_root_a = {blob.f_root_a})"
)
blob.Ls = len(sub_blobs) # for visibility and next-fork rdn
blob.sub_layers = [sub_blobs] # 1st layer of sub_blobs
for sub_blob in sub_blobs: # evaluate sub_blob
G = blob.G # Gr, Grr...
adj_M = blob.adj_blobs[
3] # adj_M is incomplete, computed within current dert_only, use root blobs instead:
# adjacent valuable blobs of any sign are tracked from frame_blobs to form borrow_M?
# track adjacency of sub_blobs: wrong sub-type but right macro-type: flat blobs of greater range?
# G indicates or dert__ extend per blob G?
borrow_M = min(G, adj_M / 2)
sub_blob.prior_forks = blob.prior_forks.copy(
) # increments forking sequence: g->a, g->a->p, etc.
if sub_blob.G > AveB: # replace with borrow_M when known
# comp_a:
sub_blob.f_root_a = 1
sub_blob.a_depth += blob.a_depth # accumulate a depth from blob to sub_blob, currently not used
sub_blob.rdn = sub_blob.rdn + 1 + 1 / blob.Ls
blob.sub_layers += intra_blob(sub_blob, **kwargs)
elif sub_blob.M - borrow_M > AveB:
# comp_r:
sub_blob.rng = blob.rng * 2
sub_blob.rdn = sub_blob.rdn + 1 + 1 / blob.Ls
blob.sub_layers += intra_blob(sub_blob, **kwargs)
def cluster_fork_recursive(blob, spliced_layers, new_dert__, sign__,
new_mask__, verbose, render, fBa):
if verbose:
if fBa: print('\na fork\n')
else: print('\nr fork\n')
# form sub_blobs:
sub_blobs, idmap, adj_pairs = flood_fill(new_dert__,
sign__,
verbose=False,
mask__=new_mask__.fill(False))
'''
adjust per average sub_blob, depending on which fork is weaker, or not taken at all:
sub_blob.rdn += 1 -|+ min(sub_blob_val, alt_blob_val) / max(sub_blob_val, alt_blob_val):
+ if sub_blob_val > alt_blob_val, else -?
'''
adj_rdn = ave_nsub - len(
sub_blobs
) # adjust ave cross-layer rdn to actual rdn after flood_fill:
blob.rdn += adj_rdn
for sub_blob in sub_blobs:
sub_blob.rdn += adj_rdn
assign_adjacents(adj_pairs)
if render:
visualize_blobs(
idmap,
sub_blobs,
winname=
f"Deep blobs (froot_Ba = {blob.fBa}, froot_Ba = {blob.prior_forks[-1] == 'a'})"
)
if fBa: sublayers = blob.asublayers
else: sublayers = blob.rsublayers
sublayers += [
sub_blobs
] # r|a fork- specific sub_blobs, then add deeper layers of mixed-fork sub_blobs:
sublayers += intra_blob_root(
blob, render, verbose,
fBa) # recursive eval cross-comp range| angle| slice per blob
spliced_layers = [
spliced_layer + sublayer for spliced_layer, sublayer in zip_longest(
spliced_layers, sublayers, fillvalue=[])
]
return spliced_layers