311-pointnet-deep-learning-on-point-sets-for-3d-classification-and-segmentation
Science Score: 10.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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○DOI references
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✓Academic publication links
Links to: arxiv.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (6.5%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: SZU-AdvTech-2023
- License: mit
- Language: C++
- Default Branch: main
- Size: 635 MB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
PointNet.pytorch
This repo is implementation for PointNet(https://arxiv.org/abs/1612.00593) in pytorch. The model is in pointnet/model.py.
It is tested with pytorch-1.0.
Download data and running
git clone https://github.com/fxia22/pointnet.pytorch
cd pointnet.pytorch
pip install -e .
Download and build visualization tool
cd scripts
bash build.sh #build C++ code for visualization
bash download.sh #download dataset
Training
cd utils
python train_classification.py --dataset <dataset path> --nepoch=<number epochs> --dataset_type <modelnet40 | shapenet>
python train_segmentation.py --dataset <dataset path> --nepoch=<number epochs>
Building
cd utils/nearest_neighbors
python setup.py build_ext --inplace
Testing
cd utils
python show_cls.py --dataset <dataset path> --nepoch=<number epochs> --dataset_type <modelnet40 | shapenet>
python show_seg.py --dataset <dataset path> --nepoch=<number epochs>
Use --feature_transform to use feature transform(T-net).
Links
Owner
- Name: SZU-AdvTech-2023
- Login: SZU-AdvTech-2023
- Kind: organization
- Repositories: 1
- Profile: https://github.com/SZU-AdvTech-2023