VGGPyTorch

A comprehensive tutorial on how to implement and train a VGG model using PyTorch

Demo notebooks

1. Before training the VGG model, please first use the VGG_Preprocessing.ipynb notebook to calculate the channel average value, and channel PCA eigenvectors and eigenvalues on the training dataset, which is required by the data processing and augmentation during training. Copy the results to the traininng notebooks (VGG_Train.ipynb and VGG_Train_w_PreTrainModel.ipynb).
2. To train shallow models, please use the VGG_Train.ipynb notebook.
3. To train deep models, which requires transfering learned paremeters from pretrained models, please start with the VGG_Train.ipynb notebook and then useVGG_Train_w_PreTrainModel.ipynb to transfer learned parameters from pretrained models and perform training.

Tutorial

A step by step tutorial on how to build and train VGG using PyTorch can be found in my blog post (URL: https://jianzhongdev.github.io/VisionTechInsights/posts/implement_train_vgg_pytorch/)

Dependency

This repo has been implemented and tested on the following dependencies:

• Python 3.10.13
• matplotlib 3.8.2
• numpy 1.26.2
• torch 2.1.1+cu118
• torchvision 0.16.1+cu118
• notebook 7.0.6

Computer requirement

This repo has been tested on a laptop computer with the following specs:

• CPU: Intel(R) Core(TM) i7-9750H CPU
• Memory: 32GB
• GPU: NVIDIA GeForce RTX 2060

License

GPL-3.0 license

Reference

[1] Simonyan, K., & Zisserman, A. (2014). Very deep convolutional networks for Large-Scale image recognition. arXiv (Cornell University). https://doi.org/10.48550/arxiv.1409.1556

[2] Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). ImageNet Classification with Deep Convolutional Neural Networks. Neural Information Processing Systems, 25, 1097–1105. https://papers.nips.cc/paper_files/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html

[3] Krizhevsky, A., Nair, V. and Hinton, G. (2014) The CIFAR-10 Dataset. https://www.cs.toronto.edu/~kriz/cifar.html

Citation

If you found this repo helpful, please cite it as:

Zhong, Jian (May 2024). Building and Training VGG with PyTorch: A Step-by-Step Guide. Vision Tech Insights. https://jianzhongdev.github.io/VisionTechInsights/posts/implement_train_vgg_pytorch/.

Or

@article{zhong2024buildtrainVGGPyTorch,
  title   = "Building and Training VGG with PyTorch: A Step-by-Step Guide",
  author  = "Zhong, Jian",
  journal = "jianzhongdev.github.io",
  year    = "2024",
  month   = "May",
  url     = "https://jianzhongdev.github.io/VisionTechInsights/posts/implement_train_vgg_pytorch/"
}