ttach
pointnet2
ttach | pointnet2 | |
---|---|---|
1 | 2 | |
944 | 2,875 | |
- | - | |
0.0 | 0.0 | |
9 months ago | over 1 year ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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ttach
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Setting up Google Colab for Deep Learning
While Colab usually comes pre-installed with most of the basic dependencies like Tensorflow, PyTorch, scikit-learn, pandas and many more, there are chances that you have to install external packages at times. You can do that using the !pip install command. For example we can install the ttach library which is used for augmentation of images during test phase. This can be done using:
pointnet2
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Why does trained model fail on new data?
Is this how you trained the segmentation? https://github.com/charlesq34/pointnet2
- Are the New M1 Macbooks Any Good for Deep Learning? Let’s Find Out
What are some alternatives?
albumentations - Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Pointnet_Pointnet2_pytorch - PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch - Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
dgcnn.pytorch - A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)
deepsegment - A sentence segmenter that actually works!
mmrazor - OpenMMLab Model Compression Toolbox and Benchmark.
RAFT
DeepLabCut - Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
BlenderProc - A procedural Blender pipeline for photorealistic training image generation