print("Edge detection ... ", end="")
Da, Sa, Ea = algo.edgy(Ka,
channel=se['channel'],
threshold=se['threshold'],
blur=se['blur'],
dolines=se['dolines'])
Db, Sb, Eb = algo.edgy(Kb,
channel=se['channel'],
threshold=se['threshold'],
blur=se['blur'],
dolines=se['dolines'])
print("done")
# CoM detection
print("A ", end="")
com_a = algo.commie(Sa)
print("B ", end="")
com_b = algo.commie(Sb)
# Basic trajectory
nodes_ab = algo.seed(com_a, com_b, h, w)
nodes_ba = nodes_ab[:, [2, 3, 0, 1]]
nodes_i = 0.5 * (nodes_ab[:, [0, 1]] + nodes_ab[:, [2, 3]])
# Warp
print("Warping ...", end="")
Wa, posi_a = algo.deform(Ka, nodes_ab, 0.5, com_a, com_b)
Wb, posi_b = algo.deform(Kb, nodes_ba, 0.5, com_b, com_a)
print("done")
# Apply solid background color
def silhouette(settings, k, recycle=False, K=None, X=None, Y=None,
showsil=True, showedge=True, showcom=True):
"""
Perform silhouette extraction and contour detection for frame *k*.
These analysis files are generated:
- silly.png silhouette shape binary map.
- edgy.png silhouette edges binary map.
- com.json silhouette center of mass properties.
- shape.png silhouette detection diagram (returned for preview).
Usage
-----
>>> f, K, E, com = silhouette(settings, k)
Returns
-------
1. Filename of diagnostics chart
2. Key frame bitmap
3. Edge map
4. Center of mass properties
"""
# This is where the action is
folder = path.join(settings['temppath'], 'k{0:03d}'.format(k + 1))
f = path.join(folder, 'shape.png')
# Fetch ingredients
se = settings['edge']
sr = settings['render']
bc = None if sr['autoback'] else sr['backcolor']
if K is None: K = algo.load_rgba(settings['keyframes'][k])
# Do we need to do anything at all?
if recycle and path.isfile(f) and \
path.isfile(path.join(folder, 'com.json' )) and \
path.isfile(path.join(folder, 'silly.png')) and \
path.isfile(path.join(folder, 'edgy.png' )):
return f, K, None, None
# Make mesh grid
if X is None or Y is None: X, Y = algo.grid(K)
# Extract silhouette
D, S, E = algo.edgy(K,
backcolor = bc,
linecolor = sr['linecolor'],
dolines = sr['lineart' ],
threshold = se['threshold'][k] * 0.01,
channel = se['channel' ][k],
doscharr = se['scharr' ][k],
blur = se['blur' ][k],
invert = se['invert' ][k])
# Center of mass measurement
com = algo.commie(S, X=X, Y=Y, verbose=False)
# Save the harvest
saveit(com, path.join(folder, 'com.json' ))
saveit(S , path.join(folder, 'silly.png'))
saveit(E , path.join(folder, 'edgy.png' ))
# Combine all results into one classy chart
Sp = S if showsil else None
Ep = E if showedge else None
comp = com if showcom else None
fig = algo.big_figure('MuddyMorph - Silhouette Chart', *E.shape)
algo.edgeplot(D, Sp, Ep, comp, X=X, Y=Y)
plt.axis('off')
plt.savefig(f, **chartopts)
plt.close(fig)
return f, K, E, com
D, S, E = algo.edgy(K,
channel=channel,
threshold=threshold,
blur=blur,
dolines=dolines,
doscharr=doscharr)
stopwatch += time()
print("\t{} edge points".format(E.sum()))
print("\tDone in {0:.3f}s\n".format(stopwatch))
#%% Center of mass
print("Center of mass computation ...\n\t", end="")
stopwatch = -time()
com = algo.commie(S)
stopwatch += time()
print("\tDone in {0:.3f}s\n".format(stopwatch))
#%% Detect silhouette key points
print("Detecting silhouette points ...", end="")
stopwatch = -time()
nodes0 = algo.seed(*E.shape, com, com)
base = nodes0[4:]
sp = algo.spawn(E, base[:, [0, 1]], spawnpoints, r_min=simisize)
stopwatch += time()
print("\t{} silhouette points".format(len(sp)))
print("\tDone in {0:.3f}s\n".format(stopwatch))
print("Loading image ... ", end="")
K = algo.load_rgba(settings['keyframes'][0])
h, w = K.shape[:2]
print("done")
# Edge detection
print("Edge detection ... ", end="")
D, S, E = algo.edgy(K,
channel = se['channel' ],
threshold = se['threshold'],
blur = se['blur' ],
dolines = se['dolines' ])
print("done")
# CoM detection
com = algo.commie(S)
base = algo.seed(com, com, *S.shape)[:, :2]
# Pick edge points
print("Picking {} edge points ... ".format(n), end="")
stopwatch = - time()
kp = algo.spawn(E, base, n)
stopwatch += time()
print("done in {0:.0f} ms".format(stopwatch * 1000.))
##########
# Review #
##########
print("Plotting result ... ", end="")
