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TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch
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| ttach | TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch | |
|---|---|---|
| 1 | 2 | |
| 941 | 531 | |
| - | - | |
| 0.0 | 0.0 | |
| 9 months ago | over 1 year ago | |
| Python | Python | |
| MIT License | - |
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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:
TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch
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Good cameras for computer vision applied to tennis
I'll consider using two cameras, I figured one was enough because this paper gets good results with just that and was planning to use the same/similar network to get the same/similar results but applied to a different sport.
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Deep Learning and Tennis Video annotation
Thanks - there are two models for ball tracking, first one is "coarse" and looks for the approximate position of the ball (using resized image) and the second one is updating coarse coordinates - and looks only at a patch of a high res image. It helped a lot and based on https://github.com/maudzung/TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch
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
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
torchio - Medical imaging toolkit for deep learning
deepsegment - A sentence segmenter that actually works!
Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline
pointnet2 - PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
mmrazor - OpenMMLab Model Compression Toolbox and Benchmark.
DeepLabCut - Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
dgcnn.pytorch - A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)
PaddleViT - :robot: PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+