def saliancey2range(resolution_control=0.005):
for j, i in enumerate(f_list):
print(' point cloud is', i)
pc = PointCloud(i)
pc.down_sample(number_of_downsample=2048)
for k in range(4):
if k == 0:
k = -0.5
fig = pc.compute_key_points(percentage=0.1,
show_result=False,
resolution_control=resolution_control,
rate=0.05 * k + 0.05,
use_deficiency=False,
show_saliency=True)
f = mlab.gcf() # this two line for mlab.screenshot to work
f.scene._lift()
img = mlab.screenshot()
mlab.savefig(filename=str(j) + str(k) + '_without.png')
mlab.close()
fig = pc.compute_key_points(percentage=0.1,
show_result=False,
resolution_control=resolution_control,
rate=0.05 * k + 0.05,
use_deficiency=True,
show_saliency=True)
f = mlab.gcf() # this two line for mlab.screenshot to work
f.scene._lift()
img = mlab.screenshot()
mlab.savefig(filename=str(j) + str(k) + '_with.png')
mlab.close()
del pc
def key_points_plot(flist):
for i in flist:
Pc = PointCloud(i)
Pc.down_sample(4096)
fig = Pc.compute_key_points(percentage=0.1,
resolution_control=None,
show_result=True)
f = mlab.gcf() # this two line for mlab.screenshot to work
f.scene._lift()
img = mlab.screenshot()
mlab.savefig(filename=str(i) + 'key_points.png')
mlab.close()
fig = Pc.compute_key_points(percentage=0.1,
resolution_control=0.01,
show_result=True)
f = mlab.gcf() # this two line for mlab.screenshot to work
f.scene._lift()
img = mlab.screenshot()
mlab.savefig(filename=str(i) + 'key_points_with_resolution_ctrl.png')
mlab.close()
def knn_plot(pc_path=''):
f_list = [
base_path + '/' + i for i in os.listdir(base_path)
if os.path.splitext(i)[1] == '.ply'
]
for j, i in enumerate(f_list):
if j < 4:
pc = PointCloud(i)
pc.down_sample(number_of_downsample=4096)
pc.add_noise(factor=0.04)
pc.add_outlier(factor=0.04)
fig = pc.compute_key_points(
percentage=0.02,
resolution_control=1 / 15,
rate=0.05,
use_deficiency=False,
show_result=True) # get the key points id
f = mlab.gcf() # this two line for mlab.screenshot to work
f.scene._lift()
mlab.savefig(filename=str(j) + '_0.png')
mlab.close()
colorset = np.random.random((100, 3))
fig = pc.generate_k_neighbor(k=32,
show_result=True,
colorset=colorset)
f = mlab.gcf() # this two line for mlab.screenshot to work
f.scene._lift()
mlab.savefig(filename=str(j) + '_1.png')
mlab.close()
fig = pc.generate_k_neighbor(k=64,
show_result=True,
colorset=colorset)
f = mlab.gcf() # this two line for mlab.screenshot to work
f.scene._lift()
mlab.savefig(filename=str(j) + '_2.png')
mlab.close()
fig = pc.generate_k_neighbor(k=128,
show_result=True,
colorset=colorset)
f = mlab.gcf() # this two line for mlab.screenshot to work
f.scene._lift()
mlab.savefig(filename=str(j) + '_3.png')
mlab.close()