def single_segment_as_gif(segment,
directory="/tmp/online_matcher/visuals/animated/", frames=60, black_and_white=False):
import os
if not os.path.exists(directory):
os.makedirs(directory)
import voxelize
rotations = voxelize.create_rotations([voxelize.recenter_segment(segment)], n_angles=frames)
segments_as_gif(rotations, filename='segment',
directory=directory, black_and_white=black_and_white)
def single_segment_as_gif(segment,
directory="/tmp/online_matcher/visuals/animated/", frames=60, black_and_white=False):
import os
if not os.path.exists(directory):
os.makedirs(directory)
import voxelize
rotations = voxelize.create_rotations([voxelize.recenter_segment(segment)], n_angles=frames)
segments_as_gif(rotations, filename='segment',
directory=directory, black_and_white=black_and_white)
def single_segment_rotations_reconstruction_as_gif(segment, vae, confidence=0.3,
directory="/tmp/online_matcher/visuals/animated/",
frames=120, black_and_white=False):
import os
if not os.path.exists(directory):
os.makedirs(directory)
import voxelize
rotations = voxelize.create_rotations([segment], n_angles=frames)
import autoencoder.model
VOXEL_SIDE = vae.MP.INPUT_SHAPE[0]
rotations_vox, features_voxel_scale = voxelize.voxelize(rotations, VOXEL_SIDE)
reconstruction_vox = vae.batch_encode_decode([np.reshape(sample, vae.MP.INPUT_SHAPE) for sample in rotations_vox], batch_size=120)
reconstruction_vox = [np.reshape(vox, [VOXEL_SIDE, VOXEL_SIDE, VOXEL_SIDE]) for vox in reconstruction_vox]
from voxelize import unvoxelize
reconstruction = [unvoxelize(vox > confidence) for vox in reconstruction_vox]
reconstruction = [voxelize.recenter_segment(segment*scale) for (segment, scale) in zip(reconstruction, features_voxel_scale)]
segments_as_gif(reconstruction, rotate_YP=(2*np.pi/frames), filename='reconstruction_rot',
directory=directory, black_and_white=black_and_white)
def single_segment_rotations_reconstruction_as_gif(segment, vae, confidence=0.3,
directory="/tmp/online_matcher/visuals/animated/",
frames=120, black_and_white=False):
import os
if not os.path.exists(directory):
os.makedirs(directory)
import voxelize
rotations = voxelize.create_rotations([segment], n_angles=frames)
import autoencoder.model
VOXEL_SIDE = vae.MP.INPUT_SHAPE[0]
rotations_vox, features_voxel_scale = voxelize.voxelize(rotations, VOXEL_SIDE)
reconstruction_vox = vae.batch_encode_decode([np.reshape(sample, vae.MP.INPUT_SHAPE) for sample in rotations_vox], batch_size=120)
reconstruction_vox = [np.reshape(vox, [VOXEL_SIDE, VOXEL_SIDE, VOXEL_SIDE]) for vox in reconstruction_vox]
from voxelize import unvoxelize
reconstruction = [unvoxelize(vox > confidence) for vox in reconstruction_vox]
reconstruction = [voxelize.recenter_segment(segment*scale) for (segment, scale) in zip(reconstruction, features_voxel_scale)]
segments_as_gif(reconstruction, rotate_YP=(2*np.pi/frames), filename='reconstruction_rot',
directory=directory, black_and_white=black_and_white)
def single_segment_degeneration_as_gif(
segment,
vae,
confidence=0.3,
directory="/tmp/online_matcher/visuals/animated/",
frames=60,
black_and_white=False):
import os
if not os.path.exists(directory):
os.makedirs(directory)
import voxelize
import autoencoder.model
VOXEL_SIDE = vae.MP.INPUT_SHAPE[0]
segment_vox, features_voxel_scale = voxelize.voxelize([segment],
VOXEL_SIDE)
segment_vox = [
np.reshape(sample, vae.MP.INPUT_SHAPE) for sample in segment_vox
]
for i in range(frames):
reconstruction_vox = vae.batch_encode_decode(
reconstruction_vox) if i > 0 else segment_vox
degen_vox = degen_vox + list(reconstruction_vox) if i > 0 else list(
reconstruction_vox)
degen_vox = [
np.reshape(vox, [VOXEL_SIDE, VOXEL_SIDE, VOXEL_SIDE])
for vox in degen_vox
]
from voxelize import unvoxelize
reconstruction = [unvoxelize(vox > confidence) for vox in degen_vox]
reconstruction = [
voxelize.recenter_segment(segment * features_voxel_scale[0])
for segment in reconstruction
]
print(len(reconstruction))
segments_as_gif(reconstruction,
rotate_YP=0,
filename='degeneration',
directory=directory,
black_and_white=black_and_white)
def single_segment_degeneration_as_gif(segment, vae, confidence=0.3,
directory="/tmp/online_matcher/visuals/animated/",
frames=60, black_and_white=False):
import os
if not os.path.exists(directory):
os.makedirs(directory)
import voxelize
import autoencoder.model
VOXEL_SIDE = vae.MP.INPUT_SHAPE[0]
segment_vox, features_voxel_scale = voxelize.voxelize([segment], VOXEL_SIDE)
segment_vox = [np.reshape(sample, vae.MP.INPUT_SHAPE) for sample in segment_vox]
for i in range(frames):
reconstruction_vox = vae.batch_encode_decode(reconstruction_vox) if i > 0 else segment_vox
degen_vox = degen_vox + list(reconstruction_vox) if i > 0 else list(reconstruction_vox)
degen_vox = [np.reshape(vox, [VOXEL_SIDE, VOXEL_SIDE, VOXEL_SIDE]) for vox in degen_vox]
from voxelize import unvoxelize
reconstruction = [unvoxelize(vox > confidence) for vox in degen_vox]
reconstruction = [voxelize.recenter_segment(segment*features_voxel_scale[0]) for segment in reconstruction]
print(len(reconstruction))
segments_as_gif(reconstruction, rotate_YP=0, filename='degeneration',
directory=directory, black_and_white=black_and_white)