File based header detection, collate_per_PC training.
This commit is contained in:
parent
a9bf053794
commit
b7d127e840
@ -287,10 +287,11 @@ class PredictNetPartSegDataset(Dataset):
|
|||||||
Resample raw point cloud to fixed number of points.
|
Resample raw point cloud to fixed number of points.
|
||||||
Map raw label from range [1, N] to [0, N-1].
|
Map raw label from range [1, N] to [0, N-1].
|
||||||
"""
|
"""
|
||||||
def __init__(self, root_dir, transform=None, npoints=2048, headers=True):
|
def __init__(self, root_dir, train=False, transform=None, npoints=2048, headers=True, collate_per_segment=False):
|
||||||
super(PredictNetPartSegDataset, self).__init__()
|
super(PredictNetPartSegDataset, self).__init__()
|
||||||
self.npoints = npoints
|
self.npoints = npoints
|
||||||
self.dataset = ShapeNetPartSegDataset(root=root_dir, train=False, transform=transform, headers=headers)
|
self.dataset = PredictionShapeNet(root=root_dir, train=train, transform=transform,
|
||||||
|
headers=headers, collate_per_segment=collate_per_segment)
|
||||||
|
|
||||||
def __getitem__(self, index):
|
def __getitem__(self, index):
|
||||||
data = self.dataset[index]
|
data = self.dataset[index]
|
||||||
|
@ -5,7 +5,7 @@ import sys
|
|||||||
import os
|
import os
|
||||||
sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/../') # add project root directory
|
sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/../') # add project root directory
|
||||||
|
|
||||||
from dataset.shapenet import ShapeNetPartSegDataset
|
from dataset.shapenet import PredictNetPartSegDataset, ShapeNetPartSegDataset
|
||||||
from model.pointnet2_part_seg import PointNet2PartSegmentNet
|
from model.pointnet2_part_seg import PointNet2PartSegmentNet
|
||||||
import torch_geometric.transforms as GT
|
import torch_geometric.transforms as GT
|
||||||
import torch
|
import torch
|
||||||
@ -28,7 +28,7 @@ if __name__ == '__main__':
|
|||||||
print('Construct dataset ..')
|
print('Construct dataset ..')
|
||||||
test_transform = GT.Compose([GT.NormalizeScale(),])
|
test_transform = GT.Compose([GT.NormalizeScale(),])
|
||||||
|
|
||||||
test_dataset = ShapeNetPartSegDataset(
|
test_dataset = PredictNetPartSegDataset(
|
||||||
root_dir=opt.dataset,
|
root_dir=opt.dataset,
|
||||||
collate_per_segment=False,
|
collate_per_segment=False,
|
||||||
train=False,
|
train=False,
|
||||||
@ -128,12 +128,12 @@ if __name__ == '__main__':
|
|||||||
print('View gt labels ..')
|
print('View gt labels ..')
|
||||||
view_points_labels(points, gt_labels)
|
view_points_labels(points, gt_labels)
|
||||||
|
|
||||||
if True:
|
if False:
|
||||||
print('View diff labels ..')
|
print('View diff labels ..')
|
||||||
print(diff_labels)
|
print(diff_labels)
|
||||||
view_points_labels(points, diff_labels)
|
view_points_labels(points, diff_labels)
|
||||||
|
|
||||||
if True:
|
if False:
|
||||||
print('View pred labels ..')
|
print('View pred labels ..')
|
||||||
print(pred_labels)
|
print(pred_labels)
|
||||||
view_points_labels(points, pred_labels)
|
view_points_labels(points, pred_labels)
|
||||||
|
Loading…
x
Reference in New Issue
Block a user