def compute_depthmap(arguments):
"""Compute depthmap for a single shot."""
data, reconstruction, neighbors, min_depth, max_depth, shot = arguments
method = data.config['depthmap_method']
if data.raw_depthmap_exists(shot.id):
logger.info("Using precomputed raw depthmap {}".format(shot.id))
return
logger.info("Computing depthmap for image {0} with {1}".format(
shot.id, method))
de = csfm.DepthmapEstimator()
de.set_depth_range(min_depth, max_depth, 100)
de.set_patchmatch_iterations(data.config['depthmap_patchmatch_iterations'])
de.set_min_patch_sd(data.config['depthmap_min_patch_sd'])
add_views_to_depth_estimator(data, reconstruction, neighbors[shot.id], de)
if (method == 'BRUTE_FORCE'):
depth, plane, score, nghbr = de.compute_brute_force()
elif (method == 'PATCH_MATCH'):
depth, plane, score, nghbr = de.compute_patch_match()
elif (method == 'PATCH_MATCH_SAMPLE'):
depth, plane, score, nghbr = de.compute_patch_match_sample()
else:
raise ValueError('Unknown depthmap method type ' \
'(must be BRUTE_FORCE, PATCH_MATCH or PATCH_MATCH_SAMPLE)')
good_score = score > data.config['depthmap_min_correlation_score']
depth = depth * (depth < max_depth) * good_score
# Save and display results
data.save_raw_depthmap(shot.id, depth, plane, score, nghbr,
neighbors[shot.id][1:])
if data.config['depthmap_save_debug_files']:
image = data.undistorted_image_as_array(shot.id)
image = scale_down_image(image, depth.shape[1], depth.shape[0])
ply = depthmap_to_ply(shot, depth, image)
with open(data._depthmap_file(shot.id, 'raw.npz.ply'), 'w') as fout:
fout.write(ply)
if data.config.get('interactive'):
import matplotlib.pyplot as plt
plt.figure()
plt.suptitle("Shot: " + shot.id + ", neighbors: " +
', '.join(neighbors[shot.id][1:]))
plt.subplot(2, 3, 1)
plt.imshow(image)
plt.subplot(2, 3, 2)
plt.imshow(color_plane_normals(plane))
plt.subplot(2, 3, 3)
plt.imshow(depth)
plt.colorbar()
plt.subplot(2, 3, 4)
plt.imshow(score)
plt.colorbar()
plt.subplot(2, 3, 5)
plt.imshow(nghbr)
plt.colorbar()
plt.show()
def compute_depthmap(arguments):
"""Compute depthmap for a single shot."""
log.setup()
data, neighbors, min_depth, max_depth, shot = arguments
method = data.config['depthmap_method']
if data.raw_depthmap_exists(shot.id):
logger.info("Using precomputed raw depthmap {}".format(shot.id))
return
logger.info("Computing depthmap for image {0} with {1}".format(
shot.id, method))
de = csfm.DepthmapEstimator()
de.set_depth_range(min_depth, max_depth, 100)
de.set_patchmatch_iterations(data.config['depthmap_patchmatch_iterations'])
de.set_patch_size(data.config['depthmap_patch_size'])
de.set_min_patch_sd(data.config['depthmap_min_patch_sd'])
add_views_to_depth_estimator(data, neighbors, de)
if (method == 'BRUTE_FORCE'):
depth, plane, score, nghbr = de.compute_brute_force()
elif (method == 'PATCH_MATCH'):
depth, plane, score, nghbr = de.compute_patch_match()
elif (method == 'PATCH_MATCH_SAMPLE'):
depth, plane, score, nghbr = de.compute_patch_match_sample()
else:
raise ValueError(
'Unknown depthmap method type '
'(must be BRUTE_FORCE, PATCH_MATCH or PATCH_MATCH_SAMPLE)')
good_score = score > data.config['depthmap_min_correlation_score']
depth = depth * (depth < max_depth) * good_score
# Save and display results
neighbor_ids = [i.id for i in neighbors[1:]]
data.save_raw_depthmap(shot.id, depth, plane, score, nghbr, neighbor_ids)
if data.config['depthmap_save_debug_files']:
image = data.load_undistorted_image(shot.id)
image = scale_down_image(image, depth.shape[1], depth.shape[0])
ply = depthmap_to_ply(shot, depth, image)
with io.open_wt(data._depthmap_file(shot.id, 'raw.npz.ply')) as fout:
fout.write(ply)
def compute_depthmap(arguments):
"""Compute depthmap for a single shot."""
data, graph, reconstruction, neighbors, shot = arguments
if data.raw_depthmap_exists(shot.id):
logger.info("Using precomputed raw depthmap {}".format(shot.id))
return
logger.info("Computing depthmap for image {}".format(shot.id))
min_depth, max_depth = compute_depth_range(graph, reconstruction, shot)
de = csfm.DepthmapEstimator()
de.set_depth_range(min_depth, max_depth, 100)
de.set_patchmatch_iterations(data.config['depthmap_patchmatch_iterations'])
add_views_to_depth_estimator(data, reconstruction, neighbors[shot.id], de)
depth, plane, score = de.compute_patch_match()
good_score = score > data.config['depthmap_min_correlation_score']
depth = depth * (depth < max_depth) * good_score
# Save and display results
data.save_raw_depthmap(shot.id, depth, plane, score)
if data.config['depthmap_save_debug_files']:
image = data.undistorted_image_as_array(shot.id)
image = scale_down_image(image, depth.shape[1], depth.shape[0])
ply = depthmap_to_ply(shot, depth, image)
with open(data._depthmap_file(shot.id, 'raw.npz.ply'), 'w') as fout:
fout.write(ply)
if data.config.get('interactive'):
import matplotlib.pyplot as plt
plt.subplot(2, 2, 1)
plt.imshow(image)
plt.subplot(2, 2, 2)
plt.imshow(color_plane_normals(plane))
plt.subplot(2, 2, 3)
plt.imshow(depth)
plt.colorbar()
plt.subplot(2, 2, 4)
plt.imshow(score)
plt.colorbar()
plt.show()
