steffen/Labeling-Primitives-With-Point2Net
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Added normals to prediction DataObject

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Si11ium
2019-08-09 10:25:16 +02:00
parent 4e1fcdfd43
commit 8eb165f76c
7 changed files with 101464 additions and 2060 deletions
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5
main.py
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@ -33,10 +33,10 @@ parser.add_argument('--npoints', type=int, default=1024, help='resample points n
parser.add_argument('--model', type=str, default='', help='model path')
parser.add_argument('--nepoch', type=int, default=250, help='number of epochs to train for')
parser.add_argument('--outf', type=str, default='checkpoint', help='output folder')
parser.add_argument('--labels_within', type=strtobool, default=False, help='defines the label location')
parser.add_argument('--labels_within', type=strtobool, default=True, help='defines the label location')
parser.add_argument('--batch_size', type=int, default=8, help='input batch size')
parser.add_argument('--test_per_batches', type=int, default=1000, help='run a test batch per training batches number')
parser.add_argument('--num_workers', type=int, default=4, help='number of data loading workers')
parser.add_argument('--num_workers', type=int, default=1, help='number of data loading workers')
parser.add_argument('--headers', type=strtobool, default=True, help='if raw files come with headers')
parser.add_argument('--collate_per_segment', type=strtobool, default=True, help='whether to look at pointclouds or sub')
parser.add_argument('--has_variations', type=strtobool, default=False,
@ -129,7 +129,6 @@ if __name__ == '__main__':
net.train()
# ToDo: We need different dataloader here to train the network in multiple iterations, maybe move the loop down
# for dataloader in ...
for batch_idx, sample in enumerate(dataLoader):
# points: (batch_size, n, 3)
# labels: (batch_size, n)