Pointnet_Pointnet2_pytorch
pointnet
| Pointnet_Pointnet2_pytorch | pointnet | |
|---|---|---|
| 3 | 1 | |
| 3,202 | 4,574 | |
| - | - | |
| 0.0 | 0.0 | |
| 8 days ago | 5 months ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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Pointnet_Pointnet2_pytorch
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Help me understand how to use this PointNet implementation (pytorch, point cloud classification)
here is a sample from one of these log files
I am trying to use this implementation of PointNet (GitHub repo)
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Are the New M1 Macbooks Any Good for Deep Learning? Let’s Find Out
Here you go: https://github.com/yanx27/Pointnet_Pointnet2_pytorch - no need for any custom cuda code.
Note the cuda kernels in the original repo were added in August 2017. It might have been the case at the time they needed them, but again, if you need to do something like that today, you're probably an outlier. Modern DL library have a pretty vast assortment of ops. There have been a few cases in the last couple of years when I thought I'd need write a custom op in cuda (e.g. np.unpackbits) but every time I found a way to implement it with native Pytorch ops.
If you're doing DL/CV research, can you give an example from your own work where you really need to run custom cuda code today?
pointnet
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How do I balance a pointcloud dataset without compromising it?
I am using pointnet, A neural network which directly processes point clouds and labels them on a per-point basis.
What are some alternatives?
tensorflow_macos - TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.
segmentation_models - Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
pointnet2 - PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
dgcnn.pytorch - A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
h-former - H-Former is a VAE for generating in-between fonts (or combining fonts). Its encoder uses a Point net and transformer to compute a code vector of glyph. Its decoder is composed of multiple independent decoders which act on a code vector to reconstruct a point cloud representing a glpyh.
Pix2Vox - The official implementation of "Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images". (Xie et al., ICCV 2019)
AREnets - Tensorflow-based framework which lists attentive implementation of the conventional neural network models (CNN, RNN-based), applicable for Relation Extraction classification tasks as well as API for custom model implementation
RAFT
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
anime-segmentation - high-accuracy segmentation for anime character